CLOSED,TYPE−E
U.S. District Court District of Columbia (Washington, DC) CIVIL DOCKET FOR CASE #: 1:18−cv−02711−DLF

ELECTRONIC PRIVACY INFORMATION CENTER v. UNITED STATES DEPARTMENT OF COMMERCE et al Assigned to: Judge Dabney L. Friedrich Case in other court: 19−05031 Cause: 05:702 Administrative Procedure Act
Plaintiff

Date Filed: 11/20/2018 Date Terminated: 10/03/2019 Jury Demand: None Nature of Suit: 899 Administrative Procedure Act/Review or Appeal of Agency Decision Jurisdiction: U.S. Government Defendant

ELECTRONIC PRIVACY INFORMATION CENTER

represented by Alan Jay Butler ELECTRONIC PRIVACY INFORMATION CENTER 1519 New Hampshire Ave, NW Washington, DC 20036 (202) 483−1140 ext 103 Fax: (202) 483−1248 Email: butler@epic.org ATTORNEY TO BE NOTICED

Marc Rotenberg ELECTRONIC PRIVACY INFORMATION CENTER 1519 New Hampshire Avenue, N.W. Washington, DC 20036 (202) 483−1140, ext 106 Fax: (202) 483−1248 Email: rotenberg@epic.org ATTORNEY TO BE NOTICED

John L. Davisson ELECTRONIC PRIVACY INFORMATION CENTER 1519 New Hampshire Ave, NW Washington, DC 20036 (202) 483−1140 ext. 120 Email: davisson@epic.org ATTORNEY TO BE NOTICED

V.
Defendant
UNITED STATES DEPARTMENT OF COMMERCE

represented by Joseph Evan Borson U.S. DEPARTMENT OF JUSTICE Civil Division, Federal Programs Branch 1100 L Street NW Washington, DC 20005 (202) 514−1944 Fax: (202) 616−8460 Email: joseph.borson@usdoj.gov LEAD ATTORNEY ATTORNEY TO BE NOTICED
Kristina Ann Wolfe U.S. DEPARTMENT OF JUSTICE Civil Division, Federal Programs Branch P.O. Box 883 Ben Franklin Station

Defendant BUREAU OF THE CENSUS

Washington, DC 20044 (202) 353−4519 Email: kristina.wolfe@usdoj.gov LEAD ATTORNEY ATTORNEY TO BE NOTICED
represented by Joseph Evan Borson (See above for address) LEAD ATTORNEY ATTORNEY TO BE NOTICED
Kristina Ann Wolfe (See above for address) LEAD ATTORNEY ATTORNEY TO BE NOTICED

Date Filed 11/20/2018
11/21/2018 11/21/2018 11/21/2018 12/03/2018
12/03/2018 12/03/2018 12/03/2018 01/18/2019
01/18/2019

# Docket Text
1 COMPLAINT against All Defendants ( Filing fee $ 400 receipt number 0090−5802923) filed by ELECTRONIC PRIVACY INFORMATION CENTER. (Attachments: # 1 Civil Cover Sheet, # 2 Summons United States Attorney for the District of Columbia, # 3 Summons Attorney General of the United States, # 4 Summons United States Department of Commerce, # 5 Summons Bureau of the Census)(Davisson, John) (Entered: 11/20/2018)
2 LCvR 26.1 CERTIFICATE OF DISCLOSURE of Corporate Affiliations and Financial Interests by ELECTRONIC PRIVACY INFORMATION CENTER (Davisson, John) (Entered: 11/21/2018)
Case Assigned to Judge Dabney L. Friedrich. (zrdj) (Entered: 11/21/2018)
3 SUMMONS (4) Issued Electronically as to BUREAU OF THE CENSUS, UNITED STATES DEPARTMENT OF COMMERCE, U.S. Attorney and U.S. Attorney General (Attachments: # 1 Notice and Consent)(zrdj) (Entered: 11/21/2018)
4 RETURN OF SERVICE/AFFIDAVIT of Summons and Complaint Executed as to the United States Attorney. Date of Service Upon United States Attorney on 11/26/2018. Answer due for ALL FEDERAL DEFENDANTS by 1/25/2019. (Davisson, John) (Entered: 12/03/2018)
5 RETURN OF SERVICE/AFFIDAVIT of Summons and Complaint Executed. UNITED STATES DEPARTMENT OF COMMERCE served on 11/29/2018 (Davisson, John) (Entered: 12/03/2018)
6 RETURN OF SERVICE/AFFIDAVIT of Summons and Complaint Executed. BUREAU OF THE CENSUS served on 12/3/2018 (Davisson, John) (Entered: 12/03/2018)
7 RETURN OF SERVICE/AFFIDAVIT of Summons and Complaint Executed on United States Attorney General. Date of Service Upon United States Attorney General 11/30/18. (Davisson, John) (Entered: 12/03/2018)
8 MOTION for Preliminary Injunction by ELECTRONIC PRIVACY INFORMATION CENTER (Attachments: # 1 Memorandum in Support, # 2 Text of Proposed Order, # 3 Exhibit List, # 4 Exhibit Nos. 1−4, # 5 Exhibit Nos. 5−9, # 6 Exhibit Nos. 10−14, # 7 Exhibit Nos. 15−19)(Davisson, John) (Entered: 01/18/2019)
MINUTE ORDER. Having reviewed the plaintiff's 8 Motion for Preliminary Injunction, it is ORDERED that the parties shall appear for a preliminary injunction hearing on February 8, 2019 at 11:00 A.M. in Courtroom 12. See LCvR 65.1(d). In accordance with Local Civil Rule 65.1(c), the defendants' opposition, if any, shall be filed within 7 days after service of the motion. Signed by Judge Dabney L. Friedrich on January 18, 2019. (lcdlf1) Modified on 1/22/2019 to reflect updated hearing start time (jl). (Entered: 01/18/2019)

01/22/2019 01/22/2019 01/22/2019
01/23/2019 01/23/2019
01/23/2019 01/30/2019 02/05/2019 02/06/2019
02/06/2019 02/06/2019 02/08/2019 02/08/2019

Set/Reset Deadlines/Hearings: Preliminary Injunction Hearing set for 2/8/2019 at 11:00 AM in Courtroom 12 before Judge Dabney L. Friedrich. (jl). (Entered: 01/22/2019)
9 NOTICE of Appearance by Kristina Ann Wolfe on behalf of BUREAU OF THE CENSUS, UNITED STATES DEPARTMENT OF COMMERCE (Wolfe, Kristina) (Entered: 01/22/2019)
10 MOTION to Stay in Light of the Lapse of Appropriations or, in the Alternative,, MOTION for Extension of Time to File a Response to Plaintiff's Motion for a Preliminary Injunction and to Respond to the Complaint by BUREAU OF THE CENSUS, UNITED STATES DEPARTMENT OF COMMERCE (Attachments: # 1 Text of Proposed Order #1, # 2 Text of Proposed Order #2)(Wolfe, Kristina) (Entered: 01/22/2019)
11 NOTICE of Appearance by Joseph Evan Borson on behalf of BUREAU OF THE CENSUS, UNITED STATES DEPARTMENT OF COMMERCE (Borson, Joseph) (Entered: 01/23/2019)
MINUTE ORDER granting in part and denying in part the defendant's 10 Motion for a Stay in Light of the Lapse of Appropriations or, in the Alternative, an Extension of Time to File a Response to Plaintiff's Motion for a Preliminary Injunction and to Respond to the Complaint. Accordingly, it is ORDERED that the defendant's request for a stay is DENIED. It is further ORDERED that (1) the defendant shall file its response to the plaintiff's motion on or before January 30, 2019, (2) the plaintiff shall file its reply on or before February 5, 2019, and (3) the defendant shall file its answer or other response to the plaintiff's complaint within 30 days after the Court's resolution of the plaintiff's motion for a preliminary injunction. The preliminary injunction hearing will take place as scheduled on February 8, 2019 at 11:00 A.M. Signed by Judge Dabney L. Friedrich on January 23, 2019. (lcdlf1) (Entered: 01/23/2019)
Set/Reset Deadlines/Hearings: Defendant's response to plaintiff's motion due by 1/30/2019. Plaintiff's reply due by 2/5/2019. (jl) (Entered: 01/23/2019)
12 Memorandum in opposition to re 8 MOTION for Preliminary Injunction filed by BUREAU OF THE CENSUS, UNITED STATES DEPARTMENT OF COMMERCE. (Attachments: # 1 Declaration of Robin J. Bachman, # 2 Exhibit A to Bachman Decl., # 3 Exhibit B to Bachman Decl., # 4 Text of Proposed Order)(Borson, Joseph) (Entered: 01/30/2019)
13 REPLY to opposition to motion re 8 MOTION for Preliminary Injunction filed by ELECTRONIC PRIVACY INFORMATION CENTER. (Davisson, John) (Entered: 02/05/2019)
MINUTE ORDER. Local Civil Rule 65.1(d) requires the Court to hold a hearing within 21 days of an application for a preliminary injunction upon the request of the moving party "unless the Court earlier decides the motion on the papers." LCvR 65.1(d). Having reviewed the parties' briefs, the Court intends to decide the plaintiff's 8 Motion for Preliminary Injunction on the papers and issue a decision on or before February 8, 2019. Accordingly, it is ORDERED that the preliminary injunction hearing currently set for February 8, 2019 is VACATED. Signed by Judge Dabney L. Friedrich on February 6, 2019. (lcdlf1) (Entered: 02/06/2019)
14 NOTICE of Appearance by Marc Rotenberg on behalf of ELECTRONIC PRIVACY INFORMATION CENTER (Rotenberg, Marc) (Entered: 02/06/2019)
15 NOTICE of Appearance by Alan Jay Butler on behalf of ELECTRONIC PRIVACY INFORMATION CENTER (Butler, Alan) (Entered: 02/06/2019)
16 ORDER denying the plaintiff's 8 Motion for a Preliminary Injunction. See text for details. Signed by Judge Dabney L. Friedrich on February 8, 2019. (lcdlf1) (Entered: 02/08/2019)
17 MEMORANDUM OPINION regarding the plaintiff's 8 Motion for a Preliminary Injunction. See text for details. Signed by Judge Dabney L. Friedrich on February 8, 2019. (lcdlf1) (Entered: 02/08/2019)

02/12/2019
02/13/2019 02/21/2019 03/11/2019 03/14/2019 03/14/2019
03/14/2019 04/01/2019 04/11/2019 09/03/2019 10/02/2019 10/03/2019

18 NOTICE OF APPEAL TO DC CIRCUIT COURT as to 16 Order on Motion for Preliminary Injunction by ELECTRONIC PRIVACY INFORMATION CENTER. Filing fee $ 505, receipt number 0090−5942771. Fee Status: Fee Paid. Parties have been notified. (Davisson, John) (Entered: 02/12/2019)
19 Transmission of the Notice of Appeal, Order Appealed (Memorandum Opinion), and Docket Sheet to US Court of Appeals. The Court of Appeals fee was paid this date 2/12/19 re 18 Notice of Appeal to DC Circuit Court,. (ztd) (Entered: 02/13/2019)
USCA Case Number 19−5031 for 18 Notice of Appeal to DC Circuit Court, filed by ELECTRONIC PRIVACY INFORMATION CENTER. (zvt) (Entered: 02/25/2019)
20 MOTION to Dismiss by BUREAU OF THE CENSUS, UNITED STATES DEPARTMENT OF COMMERCE (Attachments: # 1 Memorandum in Support, # 2 Text of Proposed Order)(Wolfe, Kristina) (Entered: 03/11/2019)
21 Unopposed MOTION to Modify Briefing Schedule by BUREAU OF THE CENSUS, UNITED STATES DEPARTMENT OF COMMERCE (Attachments: # 1 Text of Proposed Order)(Borson, Joseph) (Entered: 03/14/2019)
MINUTE ORDER granting the defendants' 21 Unopposed Motion to Modify Briefing Schedule. Accordingly, it is ORDERED that the plaintiff shall file its response to the defendants' motion to dismiss on or before April 1, 2019 and the defendants shall file their reply on or before April 11, 2019. Signed by Judge Dabney L. Friedrich on April 14, 2019. (lcdlf1) (Entered: 03/14/2019)
Set/Reset Deadlines/Hearings: Response due by 4/1/2019. Reply due by 4/11/2019. (zcdw) (Entered: 03/18/2019)
22 Memorandum in opposition to re 20 MOTION to Dismiss filed by ELECTRONIC PRIVACY INFORMATION CENTER. (Attachments: # 1 Text of Proposed Order)(Davisson, John) (Entered: 04/01/2019)
23 REPLY to opposition to motion re 20 MOTION to Dismiss filed by BUREAU OF THE CENSUS, UNITED STATES DEPARTMENT OF COMMERCE. (Wolfe, Kristina) (Entered: 04/11/2019)
24 NOTICE of Change of Address by John L. Davisson (Davisson, John) (Entered: 09/03/2019)
25 MANDATE of USCA as to 18 Notice of Appeal to DC Circuit Court, filed by ELECTRONIC PRIVACY INFORMATION CENTER ; USCA Case Number 19−5031. (Attachments: # 1 USCA Judgment)(zrdj) (Entered: 10/04/2019)
MINUTE ORDER. On June 28, 2019, the U.S. Court of Appeals for the D.C. Circuit reviewed this Court's denial of Epic's motion for a preliminary injunction. See Elec. Privacy Info. Ctr. v. U.S. Dep't of Commerce and Bureau of the Census, 928 F.3d 95 (D.C. Cir. 2019). The Circuit held "that EPIC lacks standing as a matter of law." Id. at 104. On that ground, it vacated this Court's denial of the preliminary injunction and remanded "for the purpose of dismissal." Id. at 105. On October 2, 2019, the mandate from the Circuit issued. As such, this case is DISMISSED for lack of jurisdiction. The Clerk of Courts is directed to close this case. So Ordered by Judge Dabney L. Friedrich on October 3, 2019. (lcdlf1) (Entered: 10/03/2019)

 
 Case 1:18-cv-02711 Document 1 Filed 11/20/18 Page 1 of 28

IN THE UNITED STATES DISTRICT COURT FOR THE DISTRICT OF COLUMBIA

ELECTRONIC PRIVACY INFORMATION CENTER 1718 Connecticut Avenue, N.W., Suite 200 Washington, D.C. 20009
Plaintiff,
v.
UNITED STATES DEPARTMENT OF COMMERCE, 1401 Constitution Avenue, N.W. Washington, D.C. 20230
BUREAU OF THE CENSUS, 4600 Silver Hill Road Suitland, Md. 20746
Defendants.

Civ. Action No. _ 18-2711

COMPLAINT FOR INJUNCTIVE RELIEF 1. This is an action under the Administrative Procedure Act (“APA”), 5 U.S.C. §§ 551–706; the E-Government Act of 2002, Pub. L. 107-347, 116 Stat. 2899 (codified as amended at 44 U.S.C. § 3501 note); and the Declaratory Judgment Act, 28 U.S.C. § 2201(a), to secure the creation and publication of multiple Privacy Impact Assessments (“PIAs”) from the United States Department of Commerce and the Bureau of the Census. 2. The Electronic Privacy Information Center (“EPIC”) seeks the release of certain Privacy Impact Assessments pertaining to the Defendants’ attempted collection of personal data concerning citizenship status by means of the 2020 Census.

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Jurisdiction and Venue 3. This Court has subject matter jurisdiction over this action under 28 U.S.C. § 1331, 5 U.S.C. § 702, and 5 U.S.C. § 704. This Court has personal jurisdiction over the Department of Commerce and the Census Bureau. 4. Venue is proper in this district under 5 U.S.C. § 703 and 28 U.S.C. § 1391.
Parties 5. Plaintiff Electronic Privacy Information Center is a non-profit, public interest research center established in 1994 to focus public attention on emerging privacy and civil liberties issues. Central to EPIC’s mission is oversight of government activities that impact individual privacy, free expression, and democratic values.1 EPIC has a particular interest in preserving legal privacy protections for personal data, including those established in the E-Government Act. 6. EPIC maintains one of the most popular privacy websites in the world, epic.org, which provides the public with information about emerging privacy and civil liberties issues. EPIC also provides a wide range of publications through the EPIC Bookstore.2 7. EPIC has a robust open government practice and routinely disseminates to the public information obtained under the Freedom of Information Act (“FOIA”), the E-Government Act, and other federal and state transparency statutes. EPIC makes this information available through the EPIC website, the biweekly EPIC Alert newsletter, and various news organizations. 8. EPIC has brought numerous successful cases seeking the release of Privacy Impact Assessments. In EPIC v. DHS, 926 F. Supp. 2d 311 (D.D.C. 2013), EPIC obtained a PIA and related records concerning an effort by the Department of Homeland Security to track social
1 See EPIC, About EPIC (2018), https://epic.org/epic/about.html. 2 EPIC, EPIC Bookstore (2018), https://epic.org/bookstore/.
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media users and journalists.3 EPIC made the previously undisclosed documents available to the public through the EPIC website. In EPIC v. FBI, 235 F. Supp. 3d 207 (D.D.C. 2017), EPIC obtained unpublished PIAs from the Federal Bureau of Investigation concerning facial recognition technology, which EPIC also made available to the public through the EPIC website.4 In EPIC v. DEA, 208 F. Supp. 3d 108 (D.D.C. 2016), EPIC learned that the Drug Enforcement Administration had failed to produce PIAs for the agency’s license plate reader program, a telecommunications records database, and other systems of public surveillance.5 EPIC reported the agency’s failure to produce a PIA through the EPIC website.6 In EPIC v. Presidential Advisory Commission on Election Integrity, 266 F. Supp. 3d 297 (D.D.C.), aff'd on other grounds, 878 F.3d 371 (D.C. Cir. 2017), EPIC challenged the failure of the Presidential Advisory Commission on Election Integrity to undertake and publish a PIA prior to the collection of state voter data.7 EPIC’s suit led the Commission to suspend data collection, discontinue the use of an unsafe computer server, and delete voter information that had been illegally obtained.8 And in EPIC v. DHS, No. 18-1268 (D.D.C. filed May 30, 2018), EPIC is currently challenging the failure of the Department of Homeland Security to publish a PIA for a system designed to track journalists, bloggers, and social media users.9 EPIC’s suit revealed that
3 See EPIC, EPIC v. Department of Homeland Security: Media Monitoring (2015), https://www.epic.org/foia/epic-v-dhs-media-monitoring/. 4 See EPIC, EPIC v. FBI – Privacy Assessments (2016), https://epic.org/foia/fbi/pia/. 5 See EPIC, EPIC v. DEA – Privacy Impact Assessments (2016), https://epic.org/foia/dea/pia/. 6 See id. 7 See EPIC, EPIC v. Presidential Election Commission (2018), https://epic.org/privacy/litigation/voter/epic-v-commission/. 8 Id. 9 See EPIC, EPIC v. DHS (Media Monitoring Services) (2018), https://epic.org/foia/dhs/mediamonitoring-services/.
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the DHS had unlawfully failed to conduct a PIA prior to developing the “Media Monitoring” system.10 9. EPIC has long advocated for robust privacy protections for census respondents. EPIC was directly involved in the 2004 effort to revise the Census Bureau “sensitive data” policy after an EPIC FOIA lawsuit revealed that the DHS had acquired data on Arab Americans from the Census Bureau after 9/11.11 In formal comments to the Census Bureau this year, EPIC opposed the decision to add a citizenship question to the 2020 census.12 Through a recent FOIA request, EPIC also uncovered emails from Kansas Secretary of State Kris Kobach urging Commerce Secretary Wilbur Ross, on the direction of Chief White House Strategist Steve Bannon, to add a citizenship question to the 2020 Census.13 10. EPIC is a dues-paying membership organization, as set forth in the EPIC Articles of Incorporation14 and the EPIC Bylaws.15 EPIC is governed by a Board of Directors, all of whom “must be Members of” EPIC.16
10 Id. 11 EPIC, Department of Homeland Security Obtained Data on Arab Americans From Census Bureau (2004), https://epic.org/privacy/census/foia/. 12 See EPIC, Comments of the Electronic Privacy Information Center to the U.S. Census Bureau: 2020 Census (Aug. 7, 2018), https://epic.org/apa/comments/EPIC-Census-2020-August2018.pdf. 13 EPIC, EPIC FOIA: EPIC Obtains Documents About Decision to Add Census Citizenship Question (2018), https://epic.org/2018/06/epic-foia-epic-obtains-documen.html. 14 EPIC, Articles of Incorporation (2018) (“The Corporation [EPIC] . . . may refer to people as ‘members’ pursuant to D.C. Code § 29-404.01, and the qualifications, rights, and privileges of such people shall be as set forth in the bylaws.”). 15 EPIC, Bylaws of the Electronic Privacy Information Center § 2.02 (as amended Jan. 26, 2018), https://epic.org/epic/bylaws.pdf [hereinafter “EPIC Bylaws”]. 16 EPIC Bylaws § 2.02.
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11. EPIC’s Members are “distinguished experts in law, technology, and public policy.”17 New Members are designated by EPIC following “nomination by the current Members and a vote of the Board [of Directors.]”18 12. Defendant United States Department of Commerce is a federal agency under 5 U.S.C. § 551(1) and 44 U.S.C. § 3502(1).19 The Department of Commerce is headquartered in Washington, D.C. 13. The Bureau of the Census is a federal agency under 5 U.S.C. § 551(1) and 44 U.S.C. § 3502(1).20 The Census Bureau is an agency within the Department of Commerce and is headquartered in Suitland, Md.
Facts The Defendants’ Obligation to Conduct and Publish Privacy Impact Assessments 14. Under section 208 of the E-Government Act, federal agencies—including the Department of Commerce and the Census Bureau—are required to “conduct,” “ensure the review of,” and “make . . . publicly available” a Privacy Impact Assessment before “initiating a new collection of information” that will be digitally stored or transmitted “in an identifiable form.”21 Information is in an identifiable form if it “permits the identity of an individual to whom the information applies to be reasonably inferred by either direct or indirect means.”22 This includes “combination[s] of gender, race, birth date, geographic indicator, and other descriptors” that would permit
17 EPIC Bylaws § 5.01. 18 Id. 19 See 15 U.S.C. § 1501 (“There shall be at the seat of government an executive department to be known as the Department of Commerce[.]”). 20 See 13 U.S.C. § 2 (“The Bureau is continued as an agency within, and under the jurisdiction of, the Department of Commerce.”). 21 E-Government Act § 208(b)(1). 22 Id. § 208(d).
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individuals to be uniquely identified, even in the absence of names, social security numbers, or other direct identifiers.23
15. The Office of Budget and Management (“OMB”), which oversees enforcement of the E-
Government Act government-wide, defines a PIA as:
[A]n analysis of how information is handled: (i) to ensure handling conforms to applicable legal, regulatory, and policy requirements regarding privacy, (ii) to determine the risks and effects of collecting, maintaining and disseminating information in identifiable form in an electronic information system, and (iii) to examine and evaluate protections and alternative processes for handling information to mitigate potential privacy risks.24
16. Section 208, in mandating that a PIA be conducted and published before an agency
collects personally identifiable information, serves Congress’s dual objectives of “mak[ing] the
Federal Government more transparent and accountable,” and “ensur[ing] sufficient protections
for the privacy of personal information as agencies implement citizen-centered electronic Government.”25
17. As the Census Bureau emphasizes in the Bureau’s Policy on Conducting Privacy Impact
Assessments, “PIAs are an important tool for assuring Census Bureau census and survey
respondents, other agencies from whom we receive data, and the taxpayer, that the Census Bureau is minimizing privacy impacts and ensuring data confidentiality and security.”26
18. To satisfy section 208, a PIA must specify, inter alia, “what information is to be
collected”; “why the information is being collected”; “the intended use [by] the agency of the
23 Joshua B. Bolten, Dir., Office of Mgmt. & Budget, Executive Office of the President, M03-22, Memorandum for Heads of Executive Departments and Agencies, Attachment A § II.A.2 (Sept. 26, 2003), https://georgewbush-whitehouse.archives.gov/omb/memoranda/m03-22.html [hereinafter OMB Guidance]. 24 OMB Guidance § II.A.6. 25 E-Government Act §§ 2(b)(9), 208(a). 26 U.S. Census Bureau, Policy on Conducting Privacy Impact Assessments 2 (Nov. 16, 2005), https://www2.census.gov/foia/ds_policies/ds019.pdf [hereinafter Census Bureau PIA Policy].
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information”; “with whom the information will be shared”; “what notice or opportunities for consent would be provided”; and “how the information will be secured.”27 Additionally, a PIA “must identify what choices the agency made regarding an IT system or collection of information as a result of performing the PIA.”28 19. A PIA must be “commensurate with the size of the information system being assessed, the sensitivity of information that is in an identifiable form in that system, and the risk of harm from unauthorized release of that information[.]”29 As the OMB instructs, “The depth and content of the PIA should be appropriate for the nature of the information to be collected and the size and complexity of the IT system.”30 20. The OMB also underscores that “[a]gencies must consider the information ‘life cycle’ (i.e., collection, use, retention, processing, disclosure and destruction) in evaluating how information handling practices at each stage may affect individuals’ privacy. To be comprehensive and meaningful, privacy impact assessments require collaboration by program experts as well as experts in the areas of information technology, IT security, records management and privacy.” 21. Where a PIA is required for a “major information system,” the PIA should “reflect more extensive analyses of: 1. the consequences of collection and flow of information, 2. the alternatives to collection and handling as designed, 3. the appropriate measures to mitigate risks identified for each alternative and, 4. the rationale for the final design choice or business process.”31 A “major information system” includes any “system or project that requires special
27 E-Government Act § 208(b)(2)(B)(ii). 28 OMB Guidance § II.C.1.b. 29 E-Government Act § 208(b)(2)(B)(i). 30 OMB Guidance § II.C.2.a. 31 OMB Guidance § II.C.2.a.ii.
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management attention because of its: (i) importance to the agency mission, (ii) high development, operating and maintenance costs, (iii) high risk, (iv) high return, (v) significant role in the administration of an agency’s programs, finances, property or other resources.”32 In these circumstances, a mere “checklist or template” will not satisfy an agency’s PIA obligation.33 22. The Census Bureau further mandates that a PIA “cover the risks and effects of collecting, maintaining, and disseminating information in identifiable form in an electronic information system. A PIA must evaluate the protections and alternative processes for handling information to mitigate potential privacy risks.”34 23. According to the OMB, “Agencies should commence a PIA when they begin to develop a new or significantly modified [information technology] system or information collection[.]”35 Thus, when an agency intends to “develop[] . . . projects that collect, maintain or disseminate information in identifiable form from or about members of the public,” the agency must first conduct a PIA.36 24. But an agency’s privacy obligations under the E-Government Act do not end with the initial publication of a Privacy Impact Assessment. Rather, a PIA must be revised continually “to reflect changed information collection authorities, business processes or other factors affecting the collection and handling of information in identifiable form.”37 Specifically, a PIA must be “updated as necessary where a system change creates new privacy risks,” including “when new
32 OMB Guidance § II.A.4. 33 OMB Guidance § II.C.2.a.iii. 34 Census Bureau PIA Policy 2. 35 OMB Guidance § II.C.2 (emphasis added). 36 OMB Guidance § II.B.1.a. 37 OMB Guidance § II.B.4; accord U.S. Dep’t of Commerce, Office of Privacy & Open Gov’t, Privacy Compliance (July 9, 2018), http://www.osec.doc.gov/opog/privacy/compliance.html [hereinafter Commerce Dep’t Privacy Compliance]; Census Bureau PIA Policy 2.
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information in identifiable form added to a collection raises the risks to personal privacy (for example, the addition of health or financial information)”; “when agencies work together on shared functions involving significant new uses or exchanges of information in identifiable form”; and “when agencies adopt or alter business processes so that government databases holding information in identifiable form are merged, centralized, matched with other databases or otherwise significantly manipulated.”38 25. Compliance with section 208 is an essential step to fulfilling the U.S. Census Bureau Privacy Principles.39 Under those principles, the Census Bureau has committed to “only collect information that is necessary for meeting the Census Bureau’s mission and legal requirements”; to “be open about its programs, policies and practices to collect and protect identifiable data used to produce statistical information”; to “make it easy to access information about what [the Bureau] collect[s] and why”; and to “be considerate of respondents’ time and desire for privacy.”40
The Defendants’ Collection of Personal Data Concerning Citizenship Status 26. In order to determine the apportionment of representatives “among the several States,” the Census Clause of the U.S. Constitution, as amended, requires that an “actual Enumeration” of persons be undertaken every ten years “in such Manner as [Congress] shall by Law direct.”41
38 OMB Guidance §§ II.B.2.d, g, i; accord Commerce Dep’t Privacy Compliance. 39 U.S. Census Bureau, U.S. Census Bureau Privacy Principles (2006), https://www2.census.gov/foia/ds_policies/ds0pp.pdf. 40 Id. at 1–2. 41 U.S. Const. art. 1, § 2, cl. 3; see also U.S. Const. amend. XIV, § 2 (“Representatives shall be apportioned among the several States according to their respective numbers, counting the whole number of persons in each State, excluding Indians not taxed.”).
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27. In furtherance of the Census Clause, Congress has directed the Secretary of Commerce to “take a decennial census of population”42 and to “determine the inquiries, and the number, form, and subdivisions” of the questionnaires to be used in the Census. 28. Congress has also established the Census Bureau as an agency under the Department of Commerce.43 The Census Bureau will administer the next Census in 2020.44 29. By law, any person who refuses to answer “any of the questions . . . submitted to him in connection with any census”—or who willfully gives a false answer to a census question—is subject to criminal penalties.45 30. On March 26, 2018, Secretary of Commerce Wilbur Ross disclosed in an intra-agency letter that he “ha[d] determined that reinstatement of a citizenship question on the 2020 decennial census [wa]s necessary” and that he was “directing the Census Bureau to place the citizenship question last on the decennial census form.”46 No such question appeared on the 2010 Census,47 nor has the Census Bureau posed a citizenship question to all census respondents since the 1950 Census.48
42 13 U.S.C. § 141(a). 43 15 U.S.C. § 1501. 44 See U.S. Census Bureau, 2020 Census (Oct. 19, 2018), https://www.census.gov/programssurveys/decennial-census/2020-census.html. 45 13 U.S.C. § 221(a)–(b). 46 Letter from Wilbur Ross, Secretary of Commerce, to Karen Dunn Kelley, Under Secretary for Economic Affairs, at 8 (March 26, 2018), available at https://www.scribd.com/document/374971353/Reinstatement-of-a-Citizenship-Question-on-the2020-Decennial-Census-Questionnaire [hereinafter Ross Letter]. 47 U.S. Census Bureau, History: 2010 (July 18, 2017), https://www.census.gov/history/www/through_the_decades/index_of_questions/2010.html. 48 Tamara Keith, FACT CHECK: Has Citizenship Been A Standard Census Question?, NPR (Mar. 27, 2018), https://www.npr.org/2018/03/27/597436512/fact-check-has-citizenship-been-astandard-census-question.
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31. Secretary Ross stated that the decision to add the citizenship question was in response to
a December 2017 request by the Department of Justice (“DOJ”),49 which purportedly sought
citizenship data to enable “more effective enforcement” of the Voting Rights Act.50 The DOJ’s
request raised alarm and opposition from members of the U.S. Senate,51 the attorneys general of
at least twenty states,52 and numerous mayors from across the country.53 Moreover, Secretary
Ross’s explanation for his decision is at odds with his subsequent statement that he
communicated with Chief White House strategist Steve Bannon and Kansas Secretary of State
Kris Kobach about the citizenship question months before the DOJ made a request.54
49 Letter from Arthur E. Gary, Gen. Counsel, Justice Mgmt. Div., Dep’t of Justice, to Ron Jamin, U.S. Census Bureau (Dec. 12, 2017), available at https://www.documentcloud.org/documents/4340651-Text-of-Dec-2017-DOJ-letter-toCensus.html [hereinafter DOJ Letter]. 50 Ross Letter at 1. 51 Letter from Sen. Dianne Feinstein et al. to Wilbur Ross, Secretary of Commerce (Jan. 5, 2018), https://www.feinstein.senate.gov/public/_cache/files/3/7/376f8dcd-7f35-4913-9e80cd1e48e3b312/7E4C59B2988E2CC14866543EDD7E01A6.2018.01.05-census-citizeshipletter.pdf. 52 Letter from Attorneys General of Twenty U.S. States to Wilbur Ross, Secretary of Commerce (Feb. 12, 2018), available at https://www.brennancenter.org/sites/default/files/legal-work/MultiState-Attorney-General-Letter-re-2020-Census.pdf. 53 U.S. Conference of Mayors, Nation’s Mayors to Secretary Ross: Don’t Politicize Census. Remove the Citizenship Question (Mar. 27, 2018), https://www.usmayors.org/2018/03/27/nations-mayors-to-secretary-ross-dont-politicize-censusremove-the-citizenship-question/. 54 Defs.’ Second Suppl. Resps. to Pls.’ First Set of Interrogatories 2–3, N.Y. Immigration Coal. v. U.S. Dep’t of Commerce, 18-5025 (Oct. 11, 2018), available at https://ag.ny.gov/sites/default/files/second_supp_res_to_rog_1_final_2018.10.11.pdf; see also Email from Kris Kobach, Sec’y, Kan. Dep’t of State, to Wilbur Ross, Sec’y, Dep’t of Commerce (Jul. 21, 2017), https://epic.org/foia/censusbureau/EPIC-18-03-22-Census-Bureau-FOIA20180611-Production-Kobach-Emails.pdf.
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32. On March 28, 2018, the Census Bureau reported to Congress the Bureau’s intention to add a citizenship question to the 2020 Census.55 The question was drafted as follows:56
33. The Census Bureau reported to Congress that the “question about a person’s citizenship [would be] used to create statistics about citizen and noncitizen populations” and stated that “[t]hese statistics are essential for enforcing the Voting Rights Act and its protections against voting discrimination.”57 34. The Bureau falsely implied that a citizenship question has been continuously asked on the census since 1890,58 when in fact it has been nearly 70 years since the Bureau asked for the citizenship status of all census respondents.59 As the Pew Research Center states plainly, “[f]or
55 U.S. Census Bureau, Questions Planned for the 2020 Census and American Community Survey 7 (March 2018), https://www2.census.gov/library/publications/decennial/2020/operations/planned-questions2020-acs.pdf. 56 Id. 57 Id. (capitalization altered). 58 Id. at 7 n.1 (“Citizenship asked 1820, 1830, 1870, and 1890 to present.”). 59 See Catherine E. Shoichet, Why putting a citizenship question on the census is a big deal, CNN (Mar. 28, 2018), https://www.cnn.com/2018/03/27/politics/census-citizenship-questionexplainer/index.html.
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the first time since 1950, the U.S. Census Bureau is planning to ask everyone living in the United States whether they are citizens when it conducts its next decennial census in 2020.”60
The Privacy Implications of Collecting Personal Data Concerning Citizenship Status 35. As the Supreme Court recognized in Baldrige v. Shapiro: “Although Congress has broad power to require individuals to submit responses, an accurate census depends in large part on public cooperation. To stimulate that cooperation Congress has provided assurances that information furnished . . . by individuals is to be treated as confidential.”61 36. The Census Bureau’s collection of personally identifiable information carries inherent privacy risks, but the addition of a citizenship question on the 2020 Census presents unique threats to privacy, personal security, and the accuracy of the United States Census. 37. The citizenship question would compel the release of respondents’ citizenship and immigration status, potentially exposing individuals and their family members to investigation, sanction, and deportation.62 38. Indeed, Secretary Ross’s stated basis for adding the citizenship question was to provide the DOJ with “census block level citizen voting age population (“CVAP”) data.”63 The DOJ has also called on the Bureau to publicly “release this new data regarding citizenship at the same time it releases the other redistricting data[.]”64 39. Moreover, the most recent Privacy Impact Assessment for CEN08—a key Census Bureau division which “process[es] response data from census tests and 2020 Census operations”—
60 D’Vera Cohen, What to Know About the Citizenship Question the Census Bureau is Planning to Ask in 2020, Pew Research Center (Mar. 30, 2018). 61 Baldrige v. Shapiro, 455 U.S. 345, 354 (1982). 62 U.S. Dep’t of Commerce, U.S. Census Bureau, QuickFacts (2017), https://www.census.gov/quickfacts/fact/table/US/AGE775217. 63 Ross Letter at 1; see also DOJ Letter at 1. 64 DOJ Letter at 3.
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states, for the first time, that the Bureau is “collecting, maintaining, or disseminating” personally identifiable information through CEN08 “[f]or criminal law enforcement activities”:65
The CEN08 PIA specifically notes that “[c]itizenship” status is among the “personally identifiable information . . . collected, maintained, or disseminated” by CEN08 (though the PIA fails completely to assess the privacy implications of handling that data):66
40. This admission in the CEN08 PIA is consistent with a June 12, 2018 email exchange between Department of Justice officials, disclosed in the course of litigation against Secretary Ross,67 in which the officials “privately discussed the possibility that in the future census information could be shared with law enforcement.”68
65 U.S. Dep’t of Commerce, Privacy Impact Assessment for the CEN08 Decennial Information Technology Division (DITD) 1, 7 (approved Sep. 28, 2018), http://www.osec.doc.gov/opog/privacy/Census%20PIAs/CEN08_PIA_SAOP_Approved.pdf. 66 Id. at 5. 67 Decl. of Andrew Case in Supp. of Pls.’ Opp’n to Defs.’ Mot. Summ. J. at Ex. B, San Jose v. Ross, 18-2279 (N.D. Cal. Filed Nov. 16, 2018), available at https://assets.documentcloud.org/documents/5193403/Nov-16-2018-Declaration-of-AndrewCase-in.pdf. 68 Tara Bahrampour, Trump administration officials suggested sharing census responses with law enforcement, court documents show, Wash. Post (Nov. 19, 2018), https://www.washingtonpost.com/local/social-issues/trump-administration-officials-suggested-
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41. Transmitting personal data concerning citizenship status to the Department of Justice or other law enforcement agencies would violate the Bureau’s statutory obligation not to disclose “personally identifiable information about an individual to any other individual or agency until 72 years after it was collected for the decennial census.”69 42. Even if citizenship data were “deidentified” before dissemination, there is a material risk of reidentification. As Dr. Latanya Sweeney has demonstrated, the “practice of de-identifying data and of ad hoc generalization” used by the Census Bureau is “not sufficient to render data anonymous because combinations of attributes often combine uniquely to re-identify individuals.”70 Using Census summary data and information from other readily available sources at the time, Dr. Sweeney “found that 87% . . . of the population in the United States had reported characteristics that likely made them unique based only on {5-digit ZIP, gender, date of birth}.”71 Recent work by the National Academies of Sciences suggests that privacy-preserving techniques and privacy enhancing techniques could provide more robust approaches for deidentification, but the Census Bureau has given no indication that it will use such techniques with respect to personal data concerning citizenship status.72
sharing-census-responses-with-law-enforcement-court-documents-show/2018/11/19/41679018ec46-11e8-8679-934a2b33be52_story.html. 69 Pub. L. 94-416, 92 Stat. 915 (Oct. 5, 1978) (codified in relevant part at 44 U.S.C. § 2108); see also U.S. Dep’t of Commerce, U.S. Census Bureau, The “72-Year Rule” (2018), https://www.census.gov/history/www/genealogy/decennial_census_records/the_72_year_rule_1. html. 70 Latanya Sweeney, Simple Demographics Often Identify People Uniquely 2 (Carnegie Mellon Univ., Data Privacy Working Paper No. 3, 2000), https://dataprivacylab.org/projects/identifiability/paper1.pdf. 71 Id. 72 See Nat’l Academies of Sciences, Engineering, & Medicine, Federal Statistics, Multiple Data Sources, and Privacy Protection: Next Steps (2017), https://www.nap.edu/catalog/24893/federalstatistics-multiple-data-sources-and-privacy-protection-next-steps.
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43. Historically, the misuse of census data has caused grave harm to certain populations.73
For example, the 1910 census law prohibited the use of information supplied by businesses for
non-statistical, non-census purposes, but there was no such prohibition regarding individual citizen data.74 As a result, during World War I, the Census Bureau did in fact disclose census records to the Department of Justice and local draft boards to help enforce the draft.75 Similarly,
in 1920, the Department of Justice requested census data about individuals’ citizenship for use in deportation cases.76
44. In 1930, Congress passed a census law that would become known as Title 13, which prohibited the Census Bureau from publishing any data identifying individuals.77 However, the
Second War Powers Act weakened this restriction and permitted the Census Bureau in 1943 to
provide the U.S. Secret Service with the names, addresses, occupations, and citizenship status of every Japanese American residing in the Washington, D.C. area.78 The Census Bureau also
provided the War Department with census-block level data on Japanese Americans residing in western states to facilitate their internment.79
45. In 2004, an EPIC FOIA lawsuit revealed that the Census Bureau had provided the
Department of Homeland Security with a list of cities containing more than 1,000 Arab-
73 See, e.g., Lutz. K. Berkner, Review: The Use and Misuse of Census Data for the Historical Analysis of Family Structure, 5 J. Interdisciplinary Hist. 721 (1975). 74 Act of Jul. 2, 1909 (to provide for the expenses of the Thirteenth December Census, and for other purposes), ch. 2, § 25, 36 Stat. 1, 9. 75 Margo Anderson & William Seltzer, Challenges to the Confidentiality of U.S. Federal Statistics, 1910-1965, 23 J Official Stat. 1, 6–7 (2007). 76 Id. at 8–9. 77 Act of Jun. 18, 1929 (to provide for the fifteenth and subsequent decennial censuses and to provide for apportionment of Representatives in Congress), ch. 28, § 11, 46 Stat. 21, 25. 78 Margo Anderson & William Seltzer, Census Confidentiality Under the Second War Powers Act (1942- 1947) at 16 (Mar. 29-31, 2007) (unpublished manuscript). 79 Comm’n on Wartime Relocation and Internment of Civilians, Personal Justice Denied 104-05 (1982).
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American residents and a zip-code level breakdown of Arab-American populations throughout
the United States, sorted by country of origin.80 While the Census Bureau and Customs and
Border Protection revised their data request policies following EPIC’s FOIA case,81 many
Americans are justifiably fearful that their census responses will be used against them by other
federal agencies, which can lead individuals to provide false or incomplete information.
46. The disclosure of personal data collected for census tabulation to other agencies for other
purposes also threatens to undermine the integrity and accuracy of the census. In a 2018 report,
the Census Bureau concluded that adding a citizenship question is “very costly, harms the quality
of the census count, and would use substantially less accurate citizenship status data than are
available” from other government sources.82
The Defendants’ Failure to Assess the Privacy Impact of Collecting Personal Data Concerning Citizenship Status
47. The Department of Commerce and the Census Bureau have failed to conduct a legally
sufficient—or in some cases, any—Privacy Impact Assessment for the collection, processing,
80 EPIC, Department of Homeland Security Obtained Data on Arab Americans From Census Bureau (2004), https://epic.org/privacy/census/foia/; see also Lynette Clemetson, Homeland Security Given Data on Arab-Americans, N.Y. Times (Jul. 30, 2004). 81 U.S. Customs and Border Protection, Policy for Requesting Information of a Sensitive Nature from the Census Bureau (Aug. 9, 2004), https://epic.org/privacy/census/foia/policy.pdf; Census Bureau News, U.S. Census Bureau Announces Policy Regarding Sensitive Data, press release CB04-145, August 30, 2004; Lynette Clemetson, Census Policy On Providing Sensitive Data Is Revised, N.Y. Times, (Aug. 31, 2004), http://www.nytimes.com/2004/08/31/us/census-policyon-providing-sensitive-data-is-revised.html; Mikelyn Meyers, Center for Survey Management, U.S. Census Bureau, Presentation on Respondent Confidentiality Concerns and Possible Effects on Response Rates and Data Quality for the 2020 Census, presented at National Advisory Committee on Racial, Ethnic, and Other Populations Fall Meeting (Nov. 2, 2017), https://www2.census.gov/cac/nac/meetings/2017-11/Meyers-NAC-ConfidentialityPresentation.pdf. 82 U.S. Dep’t of Commerce, U.S. Census Bureau, Technical Review of the Dep’t of Justice Request to Add Citizenship Question to the 2020 Census (Jan. 19, 2018), available at https://epic.org/foia/censusbureau/EPIC-18-03-22-Census-Bureau-FOIA-20180611-ProductionTechnical-Review-Memo.pdf.
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and storage of citizenship information by the various Bureau systems that handle personally identifiable census data. 48. When the Department of Commerce and the Census Bureau produce a PIA concerning Bureau activities, the PIA is published on a webpage titled U.S. Census Bureau Privacy Impact Assessments (PIAs) and Privacy Threshold Analysis (PTA).83 The webpage lists Census Bureau systems and divisions that collect, process, and/or store personally identifiable information.84 The page also provides links to (1) the most recent Privacy Impact Assessment for each system, and (2) the most recent Privacy Threshold Analysis for each system.85 49. At least five of the CEN systems and divisions identified on the Census Bureau’s PIA webpage (CEN05, CEN08, CEN11, CEN13, and CEN18) will be used to collect, process, and/or store personally identifiable information obtained through the 2020 Census, including citizenship data. 50. The decision to collect personal data concerning citizenship status triggers the Bureau’s obligation to update and publish the Privacy Impact Assessment for each of these five CENs. This is so for six reasons: (1) the Bureau is creating “a new collection of information” that will be digitally stored or transmitted “in an identifiable form”;86 (2) the introduction of citizenship data is a “factor[] affecting the collection and handling of information in identifiable form”;87 (3) the introduction of citizenship data is a change to a system that “creates new privacy risks”;88 (4)
83 Dep’t of Commerce, Office of Privacy & Open Gov’t, U.S. Census Bureau Privacy Impact Assessments (PIAs) and Privacy Threshold Analysis (PTA), (Oct. 1, 2018), http://www.osec.doc.gov/opog/privacy/Census-pias.html. 84 See id. 85 See id. 86 E-Government Act § 208(b)(1). 87 OMB Guidance § II.B.4. 88 Id. § II.B.2.
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the Bureau is introducing “new information in identifiable form to a collection [that] raises the risks to personal privacy” (similar to “health or financial information”);89 (5) the Bureau’s plans for the data include “significant new uses or exchanges of information in identifiable form”;90 and (6) the Bureau is newly “merg[ing], centraliz[ing], [and] match[ing]” citizenship data with data in “other databases[.]”91 Each these conditions independently requires the publication or republication of a fully compliant PIA. 51. The Defendants’ obligation to conduct a PIA for each of the five CENs is already ripe, as the Bureau has “beg[u]n to develop a new or significantly modified [information technology] system or information collection[.]”92 52. EPIC, by itself and on behalf of its Members, sought out the full and complete Privacy Impact Assessment that the Defendants must publish under section 208 of the E-Government Act for each of the five CENs, including all of the information and analysis mandated by section 208(b)(2)(B)(ii), by the OMB Guidance, by the Commerce Department Privacy Compliance guidelines, and by the Census Bureau PIA Policy. Although a recent PIA exists for each CEN, three of the five fail to mention citizenship data at all, while the other two include zero analysis of how the collection of personal data concerning citizenship status would affect the privacy of census respondents. EPIC, by itself and on behalf of its Members, was unable to obtain—and was thereby denied—the information that it sought about each CEN and about the collection of personal data concerning citizenship status.
89 Id. § II.B.2.i. 90 Id. § II.B.2.g. 91 Id. § II.B.2.d. 92 Id. § II.C.2.
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53. EPIC, by itself and on behalf of its Members, sought out the full and complete Privacy Impact Assessment required for “CEN05 Field Systems Major Application” by visiting the Census Bureau PIA webpage.93 CEN05 is a “major information system” that “plans, organizes, coordinates, and carries out the Census Bureau’s field data collection program for sample surveys, special censuses, the Economic Census, and the Decennial census.”94 As such, the system is slated to collect personal data concerning citizenship status for the 2020 Census. 54. Nonetheless, the most recent PIA for CEN05 fails to even acknowledge that the system would handle citizenship information, let alone analyze the privacy impact of that data collection.95 As a result, EPIC, by itself and on behalf of its Members, was unable to obtain—and was thereby denied—information concerning CEN05 to which EPIC is legally entitled under the E-Government Act and implementing authorities. 55. EPIC, by itself and on behalf of its Members, also sought the full and complete Privacy Impact Assessment required for “CEN08 Decennial Information Technology Division (DITD)” by visiting the Census Bureau PIA webpage.96 CEN08 is a Census Bureau division and major information system “consist[ing] of both general support systems and major applications,” including applications that “process response data from census tests and 2020 Census operations[.]”97 As such, the system is slated to process personal data concerning citizenship status from the 2020 Census.
93 U.S. Dep’t of Commerce, Privacy Impact Assessment for the CEN05 Field Systems Major Application System (approved June 22, 2018), http://www.osec.doc.gov/opog/privacy/Census%20PIAs/CEN05_PIA_SAOP_Approved.pdf. 94 Id. at 1. 95 See generally id. 96 U.S. Dep’t of Commerce, Privacy Impact Assessment for the CEN08 Decennial Information Technology Division (DITD) (approved Sep. 28, 2018), http://www.osec.doc.gov/opog/privacy/Census%20PIAs/CEN08_PIA_SAOP_Approved.pdf. 97 Id. at 1.
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56. Although the most recent PIA for CEN08 acknowledges the existence of the citizenship question through a single word (“Citizenship”),98 the PIA entirely fails to analyze the implications of collecting this unique form of data.99 The Bureau’s one-word modification of a previous PIA, following the decision to add the most controversial question on the 2020 Census, is utterly inadequate and violates the Bureau’s obligation to produce a PIA that is “commensurate with the size of the information system being assessed, the sensitivity of information that is in an identifiable form in that system, and the risk of harm from unauthorized release of that information[.]”100 As a result, EPIC, by itself and on behalf of its Members, was unable to obtain—and was thereby denied—information concerning CEN08 to which EPIC is legally entitled under the E-Government Act and implementing authorities. 57. EPIC, by itself and on behalf of its Members, also sought the full and complete Privacy Impact Assessment required for “CEN11 Demographic Census, Surveys, and Special Processing” by visiting the Census Bureau PIA webpage.101 CEN11 is a major information system “comprised of components that support the Demographic Directorate business functions” and includes “a Commercial off the Shelf (COTS) product used by Census Bureau demographic programs for data access, transformation, reporting, and statistical analysis.”102 As such, the system is slated to process personal data concerning citizenship status from the 2020 Census.
98 Id. at 5. 99 See generally id. The first CEN08 PIA to acknowledge the existence of the citizenship question was approved earlier on June 26, 2018. U.S. Dep’t of Commerce, Privacy Impact Assessment for the CEN08 Decennial Information Technology Division (DITD) (approved June 26, 2018). But neither the June 26 nor the current (September 28) version of the CEN08 PIA analyzes the implications of collecting personal data concerning citizenship status. 100 E-Government Act § 208(b)(2)(B)(i). 101 U.S. Dep’t of Commerce, Privacy Impact Assessment for the CEN11 Demographic Census, Surveys, and Special Processing (approved June 22, 2018), http://www.osec.doc.gov/opog/privacy/Census%20PIAs/CEN11_PIA_SAOP_Approved.pdf. 102 Id. at 1.
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58. Although the most recent PIA for CEN08 acknowledges the existence of the citizenship question through a single word (“Citizenship”),103 the PIA entirely fails to analyze the implications of collecting this unique form of data.104 The Bureau’s one-word modification of a previous PIA, following the decision to add the most controversial question on the 2020 Census, is utterly inadequate and violates the Bureau’s obligation to produce a PIA that is “commensurate with the size of the information system being assessed, the sensitivity of information that is in an identifiable form in that system, and the risk of harm from unauthorized release of that information[.]”105 As a result, EPIC, by itself and on behalf of its Members, was unable to obtain—and was thereby denied—information concerning CEN08 to which EPIC is legally entitled under the E-Government Act and implementing authorities. 59. EPIC, by itself and on behalf of its Members, also sought out the full and complete Privacy Impact Assessment required for “CEN 13 Center for Economic Studies (CES)” by visiting the Census Bureau PIA webpage.106 CEN13 is a major information system whose “data holdings include census and survey data which may contain name, gender, age, date of birth etc. from across the Census Bureau[.]”107 As such, the system is slated to store personal data concerning citizenship status from the 2020 Census. 60. Nonetheless, the most recent PIA for CEN13 fails to even acknowledge that the system would handle citizenship information, let alone analyze the privacy impact of storing that data.108
103 Id. at 4. 104 See generally id. 105 E-Government Act § 208(b)(2)(B)(i). 106 U.S. Dep’t of Commerce, Privacy Impact Assessment for the CEN 18 Enterprise Applications (approved June 26, 2018), http://www.osec.doc.gov/opog/privacy/Census%20PIAs/CEN13_PIA_SAOP_Approved.pdf. 107 Id. at 1. 108 See generally id.
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As a result, EPIC, by itself and on behalf of its Members, was unable to obtain—and was thereby denied—information concerning CEN13 to which EPIC is legally entitled under the EGovernment Act and implementing authorities. 61. EPIC, by itself and on behalf of its Members, also sought out the full and complete Privacy Impact Assessment required for “CEN 18 Enterprise Applications” by visiting the Census Bureau PIA webpage.109 CEN18 is a major information system “used to deliver applications to end users of the U.S. Census Bureau network.”110 The system maintains “survey and census information,” including “personal names, personal addresses, personal contact information (telephone numbers, email address), business information, occupation, medical information, tax information, etc.”111 As such, the system is slated to store personal data concerning citizenship status from the 2020 Census. 62. Nonetheless, the most recent PIA for CEN18 fails to even acknowledge that the system would handle citizenship information, let alone analyze the privacy impact of storing that data.112 As a result, EPIC, by itself and on behalf of its Members, was unable to obtain—and was thereby denied—information concerning CEN18 to which EPIC is legally entitled under the EGovernment Act and implementing authorities. 63. Though Secretary Ross’s plan to add the citizenship question to the 2020 Census is arguably the most consequential decision in the Census Bureau’s recent history, the Department
109 U.S. Dep’t of Commerce, Privacy Impact Assessment for the CEN 13 Center for Economic Studies (CES) (approved June 26, 2018), http://www.osec.doc.gov/opog/privacy/Census%20PIAs/CEN18_PIA_SAOP_Approved.pdf. 110 Id. at 1. 111 Id. 112 See generally id.
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of Commerce and the Bureau have failed to conduct any of the privacy analysis required by the E-Government Act for a major collection of personally identifiable information.
Count I Violation of APA: Unlawful Agency Action 64. Plaintiff asserts and incorporates by reference paragraphs 1–63. 65. By placing a citizenship question on the 2020 Census and initiating the process of collecting personal data concerning citizenship status, the Defendants have unlawfully begun to develop a new or significantly modified collection of information prior to creating, reviewing, and publishing the full and complete Privacy Impact Assessments required by section 208(b) of the E-Government Act of 2002. 66. In violating section 208(b) the E-Government Act, Defendants have taken agency actions that are arbitrary, capricious, an abuse of discretion, or otherwise not in accordance with law under 5 U.S.C. § 706(2)(a) and short of statutory right under 5 U.S.C. § 706(2)(c). 67. Defendants’ decision to collect personal data concerning citizenship status through the 2020 Census, Defendants’ placement of a citizenship question on the 2020 Census, and Defendants’ initiation of the citizenship data collection process are final agency actions within the meaning of 5 U.S.C. § 704. 68. Plaintiff EPIC is adversely affected, aggrieved, and injured in fact by Defendants’ actions. By beginning the process of collecting personal data concerning citizenship status without publishing the full and complete Privacy Impact Assessments required by section 208(b) of E-Government Act, Defendants have frustrated Plaintiff’s longstanding mission to educate the public about the privacy implications of government databases that contain personally
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identifiable information and—in particular—about the collection of personally identifiable information via the census. 69. Plaintiff EPIC is also adversely affected, aggrieved, and injured in fact by Defendants’ actions through EPIC’s Members. EPIC’s Members, most of whom reside in the United States, are required by law to respond to the citizenship question that will be imminently posed to them on the 2020 Census. 13 U.S.C. § 221(a)–(b). By beginning the process of collecting citizenship data without publishing the full and complete Privacy Impact Assessments required by section 208(b) of the E-Government Act, Defendants have unlawfully denied EPIC’s Members—and by extension, EPIC—a full assessment of how their privacy interests will be affected before the collection process is initiated. 70. Plaintiff has exhausted all applicable administrative remedies.
Count II Violation of APA: Agency Action Unlawful Withheld 71. Plaintiff asserts and incorporates by reference paragraphs 1–63. 72. Defendants have failed to create, review, and publish the full and complete Privacy Impact Assessments required by section 208(b) of E-Government Act of 2002 for Defendants’ decision to collect personal data concerning citizenship status through the 2020 Census, for Defendants’ placement of a citizenship question on the 2020 Census, and for Defendants’ initiation of the citizenship data collection process. 73. In failing to take the steps required by section 208(b) of E-Government Act of 2002, Defendants have unlawfully withheld or unreasonably delayed agency action in violation of 5 U.S.C. § 706(1).
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74. Plaintiff EPIC is adversely affected, aggrieved, and injured in fact by Defendants’ inaction. By failing to publish the full and complete Privacy Impact Assessments required by section 208(b) of the E-Government Act prior to beginning the process of collecting personal data concerning citizenship status, Defendants have frustrated Plaintiff’s longstanding mission to educate the public about the privacy implications of government databases that contain personally identifiable information and—in particular—about the collection of personally identifiable information via the census. 75. Plaintiff EPIC is also adversely affected, aggrieved, and injured in fact by Defendants’ actions through EPIC’s Members. EPIC’s Members, most of whom reside in the United States, are required by law to respond to the citizenship question that will be imminently posed to them on the 2020 Census. 13 U.S.C. § 221(a)–(b). By failing to publish the full and complete Privacy Impact Assessments required by section 208(b) of the E-Government Act prior to beginning the process of collecting citizenship data, Defendants have unlawfully denied EPIC’s Members— and by extension, EPIC—a full assessment of how their privacy interests will be affected before the collection process is initiated. 76. Plaintiff has exhausted all applicable administrative remedies.
Count III Claim for Declaratory Relief 77. Plaintiff asserts and incorporates by reference paragraphs 1–63. 78. Plaintiff is entitled under 28 U.S.C. § 2201(a) to a declaration of the rights and other legal relations of the parties with respect to the claims set forth in Counts I-II.
26

Case 1:18-cv-02711 Document 1 Filed 11/20/18 Page 27 of 28
Requested Relief WHEREFORE, Plaintiff requests this Court:
A. Hold unlawful and set aside the Defendants’ decision to collect citizenship data through the 2020 Census, Defendants’ placement of a citizenship question on the 2020 Census, and Defendants’ initiation of the citizenship data collection process;
B. Order Defendants to suspend and revoke their decision collect citizenship data through the 2020 Census until the Defendants have conducted, reviewed, and published the full and complete Privacy Impact Assessments required by section 208(b) of E-Government Act of 2002;
C. Order Defendants to revoke and remove the citizenship question from the 2020 Census until the Defendants have conducted, reviewed, and published the full and complete Privacy Impact Assessments required by section 208(b) of E-Government Act of 2002;
D. Order Defendants to cease and desist from any action in furtherance of Defendants’ plan to collect citizenship data through the 2020 Census until the Defendants have conducted, reviewed, and published the full and complete Privacy Impact Assessments required by section 208(b) of E-Government Act of 2002;
E. Order Defendants to conduct, review, and publish the full and complete Privacy Impact Assessments required by section 208(b) of E-Government Act of 2002 for the Census Bureau’s collection of citizenship data;
F. Award EPIC costs and reasonable attorney’s fees incurred in this action; and G. Grant such other relief as the Court may deem just and proper.
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Case 1:18-cv-02711 Document 1 Filed 11/20/18 Page 28 of 28

Dated: November 20, 2018

Respectfully Submitted,
MARC ROTENBERG, D.C. Bar #422825 EPIC President and Executive Director
ALAN BUTLER, D.C. Bar #1012128 EPIC Senior Counsel
/s/ John Davisson JOHN DAVISSON, D.C. Bar #1531914 EPIC Counsel
ELECTRONIC PRIVACY INFORMATION CENTER 1718 Connecticut Avenue, N.W. Suite 200 Washington, D.C. 20009 (202) 483-1140 (telephone) (202) 483-1248 (facsimile)

28

 
 Case 1:18-cv-02711-DLF Document 16 Filed 02/08/19 Page 1 of 1

UNITED STATES DISTRICT COURT FOR THE DISTRICT OF COLUMBIA

ELECTRONIC PRIVACY INFORMATION CENTER,
Plaintiff,
v.
U.S. DEPARTMENT OF COMMERCE, et al.,
Defendants.

No. 18-cv-2711 (DLF)

ORDER For the reasons stated in the accompanying memorandum opinion, it is ORDERED that the plaintiff’s Motion for a Preliminary Injunction, Dkt. 8, is DENIED.

February 8, 2019

________________________ DABNEY L. FRIEDRICH United States District Judge

 
 Case 1:18-cv-02711-DLF Document 8 Filed 01/18/19 Page 1 of 2

IN THE UNITED STATES DISTRICT COURT FOR THE DISTRICT OF COLUMBIA

ELECTRONIC PRIVACY INFORMATION CENTER, Plaintiff, v.
UNITED STATES DEPARTMENT OF COMMERCE, et al.,
Defendants.

Civ. Action No. 18-2711 (DLF)

PLAINTIFF’S MOTION FOR A PRELIMINARY INJUNCTION Pursuant to Federal Rule of Civil Procedure 65 and Local Rule 65.1(c), Plaintiff Electronic Privacy Information Center (“EPIC”) respectfully moves the Court to issue a preliminary injunction preventing Defendants United States Department of Commerce and Bureau of the Census from (1) implementing the Defendants’ March 26, 2018 decision to add a citizenship question to the 2020 Census, and (2) otherwise initiating any collection of citizenship status information that would be obtained through the 2020 Census. This injunction is necessary to preserve the status quo pending final adjudication of EPIC’s claims under the Administrative Procedure Act and the E-Government Act, Pub. L. No. 107-347, 116 Stat. 2899 (Dec. 17, 2002) (codified at 44 U.S.C. § 3501 note). The full grounds for this motion are set out in the accompanying Memorandum in Support of Plaintiff’s Motion for a Preliminary Injunction. Pursuant to Local Rule 65.1(d), and for the reasons set forth the Memorandum, EPIC requests that the Court schedule a hearing on this motion at the Court’s earliest convenience.

1

Case 1:18-cv-02711-DLF Document 8 Filed 01/18/19 Page 2 of 2

Dated: January 18, 2018

Respectfully Submitted,
MARC ROTENBERG, D.C. Bar #422825 EPIC President and Executive Director
ALAN BUTLER, D.C. Bar #1012128 EPIC Senior Counsel
/s/ John Davisson JOHN DAVISSON, D.C. Bar #1531914 EPIC Counsel
ELECTRONIC PRIVACY INFORMATION CENTER 1718 Connecticut Avenue, N.W. Suite 200 Washington, D.C. 20009 (202) 483-1140 (telephone) (202) 483-1248 (facsimile)
Attorneys for Plaintiff EPIC

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Case 1:18-cv-02711-DLF Document 8-1 Filed 01/18/19 Page 1 of 49

IN THE UNITED STATES DISTRICT COURT FOR THE DISTRICT OF COLUMBIA

ELECTRONIC PRIVACY INFORMATION CENTER, Plaintiff, v.
UNITED STATES DEPARTMENT OF COMMERCE, et al.,
Defendants.

Civ. Action No. 18-2711 (DLF)

MEMORANDUM IN SUPPORT OF PLAINTIFF’S MOTION FOR A PRELIMINARY INJUNCTION

Case 1:18-cv-02711-DLF Document 8-1 Filed 01/18/19 Page 2 of 49
TABLE OF CONTENTS
TABLE OF AUTHORITIES.......................................................................................................... ii SUMMARY ....................................................................................................................................1 BACKGROUND .............................................................................................................................2
I. The E-Government Act of 2002 ...........................................................................................2 II. The Department of Commerce order initiating the collection of personal data
concerning citizenship status............................................................................................3 III. The privacy implications of collecting citizenship status information................................6 IV. The lack of privacy impact assessments analyzing the citizenship question ......................9 V. EPIC’s prior warnings to the Census Bureau of E-Government Act noncompliance.......12 VI. EPIC’s lawsuit under the E-Government Act ...................................................................13 VII. The ruling of the court in New York v. U.S. Department of Commerce ............................14 ARGUMENT ................................................................................................................................15 I. EPIC is entitled to a preliminary injunction. ......................................................................15
A. EPIC is likely to succeed on the merits of its claims. ................................................16 1. The Census Bureau is required to publish privacy impact assessments that fully address the privacy risks of collecting citizenship status information.......17 2. The Census Bureau was obligated to publish the required privacy impact assessments by March 26, 2018. ........................................................................19 3. The Census Bureau has unlawfully failed to publish the required privacy impact assessments for more than nine months. ................................................21 4. EPIC’s suit satisfies the requirements for an action under the APA. .................24
B. EPIC will suffer irreparable harm absent an injunction.............................................26 C. The equities and the public interest weigh in favor of an injunction. ........................33 II. EPIC has Article III standing in this matter. .....................................................................37 CONCLUSION .............................................................................................................................40
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TABLE OF AUTHORITIES
Cases
Baldrige v. Shapiro, 455 U.S. 345 (1982) ....................................................................................................................1
Benisek v. Lamone, 138 S. Ct. 1942 (2018) ..............................................................................................................16
Benkelman Tel. Co. v. FCC, 220 F.3d 601 (D.C. Cir. 2000)...................................................................................................20
Byrd v. EPA, 174 F.3d 239 (D.C. Cir. 1999)...................................................................................................27
Calvert Cliffs’ Coordinating Comm., Inc. v. AEC, 449 F.2d 1109 (1971) ................................................................................................................30
Chaplaincy of Full Gospel Churches v. England, 454 F.3d 290 (D.C. Cir. 2006).............................................................................................29, 31
City of San Jose v. Ross, No. 18-2279 (N.D. Cal. filed Apr. 17, 2018) ............................................................................28
Clapper v. Amnesty Int'l USA, 568 U.S. 398 (2013) ..................................................................................................................38
Conference of State Bank Supervisors v. Office of Comptroller of Currency, 313 F. Supp. 3d 285 (D.D.C. 2018) ....................................................................................37, 38
Ctr. for Sustainable Econ. v. Jewell, 779 F.3d 588 (D.C. Cir. 2015).............................................................................................38, 39
EPIC v. DOJ, 416 F. Supp. 2d 30 (D.D.C. 2006) ............................................................................................27
EPIC v. Presidential Advisory Comm'n on Election Integrity, 266 F. Supp. 3d 297 (D.D.C.), aff’d on other grounds, 878 F.3d 371 ....................27, 28, 29, 33
EPIC v. Presidential Advisory Comm’n on Election Integrity, 878 F.3d 371 (D.C. Cir. 2017)...........................................................................20, 25, 26, 30, 38
FEC v. Akins, 524 U.S. 11 (1998) ..............................................................................................................37, 38
Fed'n for Am. Immigration Reform v. Klutznick, 486 F. Supp. 564 (D.D.C. 1980) .................................................................................................8
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Case 1:18-cv-02711-DLF Document 8-1 Filed 01/18/19 Page 4 of 49
Friedman v. FAA, 841 F.3d 537 (D.C. Cir. 2016)...................................................................................................26
Hirschfeld v. Stone, 193 F.R.D. 175 (S.D.N.Y. 2000)...............................................................................................32
Illinois Commerce Comm’n v. ICC, 848 F.2d 1246 (D.C. Cir. 1988).................................................................................................30
In re Dep’t of Commerce, No. 18-557, 2018 WL 5458822 (U.S. Nov. 16, 2018) ........................................................15, 28
Int’l Union, United Auto., Aerospace & Agric. Implement Workers of Am. v. Brock, 477 U.S. 274 (1986) ..................................................................................................................39
Ipsen Biopharmaceuticals, Inc. v. Hargan, 334 F. Supp. 3d 274 (D.D.C. 2018) ..........................................................................................25
Jones v. D.C. Redevelopment Land Agency, 499 F.2d 502 (D.C. Cir. 1974)...........................................................................27, 30, 31, 34, 36
Judicial Watch, Inc. v. DHS, 895 F.3d 770 (D.C. Cir. 2018)...................................................................................................27
Kelso v. U.S. Dep’t of State, 13 F. Supp. 2d 1 (D.D.C. 1998) ................................................................................................19
Kravitz v. Dep’t of Commerce, No. GJH-18-1041, 2018 WL 6830226 (D. Md. Dec. 28, 2018) .........................................24, 28
La Union del Pueblo Entero v. Ross, No. GJH-18-1570, 2018 WL 5885528 (D. Md. Nov. 9, 2018) .................................................28
Lathan v. Volpe, 455 F.2d 1111 (9th Cir. 1971) .................................................................................30, 31, 34, 36
Nat’l Fed’n of Fed. Emps. v. Greenberg, 789 F. Supp. 430 (D.D.C. 1992) ...............................................................................................32
Navajo Nation v. Azar, 292 F. Supp. 3d 508 (D.D.C. 2018) ..............................................................................15, 26, 33
New York Immigration Coal. v. Dep't of Commerce, No. 18-CV-5025 (JMF), 2019 WL 190285 (S.D.N.Y. Jan. 15, 2019)......................................28
New York v. U.S. Dep't of Commerce, No. 18-CV-2921 (JMF), 2019 WL 190285 (S.D.N.Y. Jan. 15, 2019)..................5, 8, 14, 24, 28
iii

Case 1:18-cv-02711-DLF Document 8-1 Filed 01/18/19 Page 5 of 49
Nken v. Holder, 556 U.S. 418 (2009) ..................................................................................................................33
Norton v. Southern Utah Wilderness Alliance (SUWA), 542 U.S. 55 (2004) ..............................................................................................................25, 26
Payne Enters., Inc. v. United States, 837 F.2d 486 (D.C. Cir. 1988)...................................................................................................27
Pharm. Research & Mfrs. of Am. v. Thompson, 259 F. Supp. 2d 39 (D.D.C. 2003), aff’d, 362 F.3d 817 (D.C. Cir. 2004) ................................24
Pub. Employees for Envtl. Responsibility v. United States Fish & Wildlife Serv., 189 F. Supp. 3d 1 (D.D.C. 2016) ..............................................................................................31
Public Citizen v. DOJ, 491 U.S. 440 (1989) ..................................................................................................................38
Realty Income Tr. v. Eckerd, 564 F.2d 447 (D.C. Cir. 1977).............................................................................................31, 35
Saco River Cellular, Inc. v. FCC, 133 F.3d 25 (D.C. Cir. 1998).....................................................................................................20
Sierra Club v. Thomas, 828 F.2d 783 (D.C. Cir. 1987)...................................................................................................26
Sorenson Commc’ns, LLC v. FCC, 897 F.3d 214 (D.C. Cir. 2018)...................................................................................................38
Spokeo, Inc. v. Robins, 136 S. Ct. 1540 (2016) ..............................................................................................................38
Steel Co. v. Citizens for a Better Env’t, 523 U.S. 83 (1998) ....................................................................................................................37
Summers v. Earth Island Inst., 555 U.S. 488 (2009) ..................................................................................................................37
U.S. Army Corps of Eng’rs v. Hawkes Co., 136 S. Ct. 1807 (2016) ..............................................................................................................25
United States v. Hubbard, 650 F.2d 293 (D.C. Cir. 1980)...................................................................................................32
University of Tex. v. Camenisch, 451 U.S. 390 (1981) ..................................................................................................................16
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Case 1:18-cv-02711-DLF Document 8-1 Filed 01/18/19 Page 6 of 49
W. Org. of Res. Councils v. Zinke, 892 F.3d 1234 (D.C. Cir. 2018)...........................................................................................25, 26
Washington Post v. DHS, 459 F. Supp. 2d 61 (D.D.C. 2006) ............................................................................................27
Winter v. NRDC, 555 U.S. 7 (2008) ....................................................................................................15, 26, 29, 33
Youngstown Sheet & Tube Co. v. Sawyer, 343 U.S. 579 (1952) (Frankfurter, J., concurring).....................................................................35
Statutes 13 U.S.C. § 5 ...................................................................................................................................4 13 U.S.C. § 141(a) ...........................................................................................................................4 13 U.S.C. § 221 .............................................................................................................4, 17, 21, 25 15 U.S.C. § 1501 .............................................................................................................................4 28 U.S.C. § 2201(a) .......................................................................................................................14 42 U.S.C. § 4332 ...........................................................................................................................30 44 U.S.C. § 3502(3)(A) ...........................................................................................................20, 21 44 U.S.C. § 3902 ...........................................................................................................................19 Act of Jul. 2, 1909 (to provide for the expenses of the Thirteenth December
Census, and for other purposes), ch. 2, § 25, 36 Stat. 1, 9 ..........................................................7 Act of June 18, 1929 (to provide for the fifteenth and subsequent decennial
censuses and to provide for apportionment of Representatives in Congress), ch. 28, § 11, 46 Stat. 21, 25.......................................................................................7 Administrative Procedure Act 5 U.S.C. § 702 ...........................................................................................................................24 5 U.S.C. § 704 .....................................................................................................................24, 25 5 U.S.C. § 706 .....................................................................................................................24, 25 5 U.S.C. § 706(1).................................................................................................................14, 26 5 U.S.C. § 706(2).................................................................................................................14, 25
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E-Government Act, Pub. L. No. 107-347, 116 Stat. 2899 (Dec. 17, 2002) (codified at 44 U.S.C. § 3501 note) § 2(b) .....................................................................................................................................2, 36 § 201 ..........................................................................................................................................20 § 208(a)....................................................................................................................25, 26, 29, 36 § 208(b) .......................................................................................................... 2, 3, 14, 16, 17, 19, 22, 23, 26, 39 § 208(d) .................................................................................................................................3, 17
Regulations 5 C.F.R. § 1320.3(c) ................................................................................................................20, 21
Other Authorities 148 Cong. Rec. 11,227 (2002) (statement of Sen. Lieberman) .......................................................2 Black's Law Dictionary 705 (Special Deluxe 5th ed. 1979) .........................................................19 Br. of EPIC as Amicus Curiae in Supp. Pls.’ Position at Trial, New York v.
U.S. Dep't of Commerce, No. 18-CV-2921 (JMF), 2019 WL 190285 (S.D.N.Y. Jan. 15, 2019) .....................................................................................................13, 34 “Census” and “Citizenship”, Google News (Jan. 13, 2019)........................................................28 Census: Australian Bureau of Statistics Says Website Attacked by Overseas Hackers, ABC News (Aug. 9, 2016)...........................................................................................1 Decl. of Andrew Case in Supp. of Pls.’ Opp’n to Defs.’ Mot. Summ. J. at Ex. B, San Jose v. Ross, 18-2279 (N.D. Cal. Filed Nov. 16, 2018) ............................................6 Defs.’ Second Suppl. Resps. to Pls.’ First Set of Interrogatories, N.Y. Immigration Coal. v. U.S. Dep’t of Commerce, 18-5025 (Oct. 11, 2018) ..................................5 Dep’t of Commerce, Office of Privacy & Open Gov’t, U.S. Census Bureau Privacy Impact Assessments (PIAs) and Privacy Threshold Analysis (PTA) (Oct. 1, 2018)....................................................................................................................9 Email from Kris Kobach, Sec’y, Kan. Dep’t of State, to Wilbur Ross, Sec’y, Dep’t of Commerce (Jul. 21, 2017)..................................................................................5 EPIC, Department of Homeland Security Obtained Data on Arab Americans From Census Bureau (2004) .....................................................................................8
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EPIC, EPIC FOIA Cases (Sep. 17, 2018) ...............................................................................34, 39
Joshua B. Bolten, Dir., OMB, Executive Office of the President, M03-22, Memorandum for Heads of Executive Departments and Agencies, Attachment A (Sept. 26, 2003) (“OMB Guidance”) ..............................16, 17, 18, 19 22, 23, 38
Latanya Sweeney, Simple Demographics Often Identify People Uniquely (Carnegie Mellon Univ., Data Privacy Working Paper No. 3, 2000)..................................................................................................................................6, 18
Letter from Attorneys General of Twenty U.S. States to Wilbur Ross, Secretary of Commerce (Feb. 12, 2018) .....................................................................................5
Letter from Sen. Dianne Feinstein et al. to Wilbur Ross, Secretary of Commerce (Jan. 5, 2018).............................................................................................................5
Lynette Clemetson, Census Policy On Providing Sensitive Data Is Revised, N.Y. Times, (Aug. 31, 2004) ........................................................................................8
Lynette Clemetson, Homeland Security Given Data on Arab-Americans, N.Y. Times (Jul. 30, 2004) ..........................................................................................................8
Margo Anderson & William Seltzer, Census Confidentiality Under the Second War Powers Act (1942- 1947) (Mar. 29-31, 2007) (unpublished manuscript) ..................................................................................................................................7
Margo Anderson & William Seltzer, Challenges to the Confidentiality of U.S. Federal Statistics, 1910-1965, 23 J Official Stat. 1, 6–7 (2007).....................................7
Petition for a Writ of Mandamus, In re Dep’t of Commerce, No. 18-557, 2018 WL 5458822 (U.S. Nov. 16, 2018) ..................................................................................36
Presidential Proclamation No. 7,286, 65 Fed. Reg. 17,985 (Apr. 1, 2000)...............................2, 36
Proposed Information Collection; Comment Request; 2020 Census, 83 Fed. Reg. 26,643 (June 8, 2018)................................................................................................12
Submission for OMB Review, 83 Fed. Reg. 67,213 (Dec. 28, 2018) .........................13, 21, 32, 35
Tara Bahrampour, Trump Administration Officials Suggested Sharing Census Responses with Law Enforcement, Court Documents Show, Wash. Post (Nov. 19, 2018).........................................................................................................6
U.S. Census Bureau, 2020 Census (Oct. 19, 2018) .........................................................................4
U.S. Census Bureau, 2020 Census Operational Plan: A New Design for the 21st Century (Sept. 2017)..................................................................................13, 28, 31, 37
vii

Case 1:18-cv-02711-DLF Document 8-1 Filed 01/18/19 Page 9 of 49 U.S. Census Bureau, Decennial Census of Population and Housing (2014)................................21 U.S. Census Bureau, Subjects Planned for the 2020 Census and American
Community Survey (Mar. 2017) ................................................................................................21 U.S. Conference of Mayors, Nation’s Mayors to Secretary Ross: Don’t
Politicize Census. Remove the Citizenship Question (Mar. 27, 2018) ........................................5 U.S. Customs and Border Protection, Policy for Requesting Information of
a Sensitive Nature from the Census Bureau (Aug. 9, 2004) .......................................................8
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SUMMARY Unique among federal agencies, the U.S. Census Bureau is authorized by law to compel, from every person in the United States, their personal data including age, sex, race, ethnicity, family relationships, and homeownership status. The extraordinary reach of the Bureau into the private lives of Americans brings with it extraordinary risks to privacy. The data collected by the Bureau is not only subject to uses by other federal agencies inconsistent with the collection purpose, but may also be the target of foreign cyberattacks.1 Accordingly, “Congress has provided assurances that information furnished to the [Census Bureau] by individuals is to be treated as confidential.” Baldrige v. Shapiro, 455 U.S. 345, 354 (1982). These legal assurances include the transparency and oversight provisions of the E-Government Act, which require the Census Bureau, a component of the Department of Commerce, to conduct and publish privacy impact assessments before initiating the collection of personal data. But the Census Bureau has failed to live up to its obligations. The Bureau decided to add a citizenship question to the census yet refused to evaluate the privacy threats posed by the collection of citizenship status information, as required by the E-Government Act. As a result of the failure to complete mandatory privacy impact assessments, the Bureau has denied EPIC access to information vital to the important public debate over census changes, has undermined the agency’s own decisionmaking process, and has unduly jeopardized the privacy of EPIC’s members.
1 See, e.g., Census: Australian Bureau of Statistics Says Website Attacked by Overseas Hackers, ABC News (Aug. 9, 2016), https://www.abc.net.au/news/2016-08-10/australian-bureau-ofstatistics-says-census-website-hacked/7712216 (“Australian Privacy Commissioner Timothy Pilgrim said he would launch an investigation into the ABS cyber attacks. ‘My first priority is to ensure that no personal information has been compromised as a result of these attacks,’ he said. ‘My office will continue to work with the ABS to ensure they are taking appropriate steps to protect the personal information collected through the census.’”).
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EPIC has repeatedly warned the Census Bureau of the defective nature of the proposed census collection, yet the agency continues to move forward with this unlawful agency action. Key deadlines are fast approaching, and major privacy risks have not been addressed by the agency. And nowhere is the duty to assess privacy risks more important than the decennial census, a “unique” and compulsory collection of data that “reaches every population group, from America’s long-time residents to its most recent immigrants.” Presidential Proclamation No. 7,286, 65 Fed. Reg. 17,985, 17,985 (Apr. 1, 2000).
The Court should grant EPIC’s motion for a preliminary injunction and halt the Census Bureau’s implementation of the citizenship question until this Court has adjudicated EPIC’s EGovernment Act claims on the merits.
BACKGROUND I. The E-Government Act of 2002
In 2002, Congress passed the E-Government Act with the aim of “provid[ing] enhanced access to Government information” and “mak[ing] the Federal Government more transparent and accountable.” E-Government Act, Pub. L. No. 107-347, §§ 2(b)(9), (11), 116 Stat. 2899, 2901 (Dec. 17, 2002) (codified at 44 U.S.C. § 3501 note), see also 148 Cong. Rec. 11,227 (2002) (statement of Sen. Lieberman) (explaining that the Act is intended to “improv[e] the access of all citizens to the government services and information they rely on every day in their work and personal lives”). Among the “constituencies” accounted for in the Act are “the public access community,” “privacy advocates,” and “non-profit groups interested in good government.” 148 Cong. Rec. 11,228.
Section 208 of the Act requires federal agencies to conduct and publish a privacy impact assessment (“PIA”) before beginning the process of collecting personal data. E-Government Act § 208(b). Specifically, “before . . . initiating a new collection” of “information in an identifiable
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form” from ten or more persons, the agency must “conduct a privacy impact assessment” and, “if

practicable,” “make the privacy impact assessment publicly available through the website of the

agency, publication in the Federal Register, or other means.” Id. § 208(b). Information is in an

identifiable form if it “permits the identity of an individual to whom the information applies to be

reasonably inferred by either direct or indirect means.” Id. § 208(d). To satisfy section 208 of the

E-Government Act, a privacy impact assessment must specify:

(I) (II) (III) (IV) (V)
(VI) (VII)

what information is to be collected; why the information is being collected; the intended use of the agency of the information; with whom the information will be shared; what notice or opportunities for consent would be provided to individuals regarding what information is collected and how that information is shared; how the information will be secured; and whether a system of records is being created under section 552a of title 5, United States Code, (commonly referred to as the ‘Privacy Act’).

E-Government Act § 208(b)(2)(B)(ii). A PIA must also be “commensurate with the size of the

information system being assessed, the sensitivity of information that is in an identifiable form in

that system, and the risk of harm from unauthorized release of that information[.]” Id. §

208(b)(2)(B)(i).

II. The Department of Commerce order initiating the collection of personal data concerning citizenship status

In order to determine the apportionment of representatives “among the several States,”

the Census Clause of the U.S. Constitution, as amended, requires that an “actual Enumeration” of

persons be undertaken every ten years “in such Manner as [Congress] shall by Law direct.” U.S.

Const. art. 1, § 2, cl. 3; see also U.S. Const. amend. XIV, § 2 (“Representatives shall be

apportioned among the several States according to their respective numbers, counting the whole

number of persons in each State, excluding Indians not taxed.”). In furtherance of the Census

Clause, Congress has directed the Secretary of Commerce to “take a decennial census of

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population,” 13 U.S.C. § 141(a), and to “determine the inquiries, and the number, form, and subdivisions” of the questionnaires to be used in the census. 13 U.S.C. § 5. Congress has also established the Census Bureau as an agency under the Department of Commerce. 15 U.S.C. § 1501. The Bureau will administer the next Census in 2020. See U.S. Census Bureau, 2020 Census (Oct. 19, 2018).2 By law, any person who refuses to answer “any of the questions . . . submitted to him in connection with any census”—or who willfully gives a false answer to a census question—is subject to criminal penalties. 13 U.S.C. § 221(a)–(b).
On March 26, 2018, Secretary of Commerce Wilbur Ross stated that he “ha[d] determined that reinstatement of a citizenship question on the 2020 decennial census [wa]s necessary” and that he was “directing the Census Bureau to place the citizenship question last on the decennial census form.” Ex. 1, Letter from Wilbur Ross, Secretary of Commerce, to Karen Dunn Kelley, Under Secretary for Economic Affairs, at 8 (Mar. 26, 2018). No such question appeared on the 2010 Census, Ex. 16, U.S. Dep’t of Commerce, United States Census 2010 (2009), nor has the Bureau posed a citizenship question to all census respondents since the 1950 Census. See Ex. 1 at 2. On March 28, 2018, the Bureau officially reported to Congress its intention to add a citizenship question to the 2020 Census. Ex. 2, U.S. Census Bureau, Questions Planned for the 2020 Census and American Community Survey 7 (March 2018). The version of the question presented to Congress asked: “Is this person a citizen of the United States?” Id. Five responses were listed: “Yes, born in the United States”; “Yes, born in Puerto Rico, Guam, the U.S. Virgin Islands, or Northern Marianas”; “Yes, born abroad of U.S. citizen parent or parents”; “Yes, U.S. citizen by naturalization – Print year of naturalization”; “No, not a U.S. Citizen[.]” Id.
2 https://www.census.gov/programs-surveys/decennial-census/2020-census.html.
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Secretary Ross stated that the citizenship question was added in response to a December 2017 request by the Department of Justice (“DOJ”), which he claimed sought citizenship data to enable “more effective enforcement” of the Voting Rights Act. Ex. 1 at 1. The DOJ’s request raised alarm and opposition from members of Congress, the attorneys general of at least twenty states, and mayors across the country. See Letter from Sen. Dianne Feinstein et al. to Wilbur Ross, Secretary of Commerce (Jan. 5, 2018);3 Letter from Attorneys General of Twenty U.S. States to Wilbur Ross, Secretary of Commerce (Feb. 12, 2018);4 U.S. Conference of Mayors, Nation’s Mayors to Secretary Ross: Don’t Politicize Census. Remove the Citizenship Question (Mar. 27, 2018).5 Moreover, Secretary Ross’s explanation for his decision is at odds with the extensive evidence adduced in New York v. U.S. Dep't of Commerce, No. 18-CV-2921 (JMF), 2019 WL 190285 (S.D.N.Y. Jan. 15, 2019), including the Secretary’s subsequent admission that he communicated with Chief White House strategist Steve Bannon and Kansas Secretary of State Kris Kobach about the citizenship question months before the DOJ made a request. See, e.g., Defs.’ Second Suppl. Resps. to Pls.’ First Set of Interrogatories 2–3, N.Y. Immigration Coal. v. U.S. Dep’t of Commerce, 18-5025 (Oct. 11, 2018);6 Email from Kris Kobach, Sec’y, Kan. Dep’t of State, to Wilbur Ross, Sec’y, Dep’t of Commerce (Jul. 21, 2017).7
3 https://www.feinstein.senate.gov/public/_cache/files/3/7/376f8dcd-7f35-4913-9e80cd1e48e3b312/7E4C59B2988E2CC14866543EDD7E01A6.2018.01.05-census-citizeshipletter.pdf. 4 https://www.brennancenter.org/sites/default/files/legal-work/Multi-State-Attorney-GeneralLetter-re-2020-Census.pdf. 5 https://www.usmayors.org/2018/03/27/nations-mayors-to-secretary-ross-dont-politicize-censusremove-the-citizenship-question/. 6 https://ag.ny.gov/sites/default/files/second_supp_res_to_rog_1_final_2018.10.11.pdf. 7 https://epic.org/foia/censusbureau/EPIC-18-03-22-Census-Bureau-FOIA-20180611Production-Kobach-Emails.pdf.
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III. The privacy implications of collecting citizenship status information Although the Census Bureau’s collection of personally identifiable information carries
inherent privacy risks, the addition of a citizenship question to the 2020 Census poses a unique threat to privacy, personal security, and the accuracy of the United States Census. The citizenship question would compel the release of respondents’ citizenship status (and potentially immigration status), which could in turn expose individuals and their family members to investigation, sanction, and deportation. Secretary Ross’s stated basis for adding the citizenship question was to provide the DOJ with “census block level citizen voting age population (‘CVAP’) data,” Ex. 1 at 1, 8—data that is susceptible to reidentification. Ex. 3, Latanya Sweeney, Simple Demographics Often Identify People Uniquely 2 (Carnegie Mellon Univ., Data Privacy Working Paper No. 3, 2000). The Bureau has indicated that census response data— including individuals’ citizenship status information—may be transferred in “[b]ulk” to other federal agencies “[f]or criminal law enforcement activities.” Ex. 6, U.S. Dep’t of Commerce, Privacy Impact Assessment for the CEN08 Decennial Information Technology Division (DITD) at 5, 7, 9 (approved Sep. 28, 2018). And in a June 12, 2018 email exchange between DOJ officials, disclosed in the course of litigation against Secretary Ross, DOJ officials “privately discussed the possibility that in the future census information could be shared with law enforcement.” Tara Bahrampour, Trump Administration Officials Suggested Sharing Census Responses with Law Enforcement, Court Documents Show, Wash. Post (Nov. 19, 2018);8 see also Decl. of Andrew Case in Supp. of Pls.’ Opp’n to Defs.’ Mot. Summ. J. at Ex. B, San Jose v. Ross, 18-2279 (N.D. Cal. Filed Nov. 16, 2018).
8 https://www.washingtonpost.com/local/social-issues/trump-administration-officials-suggestedsharing-census-responses-with-law-enforcement-court-documents-show/2018/11/19/41679018ec46-11e8-8679-934a2b33be52_story.html.
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Historically, the misuse of census data has caused considerable harm to certain populations. For example, the 1910 census law prohibited the use of information supplied by businesses for non-statistical, non-census purposes, but there was no such prohibition regarding individual citizen data. Act of Jul. 2, 1909 (to provide for the expenses of the Thirteenth December Census, and for other purposes), ch. 2, § 25, 36 Stat. 1, 9. As a result, the Census Bureau was able to disclose census records to the Department of Justice and local draft boards during World War I. Margo Anderson & William Seltzer, Challenges to the Confidentiality of U.S. Federal Statistics, 1910-1965, 23 J Official Stat. 1, 6–7 (2007). Similarly, in 1920, the Department of Justice requested census data about individuals’ citizenship for use in deportation cases. Id. at 8–9. In 1930, Congress passed a census statute prohibiting the Bureau from publishing any data identifying individuals. Act of June 18, 1929 (to provide for the fifteenth and subsequent decennial censuses and to provide for apportionment of Representatives in Congress), ch. 28, § 11, 46 Stat. 21, 25. Yet the Second War Powers Act weakened this restriction and permitted the Bureau in 1943 to provide the U.S. Secret Service with the names, addresses, occupations, and citizenship status of every Japanese American residing in the Washington, D.C. area. Margo Anderson & William Seltzer, Census Confidentiality Under the Second War Powers Act (1942- 1947) at 16 (Mar. 29-31, 2007) (unpublished manuscript). The Bureau also provided the War Department with census-block level data on Japanese Americans residing in western states to facilitate their internment. Comm’n on Wartime Relocation and Internment of Civilians, Personal Justice Denied 104-05 (1982).9
In 2004, an EPIC Freedom of Information Act (“FOIA”) request revealed that the Census Bureau had provided the Department of Homeland Security with a list of cities containing more
9 https://www.archives.gov/files/research/japanese-americans/justice-denied/chapter-3.pdf.
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than 1,000 Arab-American residents and a zip-code level breakdown of Arab-American populations throughout the United States, sorted by country of origin. EPIC, Department of Homeland Security Obtained Data on Arab Americans From Census Bureau (2004);10 see also Lynette Clemetson, Homeland Security Given Data on Arab-Americans, N.Y. Times (Jul. 30, 2004).11 The Census Bureau and Customs and Border Protection revised their data request policies following EPIC’s FOIA case. See Lynette Clemetson, Census Policy On Providing Sensitive Data Is Revised, N.Y. Times, (Aug. 31, 2004);12 U.S. Customs and Border Protection, Policy for Requesting Information of a Sensitive Nature from the Census Bureau (Aug. 9, 2004).13
Many Americans remain fearful that their census responses will be “used against them or their loved ones” by federal agencies. New York, No. 18-CV-2921 (JMF), 2019 WL 190285, at *9. As the Census Bureau has previously acknowledged, “[q]uestions as to citizenship are particularly sensitive in minority communities and would inevitably trigger hostility, resentment and refusal to cooperate.” Fed'n for Am. Immigration Reform v. Klutznick, 486 F. Supp. 564, 568 (D.D.C. 1980). This has consequences for the accuracy of census data. Fear over the misuse of census responses can lead individuals to provide false or incomplete information, which “harms the quality of the census count, and would [result in] substantially less accurate citizenship status data than are available from administrative sources.” Ex. 4, Memorandum from John M. Abowd, Chief Scientist, U.S. Census Bureau, to Wilbur L. Ross, Sec’y of Commerce, at 1 (Jan. 19, 2018); see also Fed'n for Am. Immigration Reform, 486 F. Supp. at 568 (“[A]ccording to the
10 https://epic.org/privacy/census/foia/. 11 https://www.nytimes.com/2004/07/30/us/homeland-security-given-data-on-arabamericans.html. 12 https://www.nytimes.com/2004/08/31/us/census-policy-on-providing-sensitive-data-isrevised.html. 13 https://epic.org/privacy/census/foia/policy.pdf.
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Bureau; any effort to ascertain citizenship will inevitably jeopardize the overall accuracy of the population count.”). IV. The lack of privacy impact assessments analyzing the citizenship question
None of the privacy impact assessments published by the Census Bureau address the question that Secretary Ross chose to add to the 2020 Census on March 26, 2018. When the Department of Commerce and the Census Bureau produce a PIA concerning Bureau activities, the assessment is published on the Bureau’s PIA webpage. Dep’t of Commerce, Office of Privacy & Open Gov’t, U.S. Census Bureau Privacy Impact Assessments (PIAs) and Privacy Threshold Analysis (PTA) (Oct. 1, 2018).14 The webpage lists Census Bureau systems and divisions that collect, process, and store personally identifiable information. See id. The page also provides links to (1) the most recent privacy impact assessment for each system, and (2) the most recent privacy threshold analysis for each system. See id. At least five of the CEN systems and divisions identified on the Bureau’s PIA webpage (CEN05, CEN08, CEN11, CEN13, and CEN18) will be used to collect, process, and/or store personally identifiable information obtained through the 2020 Census, including citizenship data. See Ex. 5, U.S. Dep’t of Commerce, Privacy Impact Assessment for the CEN05 Field Systems Major Application System 1 (approved June 22, 2018); Ex. 6 at 1, 5; Ex. 7, U.S. Dep’t of Commerce, Privacy Impact Assessment for the CEN11 Demographic Census, Surveys, and Special Processing 1, 4 (approved June 22, 2018); Ex. 8, U.S. Dep’t of Commerce, Privacy Impact Assessment for the CEN13 Center for Economic Studies (CES) 1 (approved June 26, 2018); Ex. 9, U.S. Dep’t of Commerce, Privacy Impact Assessment for the CEN18 Enterprise Applications 1 (approved June 26, 2018).
EPIC, on its behalf and on behalf of its members, sought out the most recent privacy impact assessment for each CEN system slated to collect, store, or process citizenship status 14 http://www.osec.doc.gov/opog/privacy/Census-pias.html.
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information. See Ex. 10, Declaration of Christopher Wolf ¶ 13 (Nov. 29, 2018); Ex. 11, Declaration of Bruce Schneier ¶ 13 (Nov. 29, 2018); Ex. 12, Declaration of Harry R. Lewis ¶ 13 (Dec. 3, 2018). Although a recent PIA exists for each CEN, three of the five do not mention personal data concerning citizenship status at all, while the other two include no analysis of how the collection of citizenship data would affect the privacy of census respondents. See Ex. 5 at 4–5 (failing to list “citizenship” among the information collected); Ex. 8 at 3–4 (same); Ex. 9 at 3–4 (same); Ex. 6 (failing to analyze the privacy implications of collecting citizenship status information); Ex. 7 (same).
EPIC, on its behalf and on behalf of its members, sought out the privacy impact assessment for “CEN05 Field Systems Major Application” by visiting the Census Bureau PIA webpage. Ex. 5; see, e.g., Ex. 10 ¶ 13. CEN05 is a “major information system” that “plans, organizes, coordinates, and carries out the Bureau’s field data collection program for sample surveys, special censuses, the Economic Census, and the Decennial census.” Ex. 5 at 1. As such, the Bureau intends to use this system to collect personal data concerning citizenship status for the 2020 Census. Id. Nonetheless, the most recent PIA for CEN05 does not acknowledge that the system would handle citizenship information or analyze the privacy impact of that data collection. See generally id.
EPIC, on its behalf and on behalf of its members, sought out the privacy impact assessment for “CEN08 Decennial Information Technology Division (DITD)” by visiting the Census Bureau PIA webpage. Ex. 6; see, e.g., Ex. 10 ¶ 13. CEN08 is a Census Bureau division and information system “consist[ing] of both general support systems and major applications,” including applications that “process response data from census tests and 2020 Census operations[.]” Ex. 6 at 1. As such, the Bureau intends to use this system to collect personal data
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concerning citizenship status for the 2020 Census. See id. Although the most recent PIA for CEN08 acknowledges the existence of the citizenship question through a single word (“Citizenship”), id. at 5, the PIA contains no specific analysis of the impact of collecting citizenship status information. See generally id.
EPIC, on its behalf and on behalf of its members, sought out the privacy impact assessment for “CEN11 Demographic Census, Surveys, and Special Processing” by visiting the Census Bureau PIA webpage. Ex. 7; see, e.g., Ex. 10 ¶ 13. CEN11 is an information system “comprised of components that support the Demographic Directorate business functions” and includes “a Commercial off the Shelf (COTS) product used by Census Bureau demographic programs for data access, transformation, reporting, and statistical analysis.” Ex. 7 at 1. As such, the Bureau intends to use this system to collect personal data concerning citizenship status for the 2020 Census. See id. Although the most recent PIA for CEN08 acknowledges the existence of the citizenship question through a single word (“Citizenship”), id. at 5, the PIA contains no specific analysis of the impact of collecting citizenship status information. See generally id.
EPIC, on its behalf and on behalf of its members, sought out the privacy impact assessment for “CEN13 Center for Economic Studies (CES)” by visiting the Census Bureau PIA webpage. Ex. 8; see, e.g., Ex. 10 ¶ 13. The “data holdings [of CEN13] include census and survey data which may contain name, gender, age, date of birth etc. from across the Census Bureau[.]” Ex. 8 at 1. As such, the Bureau intends to use this system to collect personal data concerning citizenship status for the 2020 Census. See id. Nonetheless, the most recent PIA for CEN13 does not acknowledge that the system would handle citizenship information or analyze the privacy impact of that data collection. See generally id.
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EPIC, on its behalf and on behalf of its members, sought out the privacy impact assessment for “CEN 18 Enterprise Applications” by visiting the Census Bureau PIA webpage. Ex. 9; see, e.g., Ex. 10 ¶ 13. CEN18 is an information system “used to deliver applications to end users of the U.S. Census Bureau network.” Ex. 9 at 1. The system maintains “survey and census information,” including “personal names, personal addresses, personal contact information (telephone numbers, email address), business information, occupation, medical information, tax information, etc.” Id. As such, the Bureau intends to use this system to collect personal data concerning citizenship status for the 2020 Census. See id. Nonetheless, the most recent PIA for CEN18 does not acknowledge that the system would handle citizenship information or analyze the privacy impact of that data collection. See generally id. V. EPIC’s prior warnings to the Census Bureau of E-Government Act noncompliance
Prior to this motion, EPIC notified the Census Bureau on four occasions that the Bureau was in violation of the section 208 of the E-Government Act. On August 7, 2018, EPIC filed comments with the Bureau about the proposed questions for the 2020 Census. Ex. 13, EPIC, Comments of EPIC to the U.S. Census Bureau (Aug. 7, 2018); see also Proposed Information Collection; Comment Request; 2020 Census, 83 Fed. Reg. 26,643 (June 8, 2018). EPIC stated that the Bureau had violated its PIA obligations under section 208 and that the Bureau had “not undertaken an appropriate analysis of the privacy risks of the citizenship question.” Ex. 13 at 5. On October 2, 2018, EPIC published a statement to the Senate Committee on Homeland Security and Government Affairs concerning the nomination of Steven D. Dillingham to be Director of the Census. Ex. 14, Statement from EPIC to Ron Johnson, Chairman, Senate Comm. on Homeland Sec. & Gov’t Affairs, et al. at 4 (Oct. 2, 2018). EPIC told the Committee (and the Bureau) that the Bureau was in violation of section 208 and “should conduct a new PIA dealing specifically with the issues raised by the citizenship question.” Id. at 4. On Oct. 29, 2018, EPIC
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filed an amicus brief in New York, No. 18-CV-2921 (JMF), 2019 WL 190285, a case challenging the addition of the citizenship question to the 2020 Census. EPIC explained the Bureau’s PIA obligations in detail and warned that “the Bureau has not adequately justified the collection of citizenship information or shown that it has implemented the safeguards necessary to protect the data that it collects.” Br. of EPIC as Amicus Curiae in Supp. Pls.’ Position at Trial at 20, New York, No. 18-CV-2921 (JMF), 2019 WL 190285 (S.D.N.Y. Jan. 15, 2019). Finally, on Nov. 20, 2018, EPIC filed a (and subsequently served) a complaint in this case alleging that the agency had “failed to conduct any of the privacy analysis required by the E-Government Act for a major collection of personally identifiable information.” Complaint ¶ 63 (Nov. 2, 2018), ECF No. 1.
To date, the Census Bureau has not updated the PIAs for CEN05, CEN08, CEN11, CEN13, or CEN18 to include an analysis of how a citizenship question would impact privacy. The Department of Commerce recently reiterated, in a filing with the Office of Management and Budget (“OMB”), that the Bureau intends to collect citizenship status information through the 2020 Census. See Submission for OMB Review, 83 Fed. Reg. 67,213, 67,216 (Dec. 28, 2018). The Bureau has also stated that the “printing, addressing, and mailing of Internet invitations, reminder cards or letters, and paper questionnaire packages” for the 2020 Census will begin by June 2019. U.S. Census Bureau, 2020 Census Operational Plan: A New Design for the 21st Century at 89 (Sept. 2017).15 VI. EPIC’s lawsuit under the E-Government Act
On November 20, 2018, EPIC filed the instant suit against the U.S. Census Bureau and the Department of Commerce (collectively, “the Defendants,” “the Census Bureau,” or “the Bureau”). See Complaint. EPIC alleged that the Defendants violated the E-Government Act and
15 https://www2.census.gov/programs-surveys/decennial/2020/program-management/planningdocs/2020-oper-plan3.pdf.
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Administrative Procedure Act (“APA”) in two respects. First, EPIC alleged that the Defendants took unlawful action in violation of 5 U.S.C. § 706(2) and E-Government Act § 208(b) by initiating a new collection of information without first producing required privacy impact assessments. Complaint ¶¶ 64–70 (Count I). Second, EPIC alleged that the Defendants unlawfully withheld production of required privacy impact assessments in violation of 5 U.S.C. § 706(1) and E-Government Act § 208(b). Complaint ¶¶ 71–76 (Count II). EPIC also brought a claim under the Declaratory Judgment Act, 28 U.S.C. § 2201(a). Complaint ¶¶ 77–78 (Count III). As relief, EPIC sought, inter alia, the suspension and revocation of the citizenship question pending completion and publication of the required privacy impact assessments. Complaint pp. 26–27. VII. The ruling of the court in New York v. U.S. Department of Commerce
On January 15, 2019, the U.S. District Court for the Southern District of New York entered a final judgment in New York v. U.S. Department of Commerce, No. 18-CV-2921 (JMF), 2019 WL 190285, a separate lawsuit challenging the addition of the citizenship question under the APA, the Enumeration Clause of the U.S. Constitution, and the Fifth Amendment of the U.S. Constitution. The court, finding “no dispute” that Secretary Ross’s decision to add a citizenship question constituted “final agency action,” concluded that the Secretary “violated the APA in several respects” and “violated the public trust.” Id. at *4, *89. Accordingly, the court “vacat[ed] Secretary Ross’s decision to add a citizenship question to the 2020 census questionnaire” and “enjoin[ed] Defendants from implementing Secretary Ross’s March, 26, 2018 decision or from adding a question to the 2020 census questionnaire without curing the legal defects identified” by the Court. Id. at *125. However, the Defendants have appealed the court’s judgment to the Second Circuit, Notice of Appeal, New York, No. 18-CV-2921 (JMF) (filed Jan. 17, 2019), and there remains pending litigation in the Supreme Court concerning a possible deposition of
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Secretary Ross in the same case. In re Dep’t of Commerce, No. 18-557, 2018 WL 5458822, at *1 (U.S. Nov. 16, 2018) (granting Defendants’ mandamus petition to review a discovery order).
ARGUMENT The Court should grant EPIC’s motion for a preliminary injunction to preserve the status quo and to allow a full adjudication of EPIC’s claims on the merits. EPIC has shown that it is entitled to such an injunction. In making the final decision to add a citizenship question to the 2020 Census, the Census Bureau initiated a new collection of personal information and triggered its obligation under the E-Government Act to conduct and publish new privacy impact assessments. Yet the Bureau has failed to publish the required assessments. As a result, EPIC and its members face irreparable harm: EPIC cannot evaluate the privacy impact of the citizenship question or scrutinize any privacy protections that might be put in place for the collection of citizenship status information. The privacy of EPIC’s members is also unduly threatened by the Bureau’s actions, which violate key privacy safeguards established by Congress. Finally, EPIC has Article III standing to bring this case because its members have suffered concrete and particularized injuries redressable by the Court. I. EPIC IS ENTITLED TO A PRELIMINARY INJUNCTION. EPIC is entitled to a preliminary injunction because the Census Bureau’s failure to publish legally required privacy impact assessments causes EPIC irreparable harm and conflicts with the public interest. A plaintiff is entitled to a preliminary injunction upon “a clear showing” that “(1) [the plaintiff] ‘is likely to succeed on the merits’; (2) [the plaintiff] ‘is likely to suffer irreparable harm in the absence of preliminary relief’; (3) the ‘balance of equities’ tips in [the plaintiff’s] favor; and (4) ‘an injunction is in the public interest.’” Navajo Nation v. Azar, 292 F. Supp. 3d 508, 512 (D.D.C. 2018) (quoting Winter v. NRDC, 555 U.S. 7, 22 (2008)).
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EPIC readily satisfies each of these factors. Accordingly, the Court should enjoin the Defendants from taking any steps to collect citizenship information via the 2020 Census in order to “preserve the relative positions of the parties until a trial on the merits can be held.” Benisek v. Lamone, 138 S. Ct. 1942, 1945 (2018) (quoting University of Tex. v. Camenisch, 451 U.S. 390, 395 (1981)).
A. EPIC is likely to succeed on the merits of its claims. EPIC is likely to prevail on its claims that the Census Bureau violated the E-Government Act and Administrative Procedure Act by failing to conduct and publish privacy impact assessments for the nationwide collection of citizenship status information. Under section 208 of the E-Government Act, federal agencies must “conduct,” “ensure the review of,” and “make publicly available” a detailed privacy impact assessment “before . . . initiating a new collection of information that—” (I) will be collected, maintained, or disseminated using information
technology; and (II) includes any information in an identifiable form permitting the physical or
online contacting of a specific individual if identical questions have been posed to, or identical reporting requirements imposed on, 10 or more persons, other than agencies, instrumentalities, or employees of the Federal Government. E-Government Act § 208(b)(1) (emphasis added). Agencies must also “update[]” existing PIAs “where a system change creates new privacy risks.” Ex. 15, Joshua B. Bolten, Dir., OMB, Executive Office of the President, M03-22, Memorandum for Heads of Executive Departments and Agencies, Attachment A § II.B.2 (Sept. 26, 2003) (“OMB Guidance”). The Census Bureau has failed to satisfy these PIA obligations with respect to each of the five Bureau systems that would contain or be used to disseminate citizenship status information.
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1. The Census Bureau is required to publish privacy impact assessments that fully address the privacy risks of collecting citizenship status information.
The Census Bureau’s collection of citizenship status information is a “new collection” of personally identifiable information (“PII”) that triggers the agencies’ PIA obligations. EGovernment Act § 208(b)(1). An individual’s citizenship status constitutes PII because it “permit[s] the identity of [the] individual to whom the information applies to be reasonably inferred,” E-Government Act § 208(d), when collected in “combination [with] gender, race, birth date, geographic indicator, and other descriptors” demanded on the census. Ex. 15, OMB Guidance § II.A.2. The Bureau concedes as much. See, e.g., Ex. 6 at 5 (listing “Citizenship” data among the “General Personal Data” handled by the CEN08 system).
The Census Bureau’s collection of personal data concerning citizenship status is also “new.” The Bureau did not collect citizenship status information through the 2010 Census, see Ex. 16, which is the only other decennial census conducted since the E-Government Act was enacted in 2002. Secretary Ross himself acknowledged that the Bureau was undertaking a “reinstatement of a citizenship question” that had not been asked on “census surveys of the entire United States population” since 1950. Ex. 1 at 2, 8. Finally, in deciding to collect citizenship status information from every person in the United States, the Bureau has imposed “identical reporting requirements” on “10 or more persons.” E-Government Act § 208(b)(1)(A)(ii)(II); see also 13 U.S.C. § 221(a)–(b) (requiring all persons over 18 to respond to census questions). The Bureau is thus required to conduct and publish a fully compliant PIA for each IT system that it will deploy to collect, maintain, or disseminate citizenship status information. See E-Government Act § 208(b)(1); Ex. 5 at 1; Ex. 6 at 1, 5; Ex. 7 at 1, 4; Ex. 8 at 1; Ex. 9 at 1.
Similarly, the Census Bureau’s order initiating the collection of citizenship status information triggers the agencies’ obligation to update and republish existing PIAs because “new
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information in identifiable form [is being] added to a collection” that “raises the risks to personal privacy[.]” Ex. 15, OMB Guidance § II.B.2. On March 26, 2018—the day that the Bureau initiated a new collection of citizenship status information—each of the five IT systems slated to collect, maintain, or disseminate citizenship information was covered by a prior PIA. See Ex. 17, U.S. Dep’t of Commerce, U.S. Census Bureau Privacy Impact Assessments (PIAs) and Privacy Threshold Analysis (PTA) (Dec. 13, 2016). But none of those prior PIAs addressed the extraordinary privacy implications of collecting and processing citizenship status information from every person in the United States, as now required by the Secretary of Commerce. The Bureau was simply not engaged in such data collection prior to the March 26, 2018 order. By initiating the addition of “new information in identifiable form” to multiple Census Bureau IT systems, the Bureau therefore triggered its obligation to fully update the existing PIAs for those systems. Ex. 15, OMB Guidance §§ II.B.2.i.
Indeed, the “new privacy risks” of adding a citizenship question to the 2020 Census are profound. Ex. 15, OMB Guidance § II.B.2. Citizenship status information is every bit as sensitive as “health or financial information,” and the collection of citizenship data presents unique threats to privacy and personal security. Id. § II.B.2.i. Disclosure of citizenship status to law enforcement agencies or the public at large could potentially expose individuals and their family members to investigation, sanction, retaliation, and deportation. Secretary Ross has expressly stated that the Census Bureau will transfer to the Department of Justice “census block level citizenship voting age population (‘CVAP’) data,” Ex. 1 at 1, 8—data that is susceptible to reidentification. Ex. 3 at 2. The Bureau has also indicated that individuals’ citizenship status information may be transferred in “[b]ulk” to other federal agencies “[f]or criminal law enforcement activities.” Ex. 6 at 5, 7, 9. These planned transfers of personal data are “significant
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new uses [and] exchanges of information in an identifiable form” and constitute a “merg[ing], centraliz[ing], [or] match[ing]” of citizenship data with PII in “other databases[.]” Ex. 15, OMB Guidance §§ II.B.2.d, g.
Given the novel privacy risks posed by the collection and dissemination of citizenship status information, id. § II.B.2, the Census Bureau is required to fully update and republish the PIA for each IT system that will handle personal data concerning citizenship status. See id.; Ex. 5 at 1; Ex. 6 at 1, 5; Ex. 7 at 1, 4; Ex. 8 at 1; Ex. 9 at 1.
2. The Census Bureau was obligated to publish the required privacy impact assessments by March 26, 2018.
The deadline for the Census Bureau to conduct and publish the required privacy impact assessments was March 26, 2018. That is the day Secretary Ross ordered the addition of a citizenship question to the 2020 Census, thereby initiating a new collection of citizenship status information.
An agency must conduct, review, and publish a valid privacy impact assessment before “initiating a new collection of information[.]” E-Government Act § 208(b)(1)(A). The word “initiate” means “[c]ommence, start; originate; introduce; inchoate.” Kelso v. U.S. Dep’t of State, 13 F. Supp. 2d 1, 9 (D.D.C. 1998) (quoting Black's Law Dictionary 705 (Special Deluxe 5th ed. 1979)). Title 44, in which the E-Government Act is codified, specifically distinguishes between “initiating” a process (i.e., commencing or introducing it) and “carrying out” or “completing” a process. 44 U.S.C. § 3902(a) (“The Director of the Government Publishing Office shall have no authority to prevent or prohibit the Inspector General from initiating, carrying out, or completing any audit or investigation[.]”). The phrase “collection of information” means
the obtaining, causing to be obtained, soliciting, or requiring the disclosure to third parties or the public, of facts or opinions by or for an agency, regardless of form or format, calling for either—
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(i) answers to identical questions posed to, or identical reporting or recordkeeping requirements imposed on, ten or more persons, other than agencies, instrumentalities, or employees of the United States; or
(ii) answers to questions posed to agencies, instrumentalities, or employees of the United States which are to be used for general statistical purposes[.]
44 U.S.C. § 3502(3)(A); see also E-Government Act § 201 (“Except as otherwise provided, in this title the definitions under sections 3502 and 3601 of title 44, United States Code, shall apply.”).
An agency need not actually acquire “facts or opinions” for the collection of information to exist, so long as the process of “obtaining,” “soliciting,” or “requiring . . . disclosure” is underway. 44 U.S.C. § 3502(3)(A); see also 44 U.SC. § 3506(c) (requiring agencies to “review each collection of information” well before any information has been solicited or added to the collection). The OMB further defines “collection of information” to include “a plan and/or an instrument calling for the collection or disclosure of information[.]” 5 C.F.R. § 1320.3(c) (emphasis added); see also EPIC v. Presidential Advisory Comm’n on Election Integrity, 878 F.3d 371, 380 (D.C. Cir. 2017) (noting that an agency must “prepare a privacy impact assessment [if] it plans to collect information” (emphasis added)). Even an “algorithm” can constitute a “collection of information” under 44 U.S.C. § 3502(3)(A) if it “impose[s] a ‘reporting requirement’” on members of the public. Benkelman Tel. Co. v. FCC, 220 F.3d 601, 607 (D.C. Cir. 2000) (quoting Saco River Cellular, Inc. v. FCC, 133 F.3d 25, 33 (D.C. Cir. 1998)).
Accordingly, the Census Bureau initiated a new collection of information when—on March 26, 2018—Secretary Ross ordered the “reinstatement of a citizenship question on the 2020 decennial census.” Ex. 1 at 8. With the Secretary’s announcement “directing the Census Bureau to place the citizenship question . . . on the decennial census form,” id., the Bureau both
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commenced the “soliciting” and “obtaining” of citizenship status information, 44 U.S.C. § 3502(3)(A), and introduced a definite “plan . . . calling for the collection or disclosure of information,” 5 C.F.R. § 1320.3(c) (construing § 3502(3)(A)). By the same token, the Bureau introduced a new requirement that census respondents disclose “facts or opinions” to “third parties or the public.” 44 U.S.C. § 3502(3)(A). Persons over 18 must respond to a citizenship question on the census, 13 U.S.C. § 221(a)–(b), and the aggregate facts provided by census respondents are disclosed to the public and third parties. See U.S. Census Bureau, Decennial Census of Population and Housing (2014)16 (publishing aggregate responses to 2010 Census questions); Ex. 1 at 8 (stating that the citizenship question “is necessary to provide complete and accurate data in response to the DOJ request” for citizenship data); U.S. Census Bureau, Subjects Planned for the 2020 Census and American Community Survey 52 (Mar. 2017)17 (listing six outside agencies that would use census-collected citizenship data); Submission for OMB Review, 83 Fed. Reg. at 67,221 (promising that if state officials “indicate a need for tabulations of citizenship data . . . the Census Bureau will make a design change to include citizenship as part of that data”).
Because the Census Bureau initiated a new collection of information of citizenship status information on March 26, 2018, the Bureau was obligated to conduct and publish the required privacy impact assessments by that date.
3. The Census Bureau has unlawfully failed to publish the required privacy impact assessments for more than nine months.
The Census Bureau failed to produce valid privacy impact assessments by March 26, 2018, and still refuses to correct its unlawful conduct despite EPIC’s repeated warnings and the
16 https://www.census.gov/programs-surveys/decennial-census/data/datasets.2010.html. 17 https://www2.census.gov/library/publications/decennial/2020/operations/planned-subjects2020-acs.pdf.
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initiation of this lawsuit. To satisfy section 208 of the E-Government Act, an agency must publish a PIA specifying, inter alia, “what information is to be collected”; “why the information is being collected”; “the intended use of the agency of the information”; “with whom the information will be shared”; and “how the information will be secured[.]” E-Government Act § 208(b)(2)(B)(ii). A PIA also “must identify what choices the agency made regarding an IT system or collection of information as a result of performing the PIA.” Ex. 15, OMB Guidance § II.C.1.b. Moreover, a PIA must be “commensurate with the size of the information system being assessed, the sensitivity of information that is in an identifiable form in that system, and the risk of harm from unauthorized release of that information[.]” E-Government Act § 208(b)(2)(B)(i); see also Ex. 15, OMB Guidance § II.C.1.b (“The depth and content of the PIA should be appropriate for the nature of the information to be collected and the size and complexity of the IT system.”). Where a PIA is required for a “major information system[]”18—for example, a Census Bureau system used to collect and process hundreds of millions of census responses—the PIA “should reflect more extensive analyses of:”
1. the consequences of collection and flow of information, 2. the alternatives to collection and handling as designed, 3. the appropriate measures to mitigate risks identified for each alternative and, 4. the rationale for the final design choice or business process. Ex. 15, OMB Guidance § II.C.2.a.ii. In such cases, a mere “checklist or template” will not satisfy an agency’s PIA obligation. Id. § II.C.2.a.iii. The Census Bureau has failed to publish a valid PIA for any of the five systems that the Bureau proposes to collect, maintain, or disseminate citizenship status information. With respect
18 A “major information system” includes any “system or project that requires special management attention because of its: (i) importance to the agency mission, (ii) high development, operating and maintenance costs, (iii) high risk, (iv) high return, (v) significant role in the administration of an agency’s programs, finances, property or other resources.” Ex. 15, OMB Guidance § II.A.4.
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to three systems (CEN05, CEN13, and CEN18), the Bureau’s failure is total. Although these systems would be used to maintain or process response data from the 2020 Census, the most recent PIA for each system does not even acknowledge that citizenship status information is among the data “to be collected.” E-Govermment Act § 208(b)(2)(B)(ii); see also Ex. 5 at 1, 4–6; Ex. 8 at 1, 3–4; Ex. 9 at 1, 3–4. Consequently, the Bureau has entirely failed to assess the privacy impact of maintaining and processing personal data concerning citizenship status with these systems. See Ex. 5; Ex. 8; Ex. 9.
The current PIAs for two other Census Bureau systems (CEN08 and CEN11) acknowledge, with a single word, that citizenship status information will be collected. See Ex. 6 at 5 (“Citizenship”); Ex. 7 at 4 (“Citizenship”). Yet neither PIA includes any analysis—let alone a “commensurate” analysis, § 208(b)(2)(B)(i)—of how the collection of this new information will impact privacy. For example, neither PIA explains “why [citizenship] information is being collected” via the census for the first time in 70 years or what “the intended use of the agency of [citizenship] information” is. § 208(b)(2)(B)(ii); see also Ex. 6; Ex. 7. Nor do the PIAs address the privacy “consequences of collection and flow of [citizenship] information”; “the alternatives to collection and handling [of citizenship information]”; “the rationale for the final design choice” to include citizenship information; or “what choices the agency made . . . as a result of performing the PIA.” Ex. 15, OMB Guidance §§ II.C.1.b, a.ii; see also Ex. 6; Ex. 7. The CEN08 PIA even indicates—without explanation or analysis—that citizenship status and other census data could be transferred in “[b]ulk” to federal agencies “[f]or criminal law enforcement activities.” Ex. 6 at 7, 9. Yet the privacy risks posed by this alarming (and illegal) possibility are nowhere addressed.
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The Census Bureau was obligated to publish valid PIAs for its collection of citizenship status information by March 26, 2018. The Bureau failed to do so. After nine months and multiple filings by EPIC notifying the Bureau of its unlawful conduct, it has still failed to do so. The Bureau is therefore in violation of section 208 of the E-Government Act.
4. EPIC’s suit satisfies the requirements for an action under the APA. EPIC is entitled to bring this suit under the Administrative Procedure Act because EPIC has been “adversely affected or aggrieved” by the Census Bureau’s violations of the EGovernment Act, 5 U.S.C. § 702, which this Court has the power to review. 5 U.S.C. §§ 704, 706. Because EPIC is a membership organization, Ex. 18, Bylaws of the Electronic Privacy Information Center §§ 2.02, 5.01–5.05 (amended Jan. 26, 2018), it is aggrieved to the same extent that EPIC’s members are. See Pharm. Research & Mfrs. of Am. v. Thompson, 259 F. Supp. 2d 39, 56 (D.D.C. 2003), aff’d, 362 F.3d 817 (D.C. Cir. 2004) (finding membership organization that “represent[ed] the interests of urban Indian Centers” therefore “ha[d] prudential standing to assert” an APA claim on behalf of those centers). First, EPIC is aggrieved by the Census Bureau’s unlawful initiation of a new collection of information without first completing the required privacy impact assessments. Id.; see also Complaint ¶¶ 64–70. By “direct[ing] the Census Bureau to place the citizenship question . . . on the decennial census form” after “a thorough review of the legal, program, and policy considerations,” Ex. 1 at 8, Secretary Ross took “final agency action” on behalf of the Bureau. § 704. “There is no dispute the Secretary Ross’s decision constitutes ‘final agency action’ reviewable under the APA.” New York, No. 18-CV-2921 (JMF), 2019 WL 190285; see also Kravitz v. Dep’t of Commerce, No. GJH-18-1041, 2018 WL 6830226, at *1, *6 (D. Md. Dec. 28, 2018) (analyzing the “U.S. Census Bureau’s decision to include a citizenship question on the
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2020 Census” as a “final agency action”). This action was final because it “mark[ed] the consummation of the agency’s decisionmaking process” and is a decision “by which rights or obligations have been determined, or from which legal consequences will flow[.]” Ipsen Biopharmaceuticals, Inc. v. Hargan, 334 F. Supp. 3d 274, 277 (D.D.C. 2018) (quoting U.S. Army Corps of Eng’rs v. Hawkes Co., 136 S. Ct. 1807, 1813 (2016)); see also 13 U.S.C. § 221(a)–(b) (requiring all persons over 18 to respond to census questions). Moreover, the Bureau’s final agency action violated section 208 of the E-Government Act, a provision whose purpose is to “is to ensure sufficient protections for the privacy of personal information[.]” § 208(a); see also EPIC, 878 F.3d at 378 (explaining that section 208 of the E-Government Act “protect[s] individuals . . . by requiring an agency to fully consider their privacy before collecting their personal information” (emphasis in original)). EPIC is thus aggrieved by the Bureau’s action, which unlawfully imperils the privacy of EPIC’s members and has denied them information to which they are legally entitled. See Ex. 10 ¶¶ 11–15; Ex. 11 ¶¶ 11–15; Ex. 12 ¶¶ 11–15. Finally, this Court has the power to “hold unlawful and set aside” the Bureau’s action because it is “not in accordance with law” and was carried out “without observance of procedure required by law[.]” § 706(2); see also § 704.
Second, EPIC is “aggrieved” by the Census Bureau’s unlawful failure to complete the required privacy impact assessments for the collection of citizenship status information. An agency “unlawfully with[olds]” action under § 706 the APA when it fails to take a “discrete action that the agency has a duty to perform.” W. Org. of Res. Councils v. Zinke, 892 F.3d 1234, 1241 (D.C. Cir. 2018) (citing Norton v. Southern Utah Wilderness Alliance (SUWA), 542 U.S. 55, 62–63 (2004)). Here, the Bureau failed to take the discrete actions of conducting, reviewing, and publishing required privacy impact assessments before “initiating a new collection of
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information,” as mandated by section § 208(b) of the E-Government Act. These duties are “nondiscretionary” and amount to “specific, unequivocal command[s].” W. Org. of Res. Councils, 892 F.3d at 1241 (quoting SUWA, 542 U.S. at 63–64); see also E-Government Act § 208(b)(1)(A) (“An agency shall take actions described under subparagraph (B)[.]”). By failing to conduct or publish PIAs for the collection of citizenship status information, the Bureau has failed to “ensure sufficient protections for the privacy of personal information,” § 208(a), and failed to “fully consider the[ ] privacy” of individuals whose personal data would be collected. EPIC, 878 F.3d at 378. EPIC is thus aggrieved by the Bureau’s inaction, which unlawfully imperils the privacy of EPIC’s members and has denied them information to which they are legally entitled. See Ex. 10 ¶¶ 11–15; Ex. 11 ¶¶ 11–15; Ex. 12 ¶¶ 11–15. Finally, this Court has the power to “compel agency action unlawfully withheld or unreasonably delayed” under 5 U.S.C. § 706(1). As the D.C. Circuit recently explained, “the court can undertake review [under § 706(1)] as though the agency had denied the requested relief and can order an agency to either act or provide a reasoned explanation for its failure to act.” Friedman v. FAA, 841 F.3d 537, 545 (D.C. Cir. 2016) (quoting Sierra Club v. Thomas, 828 F.2d 783, 793 (D.C. Cir. 1987)).
Because EPIC is aggrieved by the Census Bureau’s violations of the E-Government Act and the APA, and because this Court has the power to review and remedy those violations, EPIC “is likely to succeed on the merits” of its claims. Navajo Nation, 292 F. Supp. 3d at 512 (quoting Winter, 555 U.S. at 22).
B. EPIC will suffer irreparable harm absent an injunction. EPIC and its members will “suffer irreparable harm in the absence of preliminary relief” in three ways. Navajo Nation, 292 F. Supp. 3d at 512 (quoting Winter, 555 U.S. at 22). First, EPIC and its members will be irreparably harmed—and have already been harmed—by the
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Census Bureau’s failure to disclose “information [that] is highly relevant to an ongoing and highly public matter.” EPIC v. Presidential Advisory Comm'n on Election Integrity, 266 F. Supp. 3d 297, 319 (D.D.C.), aff’d on other grounds, 878 F.3d 371. Second, EPIC and its members will be irreparably harmed—and have already been harmed—by “the failure of decision-makers” to take privacy “factors into account in the way that” the E-Government Act mandates. Jones v. D.C. Redevelopment Land Agency, 499 F.2d 502, 512 (D.C. Cir. 1974). Third, EPIC and its members will be irreparably harmed if the Bureau is permitted invade the privacy of EPIC’s members by unlawfully compelling disclosure of their citizenship status.
First, the Census Bureau’s failure to publish valid privacy impact assessments irreparably harms EPIC by denying EPIC’s members information vital to the national debate over the inclusion of the citizenship question on the 2020 Census. As the D.C. Circuit has emphasized, “stale information is of little value[.]” Judicial Watch, Inc. v. DHS, 895 F.3d 770, 778 (D.C. Cir. 2018) (quoting Payne Enters., Inc. v. United States, 837 F.2d 486, 494 (D.C. Cir. 1988)); see also Byrd v. EPA, 174 F.3d 239, 244 (D.C. Cir. 1999) (“Byrd’s injury, however, resulted from EPA’s failure to furnish him with the documents until long after they would have been of any use to him.”). Thus, “the non-disclosure of information to which a plaintiff is entitled, under certain circumstances itself constitutes an irreparable harm; specifically, where the information is highly relevant to an ongoing and highly public matter.” EPIC, 266 F. Supp. 3d at 319; see also EPIC v. DOJ, 416 F. Supp. 2d 30, 41 (D.D.C. 2006) (“EPIC will also be precluded, absent a preliminary injunction, from obtaining in a timely fashion information vital to the current and ongoing debate surrounding the legality of the Administration's warrantless surveillance program.”); Washington Post v. DHS, 459 F. Supp. 2d 61, 75 (D.D.C. 2006) (“Because the urgency with which the plaintiff makes its FOIA request is predicated on a matter of current
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national debate, due to the impending election, a likelihood for irreparable harm exists if the plaintiff's FOIA request does not receive expedited treatment.”).
The collection of citizenship status information through the 2020 Census is inarguably “an ongoing and highly public matter.” EPIC, 266 F. Supp. 3d at 319. The Census Bureau has resolved to collect the citizenship status of hundreds of millions of persons nationwide, a controversial decision that has been the subject of tens of thousands of articles of interest to the public. See “Census” and “Citizenship”, Google News (Jan. 13, 2019)19 (identifying more than 57,000 news articles containing the words “Census” and “Citizenship”). The Bureau’s decision to initiate the collection of citizenship status information is the subject of at least six other federal lawsuits,20 one of which was significant enough to warrant the Supreme Court’s granting of a mandamus petition to review an interlocutory order. In re Dep’t of Commerce, No. 18-557, 2018 WL 5458822, at *1. And the window for public debate is rapidly closing: the Bureau has stated that the “printing, addressing, and mailing of Internet invitations, reminder cards or letters, and paper questionnaire packages” for the 2020 Census must begin by June 2019. U.S. Census Bureau, 2020 Census Operational Plan: A New Design for the 21st Century, supra, at 89; see also New York, No. 18-CV-2921 (JMF), 2019 WL 190285, at *88 (noting that “the Census Bureau ‘need[s] to begin printing the 2020 census questionnaire’ in June 2019”); Ex. 19, Census Progress Report: Hearing Before the H. Comm. on Gov’t Oversight & Reform, 115 Cong. 9
19 https://www.google.com/search?q=%22Census%22+and+%22Citizenship%22&tbm=nws. 20 See New York, No. 18-CV-2921 (JMF), 2019 WL 190285; New York Immigration Coal. v. Dep't of Commerce, No. 18-CV-5025 (JMF), 2019 WL 190285 (S.D.N.Y. Jan. 15, 2019); Kravitz v. Dep’t of Commerce, No. GJH-18-1041, 2018 WL 6830226; La Union del Pueblo Entero v. Ross, No. GJH-18-1570, 2018 WL 5885528 (D. Md. Nov. 9, 2018); California v. Ross, No. 18-1865 (N.D. Cal. filed March 26, 2018); City of San Jose v. Ross, No. 18-2279 (N.D. Cal. filed Apr. 17, 2018).
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(2018) (statement of Ron Jarmin, Dir., U.S. Census Bureau) (“The physical printing of the majority of the paper materials for the 2020 Census will begin in June 2019.”).
The privacy impact assessments that the Census Bureau has unlawfully withheld are also “highly relevant” to the ongoing debate over the planned citizenship question. EPIC, 266 F. Supp. 3d at 319. In failing to publish valid assessments, the Bureau has denied EPIC and its members critical details about the methods and systems used to process personal data concerning citizenship status, leaving EPIC “little if any information about prospective [] harms and potential mitigating measures.” Winter, 555 U.S. at 23. The Bureau has thus irreparably harmed—and will continue to harm—the ability of EPIC’s members to learn about, analyze, and debate the privacy implications of collecting citizenship status information through the census. See Ex. 10 ¶¶ 14–15 (“I am unable to determine whether the Census Bureau has fully considered or addressed the risks to my privacy, even as the Bureau begins to develop a new collection of personal data that will contain my citizenship status.”); Ex. 11 ¶¶ 14–15 (same); Ex. 12 ¶¶ 14–15 (same). The requested injunction would avoid further such harm to EPIC by ensuring that the Bureau does not acquire any personal data concerning citizenship status before this Court has fully assessed the Bureau’s compliance (or non-compliance) with the E-Government Act. Absent such an injunction, EPIC will suffer harm “beyond remediation.” Chaplaincy of Full Gospel Churches v. England, 454 F.3d 290, 297 (D.C. Cir. 2006). EPIC’s ability to meaningfully debate or challenge a planned act of government—here, the acquisition of citizenship information— cannot be restored after the government has already acted.
Second, the Census Bureau’s failure to conduct and publish valid privacy impact assessments causes irreparable harm to EPIC and its members by undermining the “protections for the privacy of personal information” established by Congress. E-Government Act § 208(a).
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The E-Government Act “protect[s] individuals . . . by requiring an agency to fully consider their privacy before collecting their personal information.” EPIC, 878 F.3d at 378 (emphasis in original). When an agency bypasses the privacy safeguards set out in section 208, the agency unlawfully endangers the privacy of those whose personal data will be collected. The EGovernment Act is directly analogous to National Environmental Policy Act (“NEPA”) in this way. The NEPA requires federal agencies to publish an environment impact statement (“EIS”) before taking “actions significantly affecting the quality of the human environment.” 42 U.S.C. § 4332(2)(C). The D.C. Circuit has long held that a violation of the NEPA’s EIS requirement— like a violation of the E-Government Act’s PIA requirement—works an irreparable harm by undermining the agency’s decisionmaking process:
The harm against which NEPA's impact statement requirement was directed was not solely or even primarily adverse consequences to the environment; such consequences may ensue despite the fullest compliance. Rather NEPA was intended to ensure that decisions about federal actions would be made only after responsible decisionmakers had fully adverted to the environmental consequences of the actions, and had decided that the public benefits flowing from the actions outweighed their environmental costs. Thus, the harm with which courts must be concerned in NEPA cases is not, strictly speaking, harm to the environment, but rather the failure of decision-makers to take environmental factors into account in the way that NEPA mandates. And, for purposes of deciding whether equitable relief is appropriate, we think that this harm matures simultaneously with NEPA's requirements, i.e., at the time the agency is, under NEPA, obliged to file the impact statement and fails to do so. Jones, 499 F.2d at 512 (citing Calvert Cliffs’ Coordinating Comm., Inc. v. AEC, 449 F.2d 1109, 1115 (1971); Lathan v. Volpe, 455 F.2d 1111, 1116–17 (9th Cir. 1971)); accord Illinois Commerce Comm’n v. ICC, 848 F.2d 1246, 1259 (D.C. Cir. 1988). So too here: the failure of the Bureau to take privacy risks into account when reviewing its proposed collection, as mandated by the E-Government Act, works an irreparable harm to those whose citizenship status information will be collected (including EPIC’s members). That harm has already “mature[d],”
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in that the Bureau was “obliged to file the impact statement and fail[ed] to do so.” Jones, 499 F.2d at 512.
Moreover, a preliminary injunction will ensure that compliance with the E-Government Act “take[s] place before there has been an ‘irretrievable commitment of resources,’” Jones, 499 F.2d at 512 (quoting Lathan, 455 F.2d at 1121), such as the “printing, addressing, and mailing of Internet invitations, reminder cards or letters, and paper questionnaire packages” in June 2019. U.S. Census Bureau, 2020 Census Operational Plan: A New Design for the 21st Century, supra, at 89. As the D.C. Circuit has explained regarding environmental impact statements:
The purpose of equitable intervention in cases in which federal agencies have failed to comply with NEPA's requirements is to ensure that such compliance will take place before there has been an ‘irretrievable commitment of resources.’ It may be that preparation of the statement will, in the end, not move the agency from adherence to decisions it has already made. But it is not for the courts to prejudge. So long as the status quo is maintained, so long as the environmental impact statement is not merely a justification for a fait accompli, there is a possibility that the statement will lead the agency to change its plans in ways of benefit to the environment. It is this possibility that the courts should seek to preserve. Jones, 499 F.2d at 512–13 (quoting Lathan, 455 F.2d at 1121); cf. Pub. Employees for Envtl. Responsibility v. United States Fish & Wildlife Serv., 189 F. Supp. 3d 1, 2 (D.D.C. 2016) (quoting Realty Income Tr. v. Eckerd, 564 F.2d 447, 456 (D.C. Cir. 1977)) (“[W]hen an action is being undertaken in violation of NEPA, there is a presumption that injunctive relief should be granted against continuation of the action until the agency brings itself into compliance.”). For the same reasons, the Court should issue a preliminary injunction here to preserve the possibility that the Census Bureau will “change its plans in ways of benefit to” privacy. Jones, 499 F.2d at 512–13. Without such an injunction, the Bureau’s decisionmaking process—and the privacy interests of EPIC’s members—will be further harmed “beyond remediation.” Chaplaincy of Full Gospel Churches, 454 F.3d at 297.
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Finally, EPIC and its members will be irreparably harmed if the Census Bureau unlawfully acquires personal data concerning citizenship status from EPIC’s members. The nonconsensual or compelled disclosure of one’s personal information to a party who is not legally entitled to it constitutes irreparable harm. United States v. Hubbard, 650 F.2d 293, 314 n.73 (D.C. Cir. 1980) (finding a “serious threat of irreparable harm to the property and the privacy interests advanced” where the government seized documents from a church containing personal information of the church’s members); see also Hirschfeld v. Stone, 193 F.R.D. 175, 187 (S.D.N.Y. 2000) (“The harm at issue here—disclosure of confidential information—is the quintessential type of irreparable harm that cannot be compensated or undone by money damages.”); Nat’l Fed’n of Fed. Emps. v. Greenberg, 789 F. Supp. 430, 438 (D.D.C. 1992) (“[I]rreparable injury flows not only from the employee's failure to complete the form or to complete it in a manner that the Department deems unacceptable; the intrusive nature of the compelled disclosure itself also constitutes such injury.”), vacated on other grounds, 983 F.2d 286 (D.C. Cir. 1993).
Absent an injunction blocking the Census Bureau’s acquisition of citizenship status information and printing of census forms, EPIC’s members will necessarily suffer such harm. Just two weeks ago, the Bureau reiterated its earlier decision to collect citizenship status information in a filing to the OMB. Submission for OMB Review, 83 Fed. Reg. at 67,216 (“The proposed questions for the 2020 Census questionnaire include age, citizenship, Hispanic origin, race, relationship, sex, and tenure.”).
The Census Bureau’s collection of citizenship status information will irreparably harm EPIC by denying it information critical to an ongoing nationwide debate, by disregarding privacy safeguards established by Congress, and by unlawfully compelling disclosure of personal data
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concerning citizenship status from EPIC’s members. Each day that the Bureau fails to produce valid privacy impact assessments, the census printing deadline (and the census itself) approaches, and the irreparability of the harms suffered by EPIC increases. The Court should therefore enter a preliminary injunction to prevent irreparable injury to EPIC and to ensure adequate time for a final decision on the merits of EPIC’s claims.
C. The equities and the public interest weigh in favor of an injunction. The Court should enter a preliminary injunction as an equitable matter because “the ‘balance of equities’ tips in [the plaintiff’s] favor” and “‘an injunction is in the public interest.’” Navajo Nation, 292 F. Supp. 3d at 512 (quoting Winter, 555 U.S. at 22). These final two factors of the four-factor test “merge when the Government is the opposing party.” Id. (quoting Nken v. Holder, 556 U.S. 418, 435 (2009)). EPIC has a powerful equitable interest in avoiding the irreparable harms that will result if the Census Bureau continues its unlawful collection of citizenship status information without first conducting and publishing valid privacy impact assessments. See Part I.B, supra. For example, the equities favor enabling EPIC to review to the agency’s assessment of privacy risks before the citizenship question is fully implemented. See EPIC, 266 F. Supp. 3d at 319 (holding that a denial of “information [that] is highly relevant to an ongoing and highly public matter” works an irreparable harm). Indeed, EPIC’s informational interest in this matter is uniquely strong. EPIC is the premiere organization in the country working to enforce agencies’ EGovernment Act obligations, Complaint ¶ 8 (collecting EPIC PIA cases), and EPIC has been a leading advocate of census privacy protections for nearly two decades. Id. ¶ 9. As an organization dedicated to both privacy and open government, EPIC is uniquely equipped to evaluate the Bureau’s PIAs and to inform EPIC’s members and the public about the Bureau’s
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compliance with the E-Government Act. See Complaint ¶ 6; EPIC, EPIC FOIA Cases (Sep. 17, 2018)21 (collecting dozens of EPIC Freedom of Information Act cases resulting in the disclosure of thousands of privacy-related records). EPIC also has a strong equity in ensuring EGovernment Act compliance “before there has been an ‘irretrievable commitment of resources’” by the Bureau, Jones, 499 F.2d at 512 (quoting Lathan, 455 F.2d at 1121), and EPIC’s members have an urgent need to avoid the unlawful collection of their citizenship status information. See Ex. 10 ¶ 15; Ex. 11 ¶ 15; Ex. 12 ¶ 15.
The equities also favor an injunction because the Census Bureau has ignored four prior warnings from EPIC, including the filing of the Complaint in this matter, concerning the Bureau’s noncompliance with section 208. First, on August 7, 2018, EPIC explained in comments to the Census Bureau that the Bureau had “not undertaken an appropriate analysis of the privacy risks of the citizenship question.” Ex. 13 at 5. Second, on October 2, 2018, EPIC published a statement to the Senate Committee on Homeland Security & Government Affairs urging—in advance of a hearing on the Census—that the Bureau “should conduct a new PIA dealing specifically with the issues raised by the citizenship question.” Ex. 14 at 4. Third, on Oct. 29, 2018, EPIC filed an amicus brief in New York v. Department of Commerce arguing that “the Bureau has not adequately justified the collection of citizenship information or shown that it has implemented the safeguards necessary to protect the data that it collects.” Br. of EPIC as Amicus Curiae in Supp. Pls.’ Position at Trial at 20, New York, No. 18-CV-2921 (JMF), 2019 WL 190285. Finally, on Nov. 20, 2018, EPIC filed a (and subsequently served) a Complaint in this case alerting the Defendants that they had “failed to conduct any of the privacy analysis required by the E-Government Act for a major collection of personally identifiable information.”
21 https://www.epic.org/foia/.
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Complaint ¶ 63. Despite these repeated warnings from EPIC over the past five months, the Bureau has taken no apparent measures to remedy its noncompliance with section 208. Instead, the Bureau has doubled down on its collection of citizenship status information. See Submission for OMB Review, 83 Fed. Reg. at 67,216.
There are few, if any, equities “to overcome the much more substantial countervailing harms” to EPIC. League of Women Voters of United States v. Newby, 838 F.3d 1, 13 (D.C. Cir. 2016)” Although federal agencies and the public have an interest in the sound administration of federal law, “there is generally no public interest in the perpetuation of unlawful agency action.” Id. at 12 (citing Pursuing America’s Greatness v. FEC, 831 F.3d 500, 511-12 (D.C. Cir. 2016); Gordon v. Holder, 721 F.3d 638, 653 (D.C. Cir. 2013)). To the contrary: “there is a substantial public interest in having governmental agencies abide by the federal laws that govern their existence and operations.” Id.
Neither the Census Bureau nor the public at large has a cognizable interest in the collection of citizenship status information absent the required assessments of privacy risks. Congress has already balanced the competing interests of privacy and data collection by enacting E-Government § 208(b), which prohibits collection without assessment. The Court should not hesitate to equitably enforce that Congressionally-struck balance. Cf. Realty Income Tr., 564 F.2d at 456 (“[W]hen an action is being undertaken in violation of NEPA, there is a presumption that injunctive relief should be granted against continuation of the action until the agency brings itself into compliance.”); Youngstown Sheet & Tube Co. v. Sawyer, 343 U.S. 579, 609–10 (1952) (Frankfurter, J., concurring). (“When Congress itself has struck the balance, has defined the weight to be given the competing interests, a court of equity is not justified in ignoring that pronouncement under the guise of exercising equitable discretion.”).
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Even if the Census Bureau were legally permitted to collect citizenship status information without first evaluating the attendant privacy risks, the public interest would strongly disfavor such a collection. Permitting federal agencies to collect personal data without first conducting a privacy impact assessment endangers privacy and curtails public understanding of government decisionmaking. That is why Congress imposed a government-wide PIA requirement in the first place: “[t]o make the Federal Government more transparent and accountable” and “to ensure sufficient protections for the privacy of personal information[.]” E-Government Act §§ 2(b)(9), 208(a). Nowhere is the duty to assess privacy risks more important than the decennial census, a “unique” and compulsory collection of data that “reaches every population group, from America’s long-time residents to its most recent immigrants.” Presidential Proclamation No. 7,286, 65 Fed. Reg. at 17,985. Moreover, the public interest leans heavily against the implementation of the citizenship question because—as the Census Bureau’s chief scientist recently noted—adding the question would be “very costly, harms the quality of the census count, and would [result in] substantially less accurate citizenship status data than are available from administrative sources.” See Ex. 4 at 1.
The public interest also favors injunctive relief at this stage because there is likely to be an “irretrievable”—and potentially wasteful—“commitment of resources” by the Census Bureau absent a preliminary order halting the citizenship question. Jones, 499 F.2d at 512 (quoting Lathan, 455 F.2d at 1121). As the Bureau has argued, “finalizing the decennial census questionnaire is time-sensitive,” and it is “important to resolve as soon as possible” the key legal issues concerning the 2020 Census. Petition for a Writ of Mandamus at 15, In re Dep’t of Commerce, No. 18-557, 2018 WL 5458822 (U.S. Nov. 16, 2018). If no injunction issues prior to final judgment in this case, the Bureau will likely expend significant resources in the meantime
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implementing the citizenship question—a question that this Court may later deem unlawful. See, e.g., U.S. Census Bureau, 2020 Census Operational Plan: A New Design for the 21st Century, supra, at 89 (noting that the “printing, addressing, and mailing of Internet invitations, reminder cards or letters, and paper questionnaire packages” for the 2020 Census will begin by June 2019).
Because the balance of the equities and the public interest strongly favor a halt to the Census Bureau’s implementation of the citizenship question, the Court should grant EPIC’s motion for a preliminary injunction. The requested injunction is carefully tailored to address the privacy implications of the citizenship question and poses no impediment to other census operations or questions. II. EPIC HAS ARTICLE III STANDING IN THIS MATTER.
EPIC has Article III standing to bring this suit because EPIC’s members have suffered “concrete injur[ies]-in-fact that [are] fairly traceable to the defendant[s’] action[s] and capable of being redressed by a favorable judicial decision.” Conference of State Bank Supervisors v. Office of Comptroller of Currency, 313 F. Supp. 3d 285, 294 (D.D.C. 2018) (quoting Summers v. Earth Island Inst., 555 U.S. 488, 493 (2009)). For the purposes of determining Article III jurisdiction, courts must accept the plaintiff’s “view of the law” on which the plaintiff’s claims are based, FEC v. Akins, 524 U.S. 11, 21 (1998), so long as it is nonfrivolous. See Steel Co. v. Citizens for a Better Env’t, 523 U.S. 83, 89 (1998) (“It is firmly established in our cases that the absence of a valid (as opposed to arguable) cause of action does not implicate subject-matter jurisdiction, i.e., the courts’ statutory or constitutional power to adjudicate the case.”).
EPIC is a membership association. Ex. 18 §§ 2.02, 5.01–5.05. As such, EPIC has standing to sue on behalf of its members whenever “(1) [EPIC’s] members would otherwise have standing to sue in their own right; (2) the interests [EPIC] seeks to protect are germane to the
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organization’s purpose; and (3) neither the claim asserted nor the relief requested requires the participation of individual members in the lawsuit.” Sorenson Commc’ns, LLC v. FCC, 897 F.3d 214, 224 (D.C. Cir. 2018) (quoting Ctr. for Sustainable Econ. v. Jewell, 779 F.3d 588, 596 (D.C. Cir. 2015)) (internal quotation marks omitted). EPIC readily satisfies these criteria here.
First, EPIC’s members would have standing to bring this suit on their own because they have suffered judicially redressable injuries caused by the Census Bureau that are “concrete, particularized, and actual or imminent.” Conference of State Bank Supervisors, 313 F. Supp. 3d at 295 (quoting Clapper v. Amnesty Int'l USA, 568 U.S. 398, 409 (2013)). EPIC’s members sought and were denied information which the Government is required to disclose under section 208 of the E-Government Act: namely, “comprehensive and meaningful” assessments of how the collection, processing, and storage of their personal citizenship information will affect their privacy. Ex. 15, OMB Guidance § II.C.2.a.b; see also Ex. 10 ¶¶ 11–15; Ex. 11 ¶¶ 11–15; Ex. 12 ¶¶ 11–15. These injuries are concrete: “a plaintiff suffers an ‘injury in fact’ when”—as here— “the plaintiff fails to obtain information which must be publicly disclosed pursuant to a statute.” Akins, 524 U.S. at 21 (quoting Public Citizen v. DOJ, 491 U.S. 440, 449 (1989)); see also Spokeo, Inc. v. Robins, 136 S. Ct. 1540, 1549–50 (2016) (reiterating the Akins–Public Citizen rule that a denial of information that Congress has ordered disclosed “constitute[s] injury in fact”). These injuries are particularized: EPIC’s members each have an individual interest in obtaining the information unlawfully denied to them. See Public Citizen, 491 U.S. at 449–50 (“The fact that other citizens or groups of citizens might make the same complaint after unsuccessfully demanding disclosure . . . does not lessen appellants' asserted injury[.]”); EPIC, 878 F.3d at 378 (emphasizing that section 208 of the E-Government Act “protect[s] individuals”). These injuries are actual: the Government was required—and failed—to disclose
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the information sought by EPIC’s members before initiating a collection of personal data concerning citizenship status. E-Government Act § 208(b)(1)(A). And these injuries would be redressed by favorable decision of this Court ordering the Census Bureau (1) to conduct and publish legally sufficient privacy impact assessments and (2) to halt the process of collecting personal citizenship information unless and until such PIAs have been completed. See Compl. p. 27 (“Requested Relief”).
Second, the interests EPIC seeks to protect through this suit—the right to privacy and access to information about government data collection activities—are the very core of EPIC’s organizational mission. E.g., Ex. 18 § 1.02 (“The Corporation is organized for the charitable and educational purposes of promoting personal privacy and constitutional rights.”); Ex. 10 ¶ 4 (“Central to EPIC’s mission is oversight of government activities that impact individual privacy, free expression, and democratic values.”); EPIC, EPIC FOIA Cases, supra. EPIC therefore satisfies the requirement of “pertinence between litigation subject and organizational purpose.” Ctr. for Sustainable Econ., 779 F.3d at 597.
Finally, neither the claims nor the relief at issue in this case require the direct participation of EPIC’s members. “Member participation is not required where a ‘suit raises a pure question of law’ and neither the claims pursued nor the relief sought require the consideration of the individual circumstances of any aggrieved member of the organization.” Id. at 597 (quoting Int’l Union, United Auto., Aerospace & Agric. Implement Workers of Am. v. Brock, 477 U.S. 274, 287–88 (1986)). The Government’s unlawful initiation of a collection of information and failure to publish valid PIAs present pure questions of law. This suit does not implicate the specific factual circumstances of individual EPIC members beyond what those
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members have already declared. See Ex. 10; Ex. 11; Ex. 12. EPIC therefore has associational standing to bring this suit on behalf of EPIC’s members.
CONCLUSION For the foregoing reasons, the Court should grant EPIC’s motion for a preliminary injunction.

Dated: January 18, 2018

Respectfully Submitted,
MARC ROTENBERG, D.C. Bar #422825 EPIC President and Executive Director
ALAN BUTLER, D.C. Bar #1012128 EPIC Senior Counsel
/s/ John Davisson JOHN DAVISSON, D.C. Bar #1531914 EPIC Counsel
ELECTRONIC PRIVACY INFORMATION CENTER 1718 Connecticut Avenue, N.W. Suite 200 Washington, D.C. 20009 (202) 483-1140 (telephone) (202) 483-1248 (facsimile)
Attorneys for Plaintiff EPIC

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IN THE UNITED STATES DISTRICT COURT FOR THE DISTRICT OF COLUMBIA

ELECTRONIC PRIVACY INFORMATION CENTER, Plaintiff, v.
UNITED STATES DEPARTMENT OF COMMERCE, et al.,
Defendants.

Civ. Action No. 18-2711 (DLF)

[PROPOSED] ORDER Upon consideration of the Plaintiff’s Motion for a Preliminary Injunction, the Defendants’ Response, and the entire record, it is hereby ORDERED that the Plaintiff’s Motion is GRANTED; and it is FURTHER ORDERED that Defendants United States Department of Commerce and Bureau of the Census are enjoined from implementing the Defendants’ March 26, 2018 decision to add a citizenship question to the 2020 Census; and it is FURTHER ORDERED that Defendants United States Department of Commerce and Bureau of the Census are enjoined from initiating any collection of citizenship status information that would be obtained through the 2020 Census.

Date: ________________________

_________________________________ DABNEY L. FRIEDRICH United States District Judge
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EXHIBIT LIST
Letter from Wilbur Ross, Secretary of Commerce, to Karen Dunn Kelley, Under Secretary for Economic Affairs, at 8 (Mar. 26, 2018)....................................... Ex. 1
U.S. Census Bureau, Questions Planned for the 2020 Census and American Community Survey (March 2018) ................................................................ Ex. 2
Latanya Sweeney, Simple Demographics Often Identify People Uniquely (Carnegie Mellon Univ., Data Privacy Working Paper No. 3, 2000) .......................... Ex. 3
Memorandum from John M. Abowd, Chief Scientist, U.S. Census Bureau, to Wilbur L. Ross, Sec’y of Commerce (Jan. 19, 2018) .............................................. Ex. 4
U.S. Dep’t of Commerce, Privacy Impact Assessment for the CEN05 Field Systems Major Application System (approved June 22, 2018) ..................................... Ex. 5
U.S. Dep’t of Commerce, Privacy Impact Assessment for the CEN08 Decennial Information Technology Division (DITD) (approved Sep. 28, 2018) ............................................................................................................................. Ex. 6
U.S. Dep’t of Commerce, Privacy Impact Assessment for the CEN11 Demographic Census, Surveys, and Special Processing.............................................. Ex. 7
U.S. Dep’t of Commerce, Privacy Impact Assessment for the CEN13 Center for Economic Studies (CES) (approved June 26, 2018) ................................... Ex. 8
U.S. Dep’t of Commerce, Privacy Impact Assessment for the CEN18 Enterprise Applications (approved June 26, 2018) ...................................................... Ex. 9
Declaration of Christopher Wolf (Nov. 29, 2018) ..................................................... Ex. 10
Declaration of Bruce Schneier (Nov. 29, 2018) ......................................................... Ex. 11
Declaration of Harry R. Lewis (Dec. 3, 2018) ........................................................... Ex. 12
EPIC, Comments of EPIC to the U.S. Census Bureau (Aug. 7, 2018) ....................... Ex. 13
Statement from EPIC to Ron Johnson, Chairman, Senate Comm. on Homeland Sec. & Gov’t Affairs, et al. (Oct. 2, 2018)................................................ Ex. 14
Joshua B. Bolten, Dir., OMB, Executive Office of the President, M03-22, Memorandum for Heads of Executive Departments and Agencies, Attachment A (Sept. 26, 2003) (“OMB Guidance”) .................................................. Ex. 15
U.S. Dep’t of Commerce, United States Census 2010 (2009) ................................... Ex. 16

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U.S. Dep’t of Commerce, U.S. Census Bureau Privacy Impact Assessments (PIAs) and Privacy Threshold Analysis (PTA) (Dec. 13, 2016) ............ Ex. 17 Bylaws of the Electronic Privacy Information Center (amended Jan. 26, 2018) ........................................................................................................................... Ex. 18 Census Progress Report: Hearing Before the H. Comm. on Gov’t Oversight & Reform, 115 Cong. 9 (2018) (statement of Ron Jarmin, Dir., U.S. Census Bureau) .......................................................................................... Ex. 19

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Exhibit 1

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UNNIITTEEDDSTTAATTEESSDEEPPAARRTTMMEENNTTOFF COOMMMMEERRCCEE
The Secretary of Commerce Wasshhiinnggttoonn, D.CC. 2023300

To: Kareenn Dunnn Kellleeyy,, Undeerr Secreettaarryy for Econnoommiicc Affaiirrss

lUJ ~ ~ Frroomm:: Secrettaarryy Wilbbuurr Ross

~~

Datee:: Marcchh 26,22001188

Re: Reinnssttaatteemmeenntt of a Citizzeennsshhiipp Quessttiioonn on the 20200 Deceennnniiaall Censsuuss Quessttiioonnnnaaiirree

Dearr Undeerr Secreettaarryy Kelleeyy::
As you knoww,, on Deceemmbbeerr 12,22001177, , the Deppaarrttmmeenntt of Justiccee ("DOOJJ"")) requeesstteedd that the Censsuuss Bureeaauu reinssttaattee a citizeennsshhiipp quessttiioonn on the decennnniiaall censuuss to provviiddee censuuss blockk levell citizeennsshhiipp votinngg age popuullaattiioonn ("CVVAP")) data that are not curreennttllyy availlaabbllee fromm goveerrnnmmeenntt surveeyy data ("DOOJJ requeesstt"")).. DOJJ and the courttss use CVAP data for deterrmmiinniinngg viollaattiioonnss of Sectiioonn 2 of the Votinngg Righhttss Act ("VRRAA"")),, and havinngg thesee data at the censuuss blockk levell will permmiitt moree effeccttiivvee enforrcceemmeenntt of the Act. Sectioonn 2 proteeccttss minoorriittyy popuullaattiioonn votinngg righttss..
Folloowwiinngg receiipptt of the DOJ requeesstt,, I set out to take a hard look at the requeesstt and ensurree that I consiiddeerreedd all factss and data relevvaanntt to the questtiioonn so that I couldd makee an inforrmmeedd decissiioonn on how to respoonndd.. To that end, the Depaarrttmmeenntt of Commmmeerrccee ("Deeppaarrttmmeennt"t")) immeeddiiaatteellyy initiaatteedd a compprreehheennssiivvee revieeww proceessss led by the Censsuuss Bureeaauu..
The Depaarrttmmeenntt and Censsuuss Bureeaauu''ss revieeww of the DOJJ requeesstt-- as with all signiiffiiccaanntt Censsuuss assessssmmeennttss - priorriittiizzeedd the goal of obtaiinniinngg compplleettee and accuurraattee data.. The deceennnniiaall censuuss is mannddaatteedd in the Conssttiittuuttiioonn and its data are reliedd on for a myriiaadd of impoorrttaanntt goveerrnnmmeenntt decissiioonnss,, incluuddiinngg appoorrttiioonnmmeenntt of Conggrreessssiioonnaall seatss amonngg statess,, enforrcceemmeenntt of votinngg righttss laws,, and alloccaattiioonn of federraall fundss.. Thessee are founddaattiioonnaall elemmeennttss of our demooccrraaccyy,, and it is thereeffoorree incummbbeenntt uponn the Deppaarrttmmeenntt and the Censsuuss Bureeaauu to makee everyy efforrtt to proviiddee a compplleettee and accurraattee decennnniiaall censuuss..
At my direccttiioonn,, the Censsuuss Bureaauu and the Depaarrttmmeenntt's's Officcee of the Secreettaarryy begaann a thoroouugghh assessssmmeenntt that incluuddeedd legal,, progrraamm,, and policcyy consiiddeerraattiioonnss.. As part of the proceessss,, I also met with Censsuuss Bureeaauu leadeerrsshhiipp on multiippllee occassiioonnss to discuussss their proceessss for revieewwiinngg the DOJ requeesstt,, their data analyyssiiss,, my questtiioonnss aboutt accurraaccyy and respoonnssee ratess,, and their recommmmeennddaatitoionnss. . At preseenntt,, the Censsuuss Bureeaauu leadeerrsshhiipp are all careeerr civil servaannttss.. In addittiioonn,, my staff and I revieewweedd over 50 incommiinngg letterrss fromm stakeehhoollddeerrss,, intereesstt grouppss,, Memmbbeerrss of Conggrreessss,, and state and locall officiiaallss regarddiinngg reinssttaatteemmeenntt of a citizeennsshhiipp questtiioonn on the 20200 decennnniiaall censuuss,, and I persoonnaallllyy had speciiffiicc convveerrssaattiioonnss on
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the citizeennsshhiipp quessttiioonn withh overr 24 divveerrssee,, well inforrmmeedd and inteerreesstteedd partiieess repreesseennttiinngg a broaadd ranggee of viewwss.. My stafff and I havee also monniittoorreedd presss coveerraaggee of this issuee..
Conggrreessss has deleggaatteedd to me the authoorriittyy to deterrmmiinnee whicchh quessttiioonnss shouulldd be askeedd on the . deceennnniiaall censsuuss,, and I may exercciissee my discrreettiioonn to reinssttaattee the citizeennsshhiipp quessttiioonn on the
20200 deceennnniiaall censsuuss,, espeecciiaallllyy baseedd on DOlJ's' s requueesstt for impprroovveedd CV AP data to enfoorrccee the VRAA.. By law, the list of deceennnniiaall censsuuss quessttiioonnss is to be submmiitttteedd two yearss priorr to the decennnniiaall censsuuss - in this case, no laterr than Marcchh 31, 20188..
Th~ Depaarrttmmeenntt's's revieeww demoonnssttrraatteedd that colleeccttiioonn of citizeennsshhiipp data by the Censsuuss has beenn a longg--ssttaannddiinngg histoorriiccaall practtiiccee.. Priorr deceennnniiaall censsuuss surveeyyss of the entirree Unitteedd Stateess popuullaattiioonn conssiisstteennttllyy askedd citizeennsshhiipp quessttiioonnss up untill 19500,, and Censuuss Bureeaauu surveeyyss of samppllee popuullaattiioonnss continnuuee to ask citizeennsshhiipp quessttiioonnss to this day. In 20000,, the decennnniiaall ' censsuuss "longg formm"" surveeyy,, whicchh was distrriibbuutteedd to one in six peoppllee in the U.S..,, incluuddeedd a quessttiioonn on citizeennsshhiipp.. Folloowwiinngg the 20000 decennnniiaall censuuss,, the "longg formm"" samppllee was replaacceedd by the Ameerriiccaann Commmmuunniittyy Survveeyy ("ACCSS"")),, whicchh has incluuddeedd a citizeennsshhiipp quessttiioonn sincee 20055.. Theerreeffoorree,, the citizeennsshhiipp quessttiioonn has beenn well testeedd..
DOJJ seekss to obtaiinn CVAP data for censuuss blockkss,, blockk grouuppss,, counnttiieess,, townnss,, and otherr locattiioonnss wheerree potennttiiaall Sectioonn 2 violaattiioonnss are alleggeedd or susppeecctteedd,, and DOJJ stateess that the curreenntt data collecctteedd undeerr the ACSS are insuffffiicciieenntt in scoppee,, detaiill,, and certaaiinnttyy to meett its purppoossee undeerr the VRAA.. The Censsuuss Bureeaauu has advisseedd me that the censsuuss--bblloocckk--lelevveel l citizeennsshhiipp data requueesstteedd by DOJJ are not availlaabbllee usingg the annuuaall ACSS,, whicchh as noteedd earliieerr doess ask a citizeennsshhiipp quessttiioonn and is the preseenntt methoodd usedd to provviiddee DOJJ and the courttss withh data usedd to enfoorrccee Sectiioonn 2 of the VRAA.. The ACSS is sentt on an annuuaall basiss to a samppllee of apprrooxxiimmaatteellyy 2.6 perceenntt of the popuullaattiioonn..
To provviiddee the data requueesstteedd by DOJJ,, the Cennssuuss Bureaauu initiaallllyy analyyzzeedd threee alterrnnaattiivveess:: Optiioonn A was to conttiinnuuee the statuuss quo and use ACS respoonnsseess;; Optiioonn B was placiinngg the ACSS citizeennsshhiipp questtiioonn on the deceennnniiaall censsuuss,, whicchh goess to everyy Ameerriiccaann housseehhoolldd;; and Optiioonn C was not placciinngg a quessttiioonn on the deceennnniiaall censsuuss and insteeaadd provviiddiinngg DOJJ withh a citizeennsshhiipp analyyssiiss for the entirree popuullaattii~onn usingg federraall admiinniissttrraattiivvee recorrdd data that Censsuuss has agreeemmeennttss withh otherr agenncciieess to acceessss for statissttiiccaall purppoosseess..
Optioonn A conteemmppllaatteess rejecttiioonn of the DOJJ requueesstt and repreesseennttss the statuu;ss quo baseelliinnee.. Undeerr Optiioonn A, the 20200 deceennnniiaall censsuuss woulldd not includdee the quessttiioonn on citizeennsshhiipp that DOJJ requueesstteedd and thereeffoorree woulldd'nnoott provviiddee DOJJ withh imprroovveedd CVAAPP data.. Addiittiioonnaalllyy,., . the blockk--ggrroouupp levell CVAP data curreennttllyy obtaiinneedd throuugghh the ACSS has assocciiaatteedd marggiinnss of errorr becaauussee the ACSS is extraappoollaatteedd baseedd on samppllee surveeyyss of the popuullaattiioonn.. Provviiddiinngg moree preciissee blockk--lleevveell data wouulldd requuiirree sophhiissttiiccaatteedd statissttiiccaall moddeelliinngg,, and if Optiioonn A'i·iss selecctteedd,, the Censsuuss Burreeaauu advisseedd that it woulldd needd to deplooyy a teamm of expeerrttss to deveelloopp moddeell--bbaasseedd methhooddss that attemmpptt to betteerr facilliittaattee DOlJ's's requueesstt for moree specciiffiicc data.. But the Censsuuss Bureeaauu did not asserrtt and couldd not conffiirrmm that suchh data moddeelliinngg is posssiibbllee for censsuuss--bblloocckk--lelevveel l data withh a suffiicciieenntt degrreeee of accuurraaccyy.. Regaarrddlleessss,, DOlJ's's requueesstt is basedd at leastt in part on the fact that existtiinngg ACSS citizzeennsshhiipp data--sseettss lack specciiffiicciittyy and
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compleetteenneessss.. Any futuree modeelliinngg fromm thesee incommpplleettee dataa wouulldd onlyy commppoouunndd thaatt problemm..
Optionn A would providdee no improovveedd citizeennsshhiipp counntt,, as the exissttiinngg ACCSS sammpplliinngg woouulldd still fail to obtainn actuuaall,, compplleettee numbbeerr counnttss,, espeecciiaallllyy for certtaaiinn lowweerr poppuullaattiioonn areeaass or voting districttss,, and there is no guaraanntteeee that data coulldd be impprroovveedd usinngg smmaallll--aarreeaa modeliinngg methooddss.. Thereeffoorree,, I have concluuddeedd that Optiioonn A is not a suittaabbllee opttiioonn..
The Censuss Bureauu and many stakehhoollddeerrss expreesssseedd concceerrnn thatt Opttiioonn B, whhiicchh woouulldd adddd a citiz~enship questioonn to the decennnniiaall censuuss,, woulldd negaattiivveellyy imppaacctt the resppoonnssee rattee forr noonn-citizenss.. A signifiiccaannttllyy lowerr respoonnssee rate by nonn--cciittiizzeennss coulldd reduuccee thee acccuurraaccyy of thee decenniiaall censuss and increaassee costs for non-rreessppoonnssee follooww up ("NNRRFFUU"")) operraattiioonnss.. Howweevveerr,, neitherr the Censuuss Bureaauu nor the conceerrnneedd stakeehhoollddeerrss coulldd doccuummeenntt thaatt thee ressppoonnssee rattee would in fact declinnee materriiaallllyy.. In discuussssiinngg the quessttiioonn withh the natiioonnaall surrvveeyy ageennccyy Nielseenn,, it stated that it had addedd questtiioonnss fromm the ACSS on senssiittiivvee toppiiccss succhh as plaaccee of birth and immiggrraattiioonn statuss to certaiinn shortt surveeyy formmss withhoouutt anyy appprreecciiaabbllee deccrreeaassee in responssee rates. Furtheerr,, the formeerr direccttoorr of the Censsuuss Bureeaauu duriinngg the lastt decceennnniiaall census told me that, while he wisheedd theree weree data to answweerr the quessttiioonn,, nonnee exisstteedd to hiss knowleeddggee.. Nielseenn''ss Senioorr Vice Presiiddeenntt for Dataa Scieennccee andd the formmeerr Deeppuuttyy Diirreeccttoorr and Chief Operattiinngg Officeerr of the Censsuuss Bureeaauu undeerr Pressiiddeenntt Geoorrggee W.. Busshh alssoo confirmmeedd that, to the best of their knowwlleeddggee,, no emppiirriiccaall dataa exisstteedd on thee imppaacctt of a citizensshhiipp questioonn on responnsseess..
When analyziinngg Optionn B, the Censuuss Bureeaauu attemmpptteedd to assessss the imppaacctt thaatt reiinnssttaatteemmeenntt of a citizennsshhiipp questiioonn on the decennnniiaall censuuss wouulldd havee on resppoonnssee rateess by draawwiinngg comparriissoonnss to ACS responnsseess.. Howeevveerr,, suchh commppaarraattiivvee anallyyssiiss waass chaalllleennggiinngg,, as responssee rates generaallllyy vary betweeeenn decennnniiaall censsuusseess and otheerr cennssuuss sammppllee surrvveeyyss.. Foorr exampllee,, ACS self-reessppoonnssee rates were 3.1 perceennttaaggee poinnttss lesss thann selff--rreessppoonnssee ratteess forrththee 2010 decennniiaall censuss.. The Bureaauu attribbuutteedd this diffeerreennccee to the greaatteerr outtrreeaacchh andd follllooww-up associaatteedd with the Consttiittuuttiioonnaallyly--mmaannddataetded deceennnniiaall censsuuss.. Furrtthheerr,, thee decceennnniiaall census has differeedd signifiiccaannttllyy in naturree fromm the samppllee survveeyyss.. For exaammppllee,, thee 2000000 decennniiaall censuss surveyy contaiinneedd only eightt quessttiioonnss.. Connvveerrsseellyy,, the 200000 "loonngg forrmm"" samplee surveyy contaiinneedd over 50 questtiioonnss,, and the Censsuuss Burreeaauu estiimmaatteedd it tookk an avveerraaggee of over 30 minuteess to complleettee.. ACS surveeyyss incluuddee overr 45 queessttiioonnss on nummeerroouuss toppiiccss,, includiinngg the numbeerr of hourss workkeedd,, incommee inforrmmaattiioonn,, and houussiinngg chaarraacctteerriisstticicss..
The Censuss Bureauu determmiinneedd that, for 20133--22001166 ACSS survveeyyss,, nonnrreessppoonnsseess to thee citizennsshhiipp questioonn for non-HHiissppaanniicc whiteess ranggeedd fromm 6.0 to 6.3 perrcceenntt,, forr nonn--HHiissppaannicic blacks rangedd from 12.0 to 12.6 perceenntt,, and for Hisppaanniiccss ranggeedd fromm 11..66 to 12..33 perrcceenntt.. Howevveerr,, these rates were comppaarraabbllee to nonrreessppoonnssee ratess for otheerr queessttiioonnss on thee 2001133 anndd 2016 ACS. Censuuss Bureaauu estimmaatteess showweedd simillaarr nonrreessppoonnssee ratee rannggeess occcuurrrreedd forr questioonnss on the ACS askingg the numbbeerr timess the resppoonnddeenntt wass marrrriieedd,, 4.77 to 6.99 peerrcceenntt;; educatiioonnaall attainmmeenntt,, 5.6 to 8.5 perceenntt;; monntthhllyy gas costss,, 9.6 to 9.9 perrcceenntt;; weeeekkss woorrkkeedd in the past 12 monthhss,, 6.9 to 10.6 perceenntt;; wageess//ssaallaarryy incoommee,, 8.1 to 13.44 perrcceenntt;; anndd yeeaarrllyy properttyy insurannccee,, 23.9 to 25.6 perceenntt..
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The Censsuuss Bureeaauu also comppaarreedd the self--rreessppoonnssee rate differreenncceess betwweeeenn citizeenn and non-citizeenn housseehhoollddss'' respoonnssee ratess for the 200000 deceennnniiaall censsuuss shortt formm (whiicchh did not incluuddee a citizeennsshhiipp quessttiioonn)) and the 20000 deceennnniiaall censsuuss longg formm surveeyy (the longg formm surveeyy,, distrriibbuutteedd to onlyy one in six housseehhoollddss,, incluuddeedd a citizeennsshhiipp quessttiioonn in 20000)).. Censsuuss founndd the decliinnee in self--rreessppoonnssee ratess for non--cciittiizzeennss to be 3.3 perceenntt greatteerr than for citizeenn housseehhoollddss.. Howweevveerr,, Censsuuss was not able to isolaattee whatt perceennttaaggee of decliinnee was causseedd by the incluussiioonn of a citizeennsshhiipp quessttiioonn ratheerr than somee otherr aspeecctt of the longg formm surveeyy (it contaaiinneedd over six timeess as manyy quessttiioonnss coveerriinngg a ranggee of topiccss)).. Indeeeedd,, the Censsuuss Bureeaauu analyyssiiss showweedd that for the 20000 deceennnniiaall censsuuss theree was a signiiffiiccaanntt dropp in self respoonnssee ratess overraallll betwweeeenn the shortt and longg formm;; the maill respoonnssee rate was 66.4 perceenntt for the shortt formm and onlyy 53.9 peircceenntt for the longg formm surveeyy.. So whillee theree is wideesspprreeaadd belieeff amonngg manyy partiieess that addinngg a citizeennsshhiipp quessttiioonn couldd reduuccee respoonnssee ratess,, the Censuuss Bureeaauu''ss analyyssiiss did not provviiddee definniittiivvee,, empiirriiccaall supppoorrtt for thatt belieeff..

Optioonn C,, the use of admiinniissttrraattiivvee recorrddss ratheerr than placiinngg a citizeennsshhiipp quessttiioonn on the deceennnniiaall censsuuss,, was a potennttiiaalllyy appeeaalliinngg soluuttiioonn to the DOJJ requeesstt.. Thee use of admiinniissttrraattiivvee recorrddss is increeaassiinnggllyy part of the fabriicc and desiggnn of moddeemm censsuusseess,, and the Censuuss Bureeaauu has beenn usingg admiinniissttrraattiivvee recorrdd data to imprroovvee the accuurraaccyy and reduuccee the cost of censsuusseess sincee the earlyy 20thh centuurryy.. A Censsuuss Burreeaauu analyyssiiss matcchhiinngg admiinniissttrraattiivvee
recorrddss withh the 20110a deceennnniiaall censsuuss and ACSS respoonnsseess overr seveerraall moree recenntt yearss
showweedd that usingg admiinniissttrraattiivvee recorrddss couldd be moree accuurraattee than self--rreessppoonnsseess in the case of non--cciittiizzeennss.. Thatt Censsuuss Bureeaauu analyyssiiss showweedd that betwweeeenn 28 and 34 perceenntt of the citizeennsshhiipp self--rreessppoonnsseess for persoonnss that admiinniissttrraattiivvee recorrddss showw are non-cciittiizzeennss weree inacccuurraattee.. In otherr worrddss,, whenn non--cciittiizzeennss respoonndd to longg formm or ACSS quessttiioonnss on citizeennsshhiipp,, theyy inacccuurraatteellyy markk "citizzeenn"" abouutt 30 perceenntt of the timee.. Howweevveerr,, the Censuuss Bureeaauu is still evolvviinngg its'uussee of admiinniissttrraattiivvee recorrddss,, and the Bureeaauu doess not yet havee a compplleettee admiinniissttrraattiivvee recorrddss data set for the entirree popuullaattiioonn. . Thuss,, usingg admiinniissttrraattiivvee
recorrddss alonee to provviiddee DOJJ withh CV AP data woulldd provviiddee an incommpplleettee pictuurree.. In the 20110a
deceennnniiaall censsuuss,, the Censsuuss Bureeaauu was able to matcchh 88.66 perceenntt of the popuullaattiioonn withh whatt the Bureeaauu conssiiddeerrss crediibbllee admiinniissttrraattiivvee recorrdd data. Whillee imprreessssiivvee,, this meannss that moree than 10 percceenntt of the Ameerriiccaann popuullaattiioonn - somee 25 milliioonn votinngg age peoppllee - woulldd needd to havee theirr citizeennsshhiipp impuutteedd by the Censsuuss Bureeaauu.. Giveenn the scalee of this nummbbeerr,, it was impeerraattiivvee that anothheerr optioonn be deveellooppeedd to provviiddee a greatteerr leveell of accuurraaccyy than eitheerr self--rreessppoonnssee alonee or use of admiinniissttrraattiivvee recorrddss alonee wouulldd preseennttllyy proviiddee..

I thereeffoorree askeedd the Censsuuss Bureeaauu to deveelloopp a fourtthh alterrnnaattiivvee,, Optioonn D, whicchh woulldd' ·

combbiinnee Optiioonnss Bandd C. Unddeerr Optiioonn D, the ACSS citizeennsshhiipp quessttiioonn woulldd be askeedd on the

deceennnniiaall censsuuss,, and the Censsuuss Bureeaauu woulldd use the two yearss remaaiinniinngg untill the 202200

deceennnniiaall censsuuss to furthheerr enhaannccee its admiinniissttrraattiivvee recorrdd data sets,, protooccoollss,, and statissttiiccaall

moddeellss to provviiddee moree comppllee~~ee and accuurraattee data.. Thiss apprrooaacchh woulldd maxiimmiizzee the Censuuss

Bureeaauu''ss abiliittyy to matcchh the deceennnniiaall censsuuss respoonnsseess withh admiinniissttrraattiivvee recorrddss..

Accoorrddiinnggllyy,, at my direccttiioonn the Censsuuss Bureeaauu is workkiinngg to obtaiinn as manyy addittiioonnaall Fedeerraall

and statee admiinniissttrraattiivvee recorrddss as posssiibbllee to provviiddee moree compprreehheennssiivvee inforrmmaattiioonn for the

popuullaattiioonn..

"·

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It is my judggmmeenntt that Optiioonn D will provviiddee DOJJ withh the mostt compplleettee and accuurraattee CVAP data in respoonnssee to its requueesstt.. A"sskkininggthe citizeennsshhiipp quessttiioonn of 100 perceenntt of the popuullaattiioonn givess eachh resppoonnddeenntt the oppoorrttuunniittyy to provviiddee an answweerr.. Thiss may elimmiinnaattee the needd for the Censsuuss Burreeaauu to havee to impuuttee an answweerr for milliioonnss of peooppllee.. For the apprrooxxiimmaatteelyly 90 percceenntt of the popuullaattiioonn whoo are citizzeennss,, this quessttiioonn is no addiittiioonnaall impoossiittiioonn.. Andd for the apprrooxxiimmaatteelyly 70 percceenntt of nolni-cittiizzeennss whoo alreaaddyy answweerr this quessttiioonn accurraatteellyy on the ACSS,, the quessttiioonn is no addiittiioonnaall impoossiittiioonn sincee censsuuss respoonnsseess by law may onlyy be usedd anonnyymmoouussllyy and for statissttiiccaall purppoosseess.. Finaallllyy,, placiinngg the quessttiioonn on the deceennnniiaall censuuss and direccttiinngg the Censsuuss Burreeaauu to deterrmmiinnee the best meannss to comppaarree the deceennnniiaall censsuuss respoonnsseess withh admiinniissttrraattiivvee recorrddss will permmiitt the Censsuuss Bureeaauu to deterrmmiinnee the inacccuurraattee respoonnssee rate for citizzeennss and non--cciittiizzeennss alikee usingg the entirree poppuullaattiioonn.. Thiss will enabbllee the Censsuuss Bureeaauu to estabblliisshh,, to the best of its abiliittyy,, the accuurraattee ratioo of citizeenn to non-cciittiizzeenn respoonnsseess to impuuttee for that smallll perceennttaaggee of casess wherree it is neceessssaarryy to do so.
Conssiiddeerraattiioonn of Impaaccttss II havee careffuullllyy conssiiddeerreedd the arguummeenntt that the reinssttaatteemmeenntt of the citizeennsshhiipp quessttiioonn on the deceennnniiaall censsuuss wouulldd deprreessss respoonnssee rate.. Becaauussee a loweerr respoonnssee rate woulldd lead to increeaasseedd non--rreessppoonnssee follooww--uupp costss and less accuurraattee respoonnsseess,, this factoorr was an impoorrttaanntt conssiiddeerraattiioonn in the decissiioonn--mmaakkiningg procceessss.. I find that the needd
a for accuurraattee citizeennsshhiipp data and the limitteedd burdeenn that the reinssttaatteemmeenntt of the citizeennsshhiipp
quessttiioonn woulldd impoossee outwweeiigghh fearss abouutt a potennttiiaalllyy loweerr respoonnssee rate..
Impoorrttaannttllyy,, the Depaarrttmmeenntt's's revieeww founndd that limiitteedd empiirriiccaall evideennccee existtss abouutt whetthheerr addinngg a citizeennsshhiipp quessttiioonn wouulldd decreeaassee respoonnssee ratess mateerriiaallllyy.. Concceerrnnss abouutt decreeaasseedd respoonnssee ratess geneerraallllyy fell into the followwiinngg two categgoorriieess - distrruusstt of goveerrnpmmeenntt and increeaasseedd burddeenn.. Firstt,, stakeehhoollddeerrss,, partiiccuullaarrllyy thosee who repreesseenntteedd immmiiggrraanntt conssttiittuueenncciieess,, notedd that memmbbeerrss of theirr respeeccttiivvee commmuunniittiieess geneerraallllyy distrruusstteedd the goveerrnnmmeenntt and espeecciiaallllyy distrruusstteedd efforrttss by goveerrnnmmeenntt agenncciieess to obtaiinn inforrmmaattiioonn aboutt themm.. Stakeehhoollddeerrss fromm Califfoorrnniiaa referreenncceedd the difficcuullttyy that goveerrnnmmeenntt agenncciieess facedd obtaiinniinngg any inforrmmaattiioonn fromm immmiiggrraannttss as part of the relieeff efforrttss afterr the Califfoorrnniiaa wilddffiirreess.. Thessee goveerrnnmmeenntt agencciieess weree not seekkiinngg to ascerrttaaiinn the citizeennsshhiipp statuuss of thesee wilddffiirree victiimmss.. Otheerr stakeehhoollddeerrss referenncceedd the polittiiccaall climmaattee geneerraallllyy and fearss that Censsuuss respoonnsseess couldd be usedd for law enfoorrcceemmeenntt purppoosseess. . But no one provviiddeedd evideennccee that reinssttaattiinngg a citizeennsshhiipp quessttiioonn on the deceennnniiaall censsuuss woulldd matteerriiaalllyy decreeaassee respoonnssee ratess amonngg thosee who geneerraallllyy distrruusstteedd goveerrnnmmeenntt and goveerrnnmmeenntt inforrmmaattiioonn colleccttiioonn efforrttss,, dislikkeedd the curreenntt admiinniissttrraattiioonn,, or feareedd law enfoorrcceemmeenntt.. Rathheerr,, stakeehhoollddeerrss mereellyy identtiiffiieedd residdeennttss who madee the decissiioonn not to partiicciippaattee regarrddlleessss of whetthheerr the Censsuuss includdeess a citizeennsshhiipp quessttiioonn.. The reinssttaatteemmeenntt of a citizeennsshhiipp quessttiioonn will not decreeaassee the respoonnssee rate of resideennttss who alreaaddyy deciddeedd not to resppoonndd.. And no one provviiddeedd evideennccee that theree are residdeennttss who woulldd respoonndd accuurraatteellyy to a decennnniiaall censsuuss that did not contaaiinn a citizeennsshhiipp quessttiioonn but woulldd not respoonndd if it did (althhoouugghh manyy belieevveedd that suchh residdeennttss had to existt)).. Whillee it is posssiibbllee this belieeff is true,, theree is no inforrmmaattiioonn availlaabbllee to deterrmmiinnee the nummbbeerr of peoppllee who woulldd in fact not respoonndd due to a citizzeennsshhiipp quessttiioonn beinngg addeedd,, and no one has idennttiiffiieedd any mechhaanniissmm for makiinngg suchh a deterrmmiinnaattiioonn..
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A secoonndd concceerrnn that stakeehhoollddeerrss advaanncceedd is that recippiieennttss are geneerraallllyy less likellyy to respoonndd to a surveeyy that contaaiinneedd moree quessttiioonnss than one that contaaiinneedd feweerr.. The formmeerr Depuuttyy Direeccttoorr and Chieeff Operraattiinngg Officceerr of the Censsuuss Bureeaauu durinngg the Georrggee W. Bushh admiinniissttrraattiioonn desccrriibbeedd the deceennnniiaall censsuuss as partiiccuullaarrllyy fragiillee and stateedd that any efforrtt to .· add quessttiioonnss riskeedd loweerriinngg the respoonnssee rate,, espeecciiaallllyy a quessttiioonn abouutt citizeennsshhiipp in the curreenntt poliittiiccaall envirroonnmmeenntt.. Howweevveerr,, theree is limitteedd empiirriiccaall evideennccee to supppoorrtt this vieww.. A formmeerr Censsuuss Bureeaauu Direeccttoorr durinngg the Obammaa Admmiinniissttrraattiioonn who overssaaww the last deceennnniiaall censsuuss notedd as muchh.. He stateedd that,, evenn thouugghh he belieevveedd that the reinssttaatteemmeenntt of a citizeennsshhiipp quessttiioonn woulldd decreeaassee respoonnssee rate,, theree is limitteedd evideennccee to supppoorrtt this concclluussiioonn.. Thiss samee formmeerr direccttoorr notedd that,, in the yearss preceeddiinngg the deceennnniiaall censsuuss,, certaaiinn interreesstt grouuppss conssiisstteennttllyy attacckk the censsuuss and discoouurraaggee partiicciippaattiioonn.. Whillee the reinssttaatteemmeenntt of a citizeennsshhiipp quessttiioonn may be a data poinntt on whicchh thesee interreesstt grouuppss seizee in 20199,, past expeerriieennccee demoonnssttrraatteess that it is likellyy efforrttss to undeerrmmiinnee the deceennnniiaall censsuuss will occurr againn regarrddlleessss of whetthheerr the deceennnniiaall censsuuss incluuddeess a citizzeennsshhiipp quessttiioonn.. Therree is no evideennccee that resideennttss who are persuuaaddeedd by thesee disruuppttiivvee efforrttss are moree or less likelyy to makee theirr respeeccttiivvee decissiioonnss aboutt partiicciippaattiioonn b~ased speciiffiiccaalllyy on the reinssttaatteemmeenntt of a citizeennsshhiipp quessttiioonn.. And theree are actionnss that the Censsuuss Bureeaauu and stakeehhoollddeerr grouuppss are takinngg to mitiggaattee the impaacctt of thesee attacckkss on the deceennnniiaall censsuuss..
Addiittiioonnaall empiirriiccaall evideennccee abouutt the impaacctt of sensiittiivvee quessttiioonnss on surveeyy respoonnssee ratess camee fromm the SVP of Dataa Sciennccee at Nielsseenn.. Wheenn Nielsseenn addeedd quessttiioonnss on placee of birthh and time of arrivvaall in the Unitteedd Stateess (bothh of whicchh weree takenn fromm the ACSS)) to a shortt surveeyy,, the respoonnssee rate was not mateerriiaallllyy diffeerreenntt than it had beenn befoorree thesee two quessttiioonnss weree addeedd.. Simiillaarrllyy,, the formmeerr Depuuttyy Direeccttoorr and COOO of the Censsuuss durinngg the Georrggee W. Busshh Admmiinniissttrraattiioonn shareedd an exammppllee of a citizeennsshhiipp--lliikkee quessttiioonn that he beliieevveedd woulldd negaattiivveellyy impacctt respoonnssee ratess but did not. He citedd to the Depaarrttmmeenntt of Homeellaanndd Secuurriittyy's's 20044 requueesstt to the Censsuuss Burreeaauu to provviiddee aggrreeggaattee data on the nummbbeerr of Arabb Ameerriiccaannss by zip codee in certaaiinn areass of the counnttrryy.. The Censsuuss Bureeaauu compplliieedd,, and Censsuuss empllooyyeeeess,, incluuddiinngg the then--DDeeppuuttyy Direeccttoorr,, beliieevveedd that the resullttiinngg polittiiccaall firestorm woulldd deprreessss respoonnssee ratess for furthheerr Censsuuss Bureaauu surveeyyss in the impaacctteedd commmuunniittiieess.. But the respoonnssee rate did not channggee mateerriiaallllyy..
Twoo otherr themmeess emerrggeedd fromm stakeehhoollddeerr callss that meriitt discuussssiioonn.. Firstt,, seveerraall stakeehhoollddeerrss whoo opposseedd reinssttaatteemmeenntt of the citizzeennsshhiipp quessttiioonn did not apprreecciiaattee that the questtiioonn had beenn askeedd in somee formm or anothheerr for nearllyy 200 yearss.. Secoonndd,, otherr stakeehhoollddeerrss who oppoosseedd reinssttaatteemmeenntt did so basedd on the assuummppttiioonn that the data on citizeennsshhiipp that the Censsuuss Bureeaauu colleeccttss throuugghh the ACSS are accuurraattee,, thereebbyy obviiaattiinngg the needd to ask the quessttiioonn on the deceennnniiaall censsuuss.. But as discuusssseedd abovvee,, the Censsuuss Bureeaauu estimmaatteess that betwweeeenn 28 and 34 perceenntt of citizeennsshhiipp self--rreessppoonnsseess on the ACSS for persoonnss that adminniissttrraattiivvee recorrddss showw are non--cciittiizzeennss weree inacccuurraattee.. Becauussee thesee stakeehhoollddeerr concceerrnnss weree baseedd on incorrrreecctt premmiisseess,, they are not sufffiicciieenntt to channggee my decissiioonn..
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Finallyy,, I have consideerreedd whetheerr reinstaattiinngg the citizennsshhiipp questioonn on the 2020 Censuss will

lead to any significcaanntt monetaarryy costs, progrraammmmaattiicc or otherwissee.. The Censuss Bureauu staff

have advised that the costs of prepariinngg and addingg the questioonn would be minimaall due in large

part to the fact that the citizennsshhiipp questioonn is alreadyy includeedd on the ACS, and thus the

citizennsshhiipp questioonn has alreadyy underggoonnee the cognitiivvee researcchh and questioonnnnaaiirree testingg

requiredd for new questioonnss.. Additioonnaallllyy,, changeess to the Interneett Self-Reessppoonnssee instrummeenntt,,

revisinngg the Censuss Questioonnnnaaiirree Assistaannccee,, and redesiggnniinngg of the printedd questioonnnnaaiirree can

be easily implemmeenntteedd for questioonnss that are finalizeedd prior to the submissssiioonn of the list of

questioonnss to Congreessss..

.

The Censuss Bureauu also consideerreedd whetheerr non-ressppoonnssee followw--uupp increasseess resultingg from inclusiioonn of the citizenshhiipp questioonn would lead to increasseedd costs. As noted above,, this estimattee was difficuulltt to assess given the Censuss Bureauu and Departtmmeenntt''ss iinnaabbiilliittyy to determmiinnee what impactt there will be on decennniiaall censuss surveyy responnsseess.. The Bureauu provideedd a rough estimattee that postulaatteedd that up to 630,00000 additioonnaall househhoollddss may requiree NRFUU operatiioonnss if a citizensshhiipp questioonn is added to the 2020 decennniiaall censuss.. Howevveerr,, even assumiinngg that estimatee is correctt,, this additioonnaall Y½2 percenntt increassee in NRFUU operatiioonnss falls well within the marginn of error that the Departtmmeenntt,, with the supporrtt of the Censuss Bureauu,, provideedd to Congreessss in the revisedd Lifecyccllee Cost Estimaattee ("LCE"")) this past fall. That LCE assumeedd that NRFUU operatiioonnss might increassee by 3 percenntt due to numeroouuss factorss,, includiinngg a greaterr increassee in citizenn mistrusstt of governnmmeenntt,, difficuullttiieess in accessiinngg the Interneett to responndd,, and other factorss..

Inclussiioonn of a citizennsshhiipp questioonn on this countryy''ss decennniiaall censuss is not new-- the decisioonn to collectt citizennsshhiipp informmaattiioonn from Americcaannss throughh the decennniiaall censuss was first made centuriieess ago. The decisioonn to includee a citizennsshhiipp questioonn on a nationaall census is also not uncommmmoonn.. The Unitedd Nationnss recommmeennddss that its membeerr countriieess ask census questioonnss identifyyiinngg both an individduuaall''ss countryy of birth and the country of citizennsshhiipp.. Principals. _and Recommendations/ofror Population and Housing Censuses (Revision 3), UNIITTEEDD NATTIIOONNSS 121 (2017)).. Additioonnaallllyy,, for countriieess in which the populaattiioonn may includee a large portionn of naturalliizzeedd citizennss,, the Unitedd Nationnss notes that, "it may be importtaanntt to collectt informmaattiioonn on the methodd of acquisiittiioonn of citizenshhiipp.."" Id. at 123. And it is importtaanntt to note that other major democcrraacciieess inquiree about citizenshhiipp on their censuss,, includiinngg Austraalliiaa,, Canadaa,, Francee,, Germaannyy,, Indoneessiiaa,, Irelandd,, Mexicoo,, SSppaaiinn,, and the Unitedd Kingdoomm,, to name a few.

The Departtmmeenntt of Commmeerrccee is not able to determmiinnee definitiivveellyy how inclusiioonn of a citizennsshhiipp questioonn on the decennniiaall census will impactt responnssiivveenneessss.. Howevveerr,, even iftlhiere is some impacctt on responnsseess,, the value of more complettee and accuratee data derivedd from surveyyiinngg the entire populaattiioonn outweiigghhss such concerrnnss.. Complleettiinngg and returniinngg decennniiaall censuss questioonnnnaaiirreess is requirreedd by Federaall law, those responnsseess are protectteedd by law, and inclusiioonn of a citizennsshhiipp questioonn on the 2020 decennniiaall censuss will providdee more compleettee informmaattiioonn for those who responndd.. The citizennsshhiipp data providedd to DOJ will be more accurattee with the questioonn than withouutt it, whichh is of greaterr importaannccee than any adversee effect that may result from peoplee violattiinngg their legal duty to responndd..

7

Case 1:18-cv-02711-DLF Document 8-4 Filed 01/18/19 Page 9 of 178 To concluuddee,, after a thorouugghh revieww of the legall,, proggrraamm,, and poliiccyy connssiiddeerraattiioonnss,, as weellll as numeroouuss discusssiioonnss with the Censuuss Bureeaauu leadeerrsshhiipp and inteerreesstteedd stakkeehhoollddeerrss,, I havvee determiinneedd that reinstaatteemmeenntt of a citizeennsshhiipp quessttiioonn on the 202200 decceennnniiaall cennssuuss is necceessssaarryy to providee complleettee and accuraattee data in respoonnssee to the DOlJ requueesstt.. To minniimmiizzee anyy immppaacctt on decennniiaall censuss responnssee rates,, I am direccttiinngg the Censsuuss Burreeaauu to placcee thee citiizzeennsshhiipp questionn last on the decennnniiaall censuuss form.. Pleasee make my decisioonn knowwnn to Censsuuss Bureeaauu persoonnnneell and Memmbbeerrss of Coonnggrreessss priioorr to March 31, 2018. I look forwarrdd to continnuuiinngg to workk withh the Cennssuuss Burreeaauu as wee strriivvee forr a compleettee and accuraattee 2020 decennnniiaall censuuss.. CC: Ron Jlaarrmmiinn,, perforrmmiinngg the nonexxcclluussiivvee funccttiioonnss and dutiieess of the Diirreeccttoorr of thee
Censuss Bureauu Enriquuee Lamass,, perforrmmiinngg the nonexxcclluussiivvee funccttiioonnss and dutiieess of thee Deeppuuttyy Diirreeccttoorr of the Censuuss Bureauu
8

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Exhibit 2

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Questions Planned for the 2020 Census and American Community Survey
Federal Legislative and Program Uses
Issued March 2018
U.S. Department of Commerce
Economics and Statistics Administration
U.S. CENSUS BUREAU
census.gov

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Contents

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1

Protecting the Information Collected by These Questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2

Questions Planned for the 2020 Census . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

3

Age . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

5

Citizenship . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

Hispanic Origin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

9

Race. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

Relationship . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

Sex . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

Tenure (Owner/Renter). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

Operational Questions for use in the 2020 Census.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

Questions Planned for the American Community Survey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 Acreage and Agricultural Sales . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 Age . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 Ancestry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 Commuting (Journey to Work) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 Computer and Internet Use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 Disability. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 Fertility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 Grandparent Caregivers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 Health Insurance Coverage and Health Insurance Premiums and Subsidies . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 Hispanic Origin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 Home Heating Fuel. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 Home Value and Rent . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 Income . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 Industry, Occupation, and Class of Worker. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 Labor Force Status. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51 Language Spoken at Home . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 Marital Status and Marital History . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 Migration (Previous Residence)/Residence 1 Year Ago. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 Place of Birth, Citizenship, and Year of Entry. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 Plumbing Facilities, Kitchen Facilities, and Telephone Service . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61 Race. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63 Relationship . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 School Enrollment, Educational Attainment, and Undergraduate Field of Degree . . . . . . . . . . . . . . . . . . . . . 67 Selected Monthly Owner Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 Sex . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 Supplemental Nutrition Assistance Program (SNAP)/Food Stamps . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 Tenure (Owner/Renter). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75 Units in Structure, Rooms, and Bedrooms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77 Vehicles Available . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79 Veteran Status, Period of Military Service, and Department of Veterans Affairs (VA) Service-Connected Disability Rating . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81 Work Status Last Year . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83 Year Built and Year Moved In . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85 Operational Questions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87

Appendix A: Year the Planned Questions Were First Asked in the Decennial Census Program . . . . . . . . . . A1

U.S. Census Bureau

Questions Planned for the 2020 Census and American Community Survey iii

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Introduction

BACKGROUND
Since 1790, a national census of the U.S. population has been conducted every 10 years, as required by the U.S. Constitution. Additional information beyond the population count has been collected with each census in response to the challenges facing the nation and a national desire to understand ourselves.
For much of the 20th century, most addresses received a “short” form, while a portion of addresses received a more detailed “long” form. The Census 2000 short form was designed to collect basic demographic and housing information (i.e., age, sex, race, Hispanic origin, relationship, and tenure) to be used for congressional apportionment and to provide data to states for intrastate redistricting. The long form, sent to approximately 1 in 6 households, collected social, housing, and economic information (e.g., educational attainment, disability status, employment status, income, and housing costs) that was used to plan and determine funding for a wide array of federal, state, local, and tribal programs.
Since 2005, in order to provide communities, businesses, and the public with the detailed longform information more frequently, these data have been collected monthly (and released annually) through the American Community Survey (ACS).1 This innovation enabled the 2010 Census to be a “short-form-only” census. Decoupling the collection of short- and long-form data allowed the U.S. Census Bureau to focus decennial census efforts on the constitutional requirements to produce a count of the resident population, while employing technology in both collections to improve efficiencies, improve accuracy, and reduce costs. The result has been the dissemination of more current and detailed information than has ever been available.
The 2020 Decennial Census Program, comprised of the 2020 Census and the ACS, will provide an official count through a "short-form-only" census (i.e., age, sex, race, Hispanic origin, relationship, tenure, and citizenship), as well as a portrait of communities counted across the nation through data collected by the ACS. This program is the only data-gathering effort that collects information from enough people to

produce comparable data for every geographic area recognized by the Census Bureau.
SUBMISSION OF QUESTIONS PLANNED FOR THE 2020 DECENNIAL CENSUS PROGRAM
The Census Act requires that the questions to be included in the next census be submitted to Congress no later than 2 years before the census date. The contents of this handbook describe the questions that will be asked on the 2020 Census and the ACS.
ABOUT THE QUESTIONS PLANNED FOR THE 2020 DECENNIAL CENSUS PROGRAM
Throughout each decade, regular content reviews are conducted to ensure that the information collected through the decennial census program is required by federal programs.2
To prepare for the 2020 Census, the Office of Management and Budget and the Census Bureau embarked on a comprehensive review including chartering the Interagency Council on Statistical Policy (ICSP) Subcommittee on the ACS and conducting the 2014 ACS Content Review. This effort was designed to examine and confirm the value of each question on the ACS, and to confirm and update the statutory and regulatory authority for the questions with federal agencies. In 2016, the Census Bureau asked federal agencies to provide any updates to this documentation.
The resulting information about federal uses is presented throughout the descriptions of the questions on the following pages. These descriptions are designed to give the reader a clear understanding of 1) the relationship between questions asked of respondents and the summarized data that are released in published tables, 2) how federal agencies use the resulting data, and 3) the benefits of the data at the community level.

1 The ACS also collects short-form data on its questionnaire. However, the ACS asks for basic demographic and housing information from a sample of households, while the decennial census asks for basic demographic and housing information from all households.

2 Selected statutory uses of each subject are published in the "Subjects Planned for the 2020 Census and American Community Survey," available at <www.census.gov/library/publications/2017/dec /planned-subjects-2020-acs.html>.

U.S. Census Bureau

Questions Planned for the 2020 Census and American Community Survey 1

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Protecting the Information Collected by These Questions

The Census Bureau has an obligation to produce accurate, relevant statistics about the nation’s economy and people, but we recognize that the information collected by these questions is often private. We depend on cooperation and trust, and promise to protect the confidentiality of this information.
Federal law protects this information; Title 13 of the U.S. Code protects the confidentiality of all collected information. Violating this law is a crime with severe penalties. Please visit <www.census.gov/about /policies/privacy/data_protection/federal_law.html> for details.
OUR PRIVACY PRINCIPLES
We recognize the value of respondent trust, and we believe that when a person answers the 2020 Census or the ACS we must serve as caretakers of the information. The Census Bureau’s Privacy Principles remind us of this promise and help ensure the protection of respondent information throughout all of our activities.
The Privacy Principles are our guidelines. They help us as we determine content to consider respondents’ rights and concerns. Every principle embodies a promise to the respondent.
Necessity: Do we need to collect information on this question?
Every time we prepare to ask a question, we determine whether the information is truly necessary. All of the information we collect is used for federal programs.
• We promise to collect only information necessary for each survey and census.
• We promise that we will use the information only to produce timely, relevant statistics about the population and the economy of the United States.
Openness: Do respondents know why we are collecting this information?
We collect information only for statistical purposes, and it is never used to identify individuals. Before participating, respondents have the right to know why we are conducting the survey or census, why we are asking specific questions, and the purposes for which the information will be used.

• We promise to inform respondents about the purpose and uses for every survey or census we conduct before respondents provide answers.
Respectful treatment of respondents: Are our efforts reasonable and do we treat people with respect?
• We promise to minimize the effort and time it takes for respondents to participate in the data collection by efficient designs.
• We promise to use only legal, ethical, and professionally accepted practices in collecting data.
• We promise to ensure any collection of sensitive information from children and other sensitive populations does not violate federal protections for research participants and is done only when it benefits the public good.
Confidentiality: How do we protect this information?
In addition to removing personally identifiable information (i.e., names, telephone numbers, and addresses) from our data files, we use various approaches to protect personal information—including computer technologies, statistical methodologies, and security procedures.
Our security measures ensure that only a restricted number of authorized people have access to private information and that access is only granted to conduct our work and for no other purposes. Every person who works with census confidential information collected by the Census Bureau is sworn for life to uphold the law.
Violating the confidentiality of a respondent is a federal crime with serious penalties, including a federal prison sentence of up to 5 years, a fine of up to $250,000, or both.
• We promise that every person with access to respondent information is sworn for life to protect respondent confidentiality.
• We promise that we will use every technology, statistical methodology, and physical security procedure at our disposal to protect respondent information.

2 Questions Planned for the 2020 Census and American Community Survey

U.S. Census Bureau

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Questions Planned for the 2020 Census

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Age asked since 1790.

What is this person's age and what is this person's date of birth? For babies less than 1 year old, do not write the age in months. Write Oas the age.

Age on April 1, 2020

Print numbers in boxes .

Month

Day

Year of birth

.___ __.yIears

D

ANSWERS TO THE AGE AND DATE OF BIRTH QUESTION PROVIDE THE DATA THAT HELP US UNDERSTAND THE SIZE OF DIFFERENT AGE GROUPS AND HOW OTHER CHARACTERISTICS MAY VARY BY AGE.
Age data are used in planning and funding government programs that provide funds or services for specific age groups, such as children, workingage adults, women of childbearing age, or the older population. These statistics are also used to enforce laws, regulations, and policies against age discrimination in government programs and in society.
AGE DATA HELP COMMUNITIES:
Provide Assistance to Older Americans
Knowing how many people in a community are aged 60 and older helps local officials provide programs and services that enable older adults to remain

living safely in their homes and communities (Older Americans Act). Age data are also used in programs that provide services and assistance to seniors, such as financial assistance with utilities (Low Income Home Energy Assistance Program).
Provide Assistance to Children and Families
Knowing the numbers and ages of children in families can help communities enroll eligible families in programs designed to assist them. For example, age data are used in targeted efforts to enroll eligible people in Medicaid and the Children’s Health Insurance Program.
Educate Children and Adults
Knowing how many children and adults depend on services through schools helps school districts make long-term building, staffing, and funding decisions.
Ensure Equal Opportunity
Knowing the age distribution of a community’s population helps government and communities enforce laws, regulations, and policies against discrimination based on age.

U.S. Census Bureau

Questions Planned for the 2020 Census and American Community Survey 5

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Citizenship asked since 1820.1

Is this person a citizen of the United States?
D Yes, born in the United States D Yes, born in Puerto Rico, Guam, the U.S. Virgin Islands, or
Northern Marianas
D Yes, born abroad of U.S. citizen parent or parents D Yes, U.S. citizen by naturalization - Print year of naturalization¥
D No, not a U.S. citizen

A QUESTION ABOUT A PERSON'S CITIZENSHIP IS USED TO CREATE STATISTICS ABOUT CITIZEN AND NONCITIZEN POPULATIONS.
These statistics are essential for enforcing the Voting Rights Act and its protections against voting discrimination.
1 Citizenship asked 1820, 1830, 1870, and 1890 to present.

CITIZENSHIP DATA HELP COMMUNITIES:
Enforce Voting Rights Law
Knowing how many people reside in the community and how many of those people are citizens, in combination with other information, provides the statistical information that helps the government enforce Section 2 of the Voting Rights Act and its protections against discrimination in voting.
Understand Changes
Knowing how many citizens and noncitizens live in the United States, in combination with other information, is of interest to researchers, advocacy groups, and policymakers.

U.S. Census Bureau

Questions Planned for the 2020 Census and American Community Survey 7

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8 Questions Planned for the 2020 Census and American Community Survey

U.S. Census Bureau

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Hispanic Origin asked since 1970.
Is this person of Hispanic, Latino, or Spanish origin?
D No , not of Hispanic , Latino , or Spanish origin D Yes , Mexican , Mexican Am., Chicano D Yes, Puerto Rican D Yes , Cuban D Yes , another Hispanic, Latino, or Spanish origin - Print, for
example , Salvadoran , Dominican, Colombian , Guatemalan , Spaniard, Ecuadorian , etc. 7

A QUESTION ABOUT WHETHER A PERSON IS OF HISPANIC, LATINO, OR SPANISH ORIGIN IS USED TO CREATE STATISTICS ABOUT THIS ETHNIC GROUP.
These data are required for federal and state programs and are critical factors in the basic research behind numerous policies, particularly for civil rights. Hispanic origin data are used in planning and funding government programs that provide funds or services for specific groups. These data are also used to evaluate government programs and policies to ensure they fairly and equitably serve the needs of the Hispanic population and to monitor compliance with antidiscrimination laws, regulations, and policies. States also use these data to meet legislative redistricting requirements.
Though many respondents expect to see a Hispanic, Latino, or Spanish category on the race question, this question is asked separately because people of Hispanic origin may be of any race(s) in accordance with the 1997 Office of Management and Budget standards on race and ethnicity.

HISPANIC ORIGIN DATA HELP COMMUNITIES:
Ensure Equal Opportunity
We ask about the Hispanic or Latino origin of community members to help governments and communities enforce antidiscrimination laws, regulations, and policies. For example, data on the Hispanic population are used to:
• Establish and evaluate the guidelines for federal affirmative action plans under the Federal Equal Opportunity Recruitment Program.
• Monitor compliance with the Voting Rights Act.
• Monitor and enforce equal employment opportunities under the Civil Rights Act of 1964.
• Identify segments of the population who may not be getting needed medical services under the Public Health Service Act.
Understand Changes
Researchers, advocacy groups, and policymakers are interested in knowing if the distribution of the Hispanic and non-Hispanic population changes by age, sex, relationship, and housing tenure.

U.S. Census Bureau

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Race asked since 1790.

What is this person's race?
Mark 1K]one or more boxes AND print origins.
D White - Print, for example, German, Irish, English, Italian,
Lebanese, Egyptian, etc.7

D Black or African Am. - Print, for example, African American ,
Jamaican , Haitian, Nigerian, Ethiopian, Somali, etc. 7

D American Indian or Alaska Native - Print name of enrolled or
principal tribe(s), for example, Navajo Nation, Blackfeet Tribe,
Mayan, Aztec, Native Village of Barrow lnupiat Traditional Government, Nome Eskimo Community, etc. 7

□ Chinese

□ Vietnamese

□ Filipino

□ Korean

□ □ Asian Indian

Japanese

□ Other Asian Print, for example,

Pakistani, Cambodian,

Hmong, etc. 7

□ Native Hawaiian □ Samoan □ Chamorro □ Other Pacific Islander -
Print, for example, Tongan, Fijian, Marsha/Iese, etc. 7

D Some other race - Print race or origin. 7

A QUESTION ABOUT A PERSON’S RACE IS USED TO CREATE STATISTICS ABOUT RACE AND TO PRESENT OTHER STATISTICS BY RACE GROUPS.
These data are required for federal, state, and tribal programs and are critical factors in the basic research behind numerous policies, particularly for civil rights. Race data are used in planning and funding government programs that provide funds or services for specific groups. These data are also

used to evaluate government programs and policies to ensure they fairly and equitably serve the needs of all racial groups and to monitor compliance with antidiscrimination laws, regulations, and policies. States also use these data to meet legislative redistricting requirements.
The U.S. Census Bureau collects race data in accordance with the 1997 Office of Management and Budget standards on race and ethnicity. The categories on race are based on self-identification and generally reflect a social definition of race. The categories are not an attempt to define race biologically, anthropologically, or genetically.

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Race asked since 1790—Con.

RACE DATA HELP COMMUNITIES:
Ensure Equal Opportunity
Knowing the races of community members helps government and communities enforce antidiscrimination laws, regulations, and policies. For example, race data are used in the following ways:
• Establish and evaluate the guidelines for federal affirmative action plans under the Federal Equal Opportunity Recruitment Program.
• Monitor compliance with the Voting Rights Act.
• Monitor and enforce equal employment opportunities under the Civil Rights Act of 1964.
• Identify segments of the population who may not be getting needed medical services under the Public Health Service Act.

Understand Changes
Researchers, advocacy groups, and policymakers are interested in knowing if the distribution of the different racial groups changes by age, sex, relationship, and housing tenure.
Administer Programs for Specific Groups
Knowing how many people are eligible to participate in certain programs helps communities, including tribal governments, ensure that programs are operating as intended. For example, the Indian Housing Block Grant program, Indian Community Development Block Grant program, and Indian Health Service all depend on accurate statistics of American Indians and Alaska Natives. Data for the American Indian and Alaska Native population come from the question about a person’s race.

12 Questions Planned for the 2020 Census and American Community Survey

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Relationship asked since 1880.

How is this person related to Person 1? Mark 1K]ONE box.

□ □ Opposite-sex husband/wife/spouse

Father or mother

□ Opposite-sex unmarried partner

□ Grandchild

□ Same-sex husband/wife/spouse

□ Parent-in-law

□ Same-sex unmarried partner

□ Son-in-law or daughter-in-law

□ Biological son or daughter

□ Other relative

□ Adopted son or daughter

□ Roommate or housemate

□ Stepson or stepdaughter

□ Foster child

□ Brother or sister

□ Other nonrelative

A QUESTION ABOUT THE RELATIONSHIP OF EACH PERSON IN A HOUSEHOLD TO ONE CENTRAL PERSON IS USED TO CREATE ESTIMATES ABOUT FAMILIES, HOUSEHOLDS, AND OTHER GROUPS, AND TO PRESENT OTHER DATA AT A HOUSEHOLD LEVEL.
Relationship data are used in planning and funding government programs that provide funds or services for families, people living or raising children alone, grandparents living with grandchildren, or other households that qualify for additional assistance.

RELATIONSHIP DATA HELP COMMUNITIES:
Provide Adequate Housing
Knowing about the different types of households in a community (single people, couples, families, roommates, etc.) helps communities understand whether available housing meets the needs of residents.
When housing is not sufficient or not affordable, relationship data can help communities enroll eligible households in programs designed to assist them, and can help communities qualify for grants from the Community Development Block Grant, HOME Investment Partnership Program, Emergency Solutions Grant, Housing Opportunities for Persons With AIDS, and other programs.
Provide Assistance to Families
Knowing more about families, such as the ages of children, can help communities enroll eligible families in programs designed to assist them, such as Head Start and the Children’s Health Insurance Program, and can help communities qualify for grants to fund these programs. Relationship data are also used to ensure that programs like Temporary Assistance for Needy Families are making a difference for families.

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Relationship asked since 1880—Con.

Understand Changing Households
Information about living arrangements and how they are changing, including whether older residents are staying in their homes as they age, whether young people are living with parents or moving in with roommates, and which kinds of households include

young children, can help communities plan future programs and services for residents. For example, the Social Security Administration estimates future program needs based on the current relationships of working people.

14 Questions Planned for the 2020 Census and American Community Survey

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Sex asked since 1790.

What is this person's sex? Mark [K] ONE box.

D D Male

Female

A QUESTION ABOUT THE SEX OF EACH PERSON IS USED TO CREATE STATISTICS ABOUT MALES AND FEMALES AND TO PRESENT OTHER DATA BY SEX.
Data disaggregated by sex are used in planning and funding government programs and in evaluating other government programs and policies to ensure they fairly and equitably serve the needs of males and females. These statistics are also used to enforce laws, regulations, and policies against discrimination in government programs and in society.
DATA DISAGGREGATED BY SEX HELP COMMUNITIES:
Provide Resources for Education
Data disaggregated by sex are used to allocate funds to institutions of higher learning that increase participation, particularly of minority women, in scientific and engineering programs under the Higher Education Act.

Ensure Equal Opportunity
Data disaggregated by sex are used to evaluate employment practices under the Civil Rights Act of 1964. The Equal Employment Opportunity Commission, using sex-disaggregated data, establishes and evaluates guidelines dealing with equal employment opportunity. Data disaggregated by sex are used to evaluate housing policies and practices under the Civil Rights Act.
Understand Changes
State and local planners analyze social and economic characteristics of males and females to predict future needs for housing, education, childcare, health care, transportation, and employment.

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Tenure (Owner/Renter) asked since 1890.

3. Is this house, apartment, or mobile home — Mark I J K ONE box.
□ Owned by you or someone in this household with a mortgage or loan? Include home equity loans.
□ Owned by you or someone in this household free and clear (without a mortgage or loan)?
□ Rented? □ Occupied without payment of rent?

A QUESTION ABOUT WHETHER A HOME IS OWNED OR RENTED IS USED TO CREATE DATA ABOUT TENURE, RENTERS, AND HOMEOWNERSHIP.
Tenure is the most basic characteristic to assess housing inventory. Tenure data are used in government programs that analyze whether adequate housing is available to residents. Tenure data are also used to provide and fund housing assistance programs. These statistics are also used to enforce laws, regulations, and policies against discrimination in private-market housing, government programs, and in society.
TENURE DATA HELP COMMUNITIES:
Provide Adequate Housing
Knowing the rates of home rental and ownership helps communities understand whether available housing meets the needs of residents.
When housing is not sufficient, data about owners and renters can help communities enroll eligible households in programs designed to assist them.

Plan Community Development
Knowing how the balance of rented homes, mortgaged homes, and homes owned free and clear changes over time can help communities understand changes in local housing markets; identify opportunities to improve tax, assistance, and zoning policies; and reduce tax revenue losses from vacant or abandoned properties.
Ensure Equal Opportunity
Knowing the characteristics of people who rent and people who own homes in the community, such as age, sex, race, and Hispanic origin, helps government and communities enforce laws, such as the 1968 Fair Housing Act, designed to eliminate discrimination in housing.
Understand Changing Households
Knowing whether older residents are staying in homes as they age or moving into rented homes, and whether young people are staying with parents, renting with roommates, or buying homes, can help governments and communities distribute funds appropriately between homeownership and rental housing programs and services for residents.

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Operational Questions for use in the 2020 Census.

How many people were living or staying in this house, apartment, or mobile home on April 1, 2020?
W Number of people =
2. Were there any additional people staying here on April 1, 2020
that you did not include in Question 1? Mark K I J all that apply.
□ Children, related or unrelated, such as newborn babies, grandchildren, or foster children
□ Relatives, such as adult children, cousins, or in-laws □ Nonrelatives, such as roommates or live-in babysitters □ People staying here temporarily □ No additional people 3.
4. What is your telephone number?
We will only contact you if needed for official Census Bureau business. Telephone Number
I– _I_I – ..____I__,

Please provide information for each person living here. If there is someone living here who pays the rent or owns this residence, start by listing him or her as Person 1. If the owner or the person who pays the rent does not live here, start by listing any adult living here as Person 1.

What is Person 1's name? Print name below.

First Name

Ml

□
Last Name(s)

Does this person usually live or stay somewhere else? Mark 1K]a// that apply .
0 No

□ Yes, for college □ Yes, for a military assignment □ Yes, for a job or business □ Yes, in a nursing home

□ Yes, with a parent or other relative
□ Yes, at a seasonal or second residence
□ Yes, in a jail or prison □ Yes, for another reason

Some operational questions will appear on the 2020 Census that will not result in published counts. These questions are asked to better administer the data collection process and to ensure greater accuracy of the data collected. Contact information is not part of published estimates and is carefully protected, as mandated by federal law, to respect the personal information of respondents.

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Questions Planned for the American Community Survey

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Acreage aasnkedd since 1960. Agricultural Sales asked since 1960.

4 How many acres is this house or mobile home on?
□ Less than 1 acre ➔ SKIP to question 6a □ 1 to 9.9 acres □ 10 or more acres

5 IN THE PAST 12 MONTHS, what were the actual sales of all agricultural products from this property?
□ None □ $1 to $999 □ $1,000 to $2,499 □ $2,500 to $4,999 □ $5,000 to $9,999 □ $10,000 or more

QUESTIONS ABOUT THE ACREAGE ASSOCIATED WITH HOUSES, MOBILE HOMES, AND AGRICULTURAL SALES ARE USED TO CREATE DATA ABOUT AGRICULTURAL PROPERTIES AND TO BETTER UNDERSTAND HOME VALUE STATISTICS.
These data are used in planning government programs designed to benefit the farm population and identifying or excluding agricultural areas for many other programs.
ACREAGE AND AGRICULTURAL SALES DATA HELP COMMUNITIES:
Provide Equitable Housing Assistance
Knowing which homes might qualify for farm subsidies and which homes qualify for housing subsidies is important to ensure that funds are fairly allocated. For example, the historical definition of Fair Market Rents, used to allocate housing assistance, has always excluded units on acreage of more than 10 acres to

eliminate those units that might benefit from farm subsidies and therefore have lower-than-market rents. Understanding which kinds of properties are eligible for certain programs helps communities inform eligible residents and determine whether the community is eligible for funds based on its farm population.
Support Agricultural Programs
Knowing which areas of a community are agricultural helps communities ensure eligible institutions receive funding for cooperative agricultural extension work and agricultural research. This funding is distributed to eligible institutions based on a legislatively determined formula that uses these data.
Plan Community Development
Knowing the size and agricultural nature of areas of each community can help communities understand changes in local housing markets; identify opportunities to improve tax, assistance, and zoning policies; and reduce tax revenue losses from vacant or abandoned properties.

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Age asked since 1790.

What is Person 1 'sage and what is Person 1 's date of birth?
For babies less than 1 year old, do not write the age in
months. Write Oas the age .

Age (in years)
CJ

Print numbers in boxes.

Month

Day

Year of birth

□□ I~

AGE AND DATE OF BIRTH QUESTIONS ARE USED TO UNDERSTAND THE SIZE AND CHARACTERISTICS OF DIFFERENT AGE GROUPS AND TO PRESENT OTHER DATA BY AGE.
Age data are used in planning and funding government programs that provide funds or services for specific age groups, such as children, workingage adults, women of childbearing age, or the older population. These statistics are also used to enforce laws, regulations, and policies against age discrimination in government programs and in society.
AGE DATA HELP COMMUNITIES:
Provide Assistance to Older Americans
Knowing how many people in a community are aged 60 and older helps local officials provide programs and services that enable older adults to remain living safely in their homes and communities (Older Americans Act). Age data are also used in programs that provide services and assistance to seniors, such as financial assistance with utilities (Low Income Home Energy Assistance Program).

Provide Assistance to Children and Families
Knowing the numbers and ages of children in families in combination with other information, such as household income, health insurance status, and poverty status, can help communities enroll eligible families in programs designed to assist them. For example, age data are used in targeted efforts to enroll eligible people in Medicaid and the Children’s Health Insurance Program.
Educate Children and Adults
Knowing how many children and adults depend on services through schools helps school districts make long-term building, staffing, and funding decisions. Age in combination with other information, such as disability status, language spoken at home, and poverty status, assists schools in understanding the needs of their students and qualifying for grants that help fund programs for those students (Elementary and Secondary Education Act of 1965).
Ensure Equal Opportunity
Knowing the ages of people in the community in combination with information about housing, employment, and education, helps government and communities enforce laws, regulations, and policies against discrimination based on age. For example, age information is used to analyze the employment status of workers by age (Age Discrimination in Employment Act).

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Ancestry asked since 1980.

13 What is this person’s ancestry or ethnic origin?
Mark (X) ONE box.

(For example: Italian, Jamaican, African Am., Cambodian, Cape Verdean, Norwegian, Dominican, French Canadian, Haitian, Korean, Lebanese, Polish, Nigerian, Mexican, Taiwanese, Ukrainian, and so on.)

A QUESTION ABOUT A PERSON’S ANCESTRY OR ETHNIC ORIGIN IS USED TO CREATE STATISTICS ABOUT VARIOUS ANCESTRY GROUPS.
Ancestry data are used in planning and evaluating government programs and policies to ensure they fairly and equitably serve the needs of all groups. These statistics are also used to enforce laws, regulations, and policies against discrimination in society.
ANCESTRY DATA HELP COMMUNITIES:
Ensure Equal Opportunity
Knowing the ethnic groups in a community in combination with information about housing, voting, language, employment, and education, helps government and communities enforce laws, regulations, and policies against discrimination

based on national origin. For example, ancestry data are used to enforce nondiscrimination in education (including monitoring desegregation); to enforce nondiscrimination in employment by federal agencies, private employers, employment agencies, and labor organizations; and to enforce laws, regulations, and policies against discrimination in federal financial assistance (Civil Rights Act of 1964).
Understand Changes
Knowing whether people from different backgrounds have the same opportunities in education, employment, voting, homeownership, and many other areas is of interest to researchers, advocacy groups, and policymakers. For example, ancestry data are used with age and language data to address language and cultural diversity needs in health care plans for the older population.

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Commuting (Journey to Work) asked since 1960.

31 At what location did this person work LAST WEEK? If this person worked at more than one
location, print where he or she worked most last week. a. Address (Number and street name)
If the exact address is not known, give a description of the location such as the building name or the nearest street or intersection. b. Name of city, town, or post office
c. Is the work location inside the limits of that city or town?
□ Yes □ No, outside the city/town limits
d. Name of county
e. Name of U.S. state or foreign country
f. ZIP Code

How did this person usually get to work LAST WEEK?Mark ONE box for the method of transportation used for most of the distance.

□ Car, truck, or van

□ Taxicab

□ Bus

□ Motorcycle

□ Subway or elevated rail □ Bicycle

□

Long-distance train or commuter rail

□ Light rail, streetcar,
or trolley

□ Walked
□ Worked from
home ➔ SKIP
to question 40a

□ Ferryboat

□ Other method

33 How many people, including this person, usually rode to work in the car, truck, or van LAST WEEK?
Person(s)
D

34 LAST WEEK, what time did this person’s trip to work usually begin?

Hour

Minute

D :D

□ a.m. □ p.m.

35 How many minutes did it usually take this person to get from home to work LAST WEEK? Minutes

QUESTIONS ABOUT WHERE PEOPLE WORK, HOW THEY GET THERE, WHEN THEY LEAVE, AND HOW LONG IT TAKES ARE USED TO CREATE DATA ABOUT COMMUTING OR A PERSON’S JOURNEY TO WORK.

Journey to work data are used in planning and funding for improvements to road and highway infrastructure, developing transportation plans and services, and understanding where people are traveling in the course of a normal day. These data are also used to evaluate transportation plans to ensure they fairly and equitably serve the needs of all groups.

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Commuting (Journey to Work) asked since 1960—Con.

COMMUTING DATA HELP COMMUNITIES:
Improve Transportation Planning
Knowing where people commute to and from, and what time of day they are commuting, helps transportation planners create mass transportation and metropolitan transportation plans that are compliant with various transportation, environmental, and antidiscrimination regulations.
Local agencies and organizations use these statistics to plan transportation programs and services that meet the diverse needs of local populations, including the disabled population, bicycle commuters, carpools, and ride-sharers. Commuting data are also used to forecast future use of new or updated transportation systems.

Ensure Equal Opportunity
Knowing where people could reasonably commute from in order to work in a certain area is used by communities and businesses for employment planning, and by communities and governments to enforce laws, regulations, and policies against employment discrimination.
Understand Changes in Commutes
As commuting patterns change, information about where people could reasonably commute from in order to work in a certain area is used to understand commercial markets and labor force participation, and to plan local emergency response programs.

30 Questions Planned for the 2020 Census and American Community Survey

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Computer and Internet Use asked since 2013.

• At this house, apartment, or mobile home -

do you or any member of this household

own or use any of the following types of

computers?

Yes No

a. Desktop or laptop

□ □

b. Smartphone
c. Tablet or other portable wireless computer

□ □ □ □

d. Some other type of computer Specify "il

□ □

• At this house, apartment, or mobile home do you or any member of this household have access to the internet?
D Yes, by paying a cell phone company or
internet service provider
D Yes, without paying a cell phone company
or internet service provider ➔ SKIP to question 12
D No access to the internet at this house,
apartment, or mobile home ➔ SKIP to question 12

Do you or any member of this household have access to the internet using a -

a. cellular data plan for a smartphone or other mobile device?

Yes No
□ □

b. broadband (high speed)

internet service such as cable,

fiber optic, or DSL service installed in this household?

□ □

c. satellite internet service installed in this household?

□ □

d. dial-up internet service installed in this household?

□ □

e. some other service? Specify service "il

□ □

QUESTIONS ABOUT THE COMPUTERS AND DEVICES THAT PEOPLE USE, WHETHER PEOPLE ACCESS THE INTERNET, AND HOW PEOPLE ACCESS THE INTERNET ARE USED TO CREATE DATA ABOUT COMPUTER AND INTERNET USE.
These statistics were first released to the public in September 2014. The questions were added as a requirement of the Broadband Data Improvement Act of 2008. They help federal agencies measure the nationwide development of broadband access and decrease barriers to broadband access.
COMPUTER AND INTERNET USE DATA HELP COMMUNITIES:
Ensure Residents Can Communicate
State and local agencies can use these statistics to evaluate access to broadband in their communities. Schools, libraries, rural health care providers, and other public service providers also use this information. Communities ensure their residents are connected to assistance programs, emergency services, and important information. These statistics may also be useful to understand whether to use Internet or more expensive outreach methods for distributing important public health or safety information.
Federal agencies use these data to evaluate the extent of access to, and adoption of broadband, with a focus on underserved areas. State and local agencies might choose to use these statistics to evaluate access to broadband in their communities.

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Disability asked since 1830.

18 a. Is this person deaf or does he/she have serious difficulty hearing?
□ Yes □ No
b. Is this person blind or does he/she have serious difficulty seeing even when wearing glasses?
□ Yes □ No
No" for EACH type 19 a. Because of a physical, mental, or emotional condition, does this person have serious difficulty concentrating, remembering, or making decisions?
□ Yes □ No
b. Does this person have serious difficulty walking or climbing stairs?
□ Yes □ No
c. Does this person have difficulty dressing or bathing?
□ Yes □ No

A premium

20 Because of a physical, mental, or emotional condition, does this person have difficulty doing errands alone such as visiting a doctor’s office or shopping?
□ Yes □ No
27

QUESTIONS ABOUT A PERSON’S DIFFICULTY WITH SPECIFIC DAILY TASKS ARE USED TO CREATE STATISTICS ABOUT DISABILITY.
Disability data are used in planning and funding government programs that provide funds or services for populations with disabilities. In addition, these data are used in evaluating other government programs and policies to ensure that they fairly and equitably serve the needs of all groups. These statistics are also used to enforce laws, regulations, and policies against discrimination.
DISABILITY DATA HELP COMMUNITIES:
Provide Adequate Housing
Knowing the different types of disabled households in a community helps communities understand whether available housing meets the needs of residents. When housing is not sufficient or not affordable, disability data can help communities enroll eligible households in programs designed to assist them and can help communities qualify for grants from the Community Development Block Grant, HOME Investment Partnership Program, Emergency Solutions Grants, Housing Opportunities for Persons With AIDS, and other programs.

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Disability asked since 1830—Con.

Provide Health Care to Children and Families
Knowing the disability status of people in families in combination with other information, such as household income, health insurance status, and poverty status, can help communities enroll eligible families in programs designed to assist them. For example, disability data are used to target efforts to enroll eligible people in Marketplace, Medicaid, and the Children’s Health Insurance Program (CHIP). Disability data are also used to ensure that Marketplace, Medicare, Medicaid, and CHIP programs are adequately serving these families.
Ensure Equal Opportunity
Knowing the disability status of people in the community in combination with information about housing, voting, employment, and education, helps governments and communities enforce laws, regulations, and policies against discrimination based on disability status. For example, disability data are used to evaluate whether there are health care or public health program disparities based on disability status (Developmental Disabilities Assistance and Bill of Rights Act of 2000).

Provide Assistance to People With Disabilities
Knowing how many people in a community over a certain age have a disability helps local officials provide programs and services to older adults that enable them to remain living safely in their homes and communities (Older Americans Act). Disability status data are also used in programs that provide services and assistance to people with a disability, such as financial assistance with utilities (Low Income Home Energy Assistance Program).
Understand Changes
Knowing whether people with disabilities have the same opportunities in education, employment, voting, homeownership, and many other areas is of interest to researchers, advocacy groups, and policymakers. Communities also need to understand changes in the needs and geographic concentrations of people with disabilities to ensure that they can meet the community’s needs during weather events, disasters, and public health emergencies.

34 Questions Planned for the 2020 Census and American Community Survey

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Fertility asked since 1890.

a. Because of a physical, mental, or emotional

25 In the PAST 12 MONTHS, has this person
given birth to any children?

□ Yes □ No

A QUESTION ABOUT WHETHER A WOMAN HAD A BABY IN THE LAST YEAR IS USED TO CREATE STATISTICS ABOUT FERTILITY.
Fertility data are used in planning government programs and adjusting other important data, such as the size of the population eligible for different services, as new people are born. These statistics can also be used to project the future size of the population and to understand more about growing families.
FERTILITY DATA HELP COMMUNITIES:
Provide Health Care to Children and Families
Knowing the number of women with a recent birth in combination with other information, such as marital status, labor force status, household income, health insurance status, and poverty status, can help communities understand changes in the demand for health care. For example, knowing how many American Indian babies are born can help

communities, tribes, and the federal government estimate the demand for health care through the Indian Health Service.
Understand Changing Households
Knowing the characteristics of women who are giving birth, including where in the country they live, is important to understand the relationships among different development patterns, including housing and travel information, public health, and pollution.
Though local vital statistics offices typically have a count of births per year, fertility data are able to provide federal program planners, policymakers, and researchers with additional statistics about the age, education, and employment of parents in households welcoming children, and other important information about the homes (age, size, etc.) and households (income, language spoken, etc.) for a more complete picture of families.
State and local agencies can use these statistics in combination with other information about new mothers, such as education and income, to understand future needs for the local education system and health services.

U.S. Census Bureau

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Grandparent Caregivers asked since 2000.

e a. Does this person have any of his/her own grandchildren under the age of 18 living in this house or apartment?
D Yes D No ➔ SKIPto question 27
b. Is this grandparent currently responsible for most of the basic needs of any grandchildren under the age of 18 who live in this house or apartment?
D Yes D No ➔ SKIPto question 27
c. How long has this grandparent been responsible for these grandchildren? If the grandparent is financially responsible for more than one grandchild , answer the question for the grandchild for whom the grandparent has been responsible for the longest period of time.
□ Less than 6 months □ 6 to 11 months □ 1 or 2 years □ 3 or 4 years □ 5 or more years
QUESTIONS ABOUT WHETHER A PERSON IS THE PRIMARY CAREGIVER FOR HIS/HER GRANDCHILDREN AND HOW LONG HE/SHE HAS CARED FOR HIS/HER GRANDCHILDREN ARE USED TO CREATE STATISTICS ABOUT GRANDPARENT CAREGIVERS.

GRANDPARENT CAREGIVER DATA HELP COMMUNITIES:
Provide Assistance to Families
Knowing more about families, particularly those where grandparents care for grandchildren, along with data about the ages of children, household income, disability, and poverty status can help communities enroll eligible families in programs designed to assist them, such as the Children’s Health Insurance Program, and can help communities qualify for grants to fund these programs. These data are also used to evaluate programs like Temporary Assistance for Needy Families.
Provide Assistance to Older Americans
Knowing how many people in a community are over a certain age, including whether older Americans are caring for grandchildren, helps local officials fund programs and services targeted to reach older adults with the greatest economic and social needs (Older Americans Act).
Understand Changing Households
Knowing more about how often grandparents are responsible for the basic care for grandchildren and how long they have been responsible in combination with information about age, presence of children, income, etc., can help communities understand if available housing and services are meeting residents’ needs.

Grandparent caregiver data help federal agencies understand the special provisions needed for federal programs designed to assist families, as older Americans are often in different financial, housing, and health circumstances than those of other ages. These data are also used to measure the effects of policies and programs that focus on the well-being of families, including tax policies and financial assistance programs.

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Health Insurance Coverage aasnkedd since 2008. Health Insurance Premiums and Subsidies starting in 2019.

. Is this person CURRENTLY covered by any of the following types of health insurance or health
coverage plans? Mark "Yes" or "No" for EACH type of coverage in items a - h.

a. Insurance through a current or former employer or union (of this
person or another family member)

Yes No
□ □

b. Insurance purchased directlh from an insurance company (by t is person or another family member)

□ □

c. Medicare, for people 65 and older, or people with certain disabilities

□ □

d. Medicaid, Medical Assistance, or any kind of government-assistance
plan for those with low incomes or a disability

□ □

e. TRICAREor other military health care □ □

f. VA (includin~ those who have enrolled for A health care)
g. Indian Health Service

□ □ □ □

h. Anh other type of health insurance or eaIth coverage plan - Specify?

□ □

17 a. Is there a premium for this plan? A premium is a fixed amount of money paid on a regular basis for health coverage. It does not include copays, deductibles, or other expenses such as prescription costs.
□ Yes □ No ➔ SKIP to question 18a
b. Does this person or another family member receive a tax credit or subsidy based on family income to help pay the premium?
□ Yes □ No

QUESTIONS ABOUT THE SOURCES OF A PERSON’S HEALTH INSURANCE ARE USED TO CREATE STATISTICS ABOUT THE PERCENTAGE OF PEOPLE COVERED BY HEALTH INSURANCE AND THE SOURCES OF HEALTH INSURANCE.
Health insurance data are used in planning government programs, determining eligibility criteria, and encouraging eligible people to participate in health insurance programs.

HEALTH INSURANCE DATA HELP COMMUNITIES:
Provide Assistance to Children and Families
Knowing the health insurance coverage status in combination with other information, such as number and age of children in families, household income, and poverty status, can help communities enroll eligible families in programs designed to assist them. For example, health insurance coverage status and age data are used to target efforts to enroll eligible people in Marketplace, Medicaid, and the Children’s Health Insurance Program (CHIP). Health Insurance data are also used to ensure that Marketplace, Medicare, Medicaid, and CHIP programs are improving health outcomes for families.

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Health Insurance Coverage aasnkedd since 2008—Con. Health Insurance Premiums and Subsidies starting in 2019—Con.

Provide Health Care for Veterans
Knowing the number and characteristics of veterans eligible to use Department of Veterans Affairs health care, compared to those currently using services, can help communities and the federal government estimate the future demand for health care services and facilities for veterans.
Provide Health Care for American Indians
Knowing the health insurance coverage status of American Indians can help communities, tribes, and the federal government estimate the demand for health care through the Indian Health Service.

Understand Changes
Knowing the health insurance coverage status of people in a community helps planners identify gaps in community services, plan programs that address those gaps, and qualify for funding for those programs.
Knowing more about changes in health insurance coverage rates and the characteristics of people who have or do not have health insurance is also of interest to researchers, advocacy groups, and policymakers. For example, State Councils on Developmental Disabilities use health insurance coverage data in their comprehensive reviews and analyses of the unmet needs of people with developmental disabilities.

40 Questions Planned for the 2020 Census and American Community Survey

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Hispanic Origin asked since 1970.

Is Person 1 of Hispanic, Latino, or Spanish origin?

□ No, not of Hispanic, Latino, or Spanish origin

□ Yes, Mexican, Mexican Am., Chicano

□ Yes, Puerto Rican

□ Yes, Cuban

□

Yes, another Hispanic, Latino, or Spanish origin - Print, for example, Salvadoran, Dominican, Colombian, Guatemalan, Spaniard, Ecuadorian, etc. 7

A QUESTION ABOUT WHETHER A PERSON IS OF HISPANIC, LATINO, OR SPANISH ORIGIN IS USED TO CREATE STATISTICS ABOUT THIS ETHNIC GROUP.
These data are required for federal and state programs and are factors in the basic research behind numerous policies, particularly for civil rights. Hispanic origin data are used in planning and funding government programs that provide funds or services for specific groups. These data are also used to evaluate government programs and policies to ensure they fairly and equitably serve the needs of the Hispanic population. They are also used to monitor compliance with antidiscrimination laws, regulations, and policies.
Though many respondents expect to see a Hispanic, Latino, or Spanish category on the race question, this question is asked separately because people of Hispanic origin may be of any race(s) in accordance with the 1997 Office of Management and Budget standards on race and ethnicity.

HISPANIC ORIGIN DATA HELP COMMUNITIES:
Ensure Equal Opportunity
Knowing about the Hispanic or Latino origin of community members in combination with information about housing, voting, language, employment, and education, to help governments and communities enforce antidiscrimination laws, regulations, and policies. For example, data on the Hispanic population are used to:
• Establish and evaluate the guidelines for federal affirmative action plans under the Federal Equal Opportunity Recruitment Program.
• Monitor compliance with the Voting Rights Act and enforce bilingual election requirements.
• Monitor and enforce equal employment opportunities under the Civil Rights Act of 1964.
• Identify segments of the population who may not be getting needed medical services under the Public Health Service Act.
• Allocate funds to school districts for bilingual services under the Bilingual Education Act.

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Hispanic Origin asked since 1970—Con.

Understand Changes
Researchers, advocacy groups, and policymakers are interested in knowing if people of Hispanic and non-Hispanic origin have the same opportunities in education, employment, voting, and homeownership. The National Science Foundation uses these data to provide information on the Hispanic population

in the science and engineering workforce. Several federal agencies use these data to investigate whether housing or transportation improvements have unintended consequences for the Hispanic population. Data on the Hispanic population are used with age and language data to address language and cultural diversity needs in health care plans for the older population.

42 Questions Planned for the 2020 Census and American Community Survey

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Home Heating Fuel asked since 1940.

13 Which FUEL is used MOST for heating this house, apartment, or mobile home?

□

Gas: from underground pipes serving the neighborhood

□ Gas: bottled, tank, or LP

□ Electricity

□ Fuel oil, kerosene, etc.

□ Coal or coke

□ Wood

□ Solar energy

□ Other fuel

□ No fuel used

QUESTIONS ABOUT HOME HEATING FUEL ARE USED TO CREATE DATA ABOUT HOME ENERGY USE.
These data are used in government programs that analyze community air quality and energy needs. Federal agencies use these statistics to forecast future energy demand, analyze the fuels available to community residents, and plan and fund programs that help low-income residents afford to heat their homes.
HOME HEATING FUEL DATA HELP COMMUNITIES:
Provide Assistance With Utilities
Knowing which fuel is used to heat homes in combination with the cost of those fuels and the characteristics of the low-income households that need assistance with their utilities, helps communities enroll eligible households in assistance programs like the Low Income Home Energy Assistance Program and qualify for grants to fund assistance. These data are also used to evaluate whether these programs benefit eligible households.

Estimate Future Energy Demand
Knowing the current users of certain heating systems and the kinds of systems used in new homes helps communities predict future demand for fuels and the future costs of systems in use in a community. For example, the Department of Energy uses these data to project demand over the next 30 years, assessing the energy needs of the U.S. economy in a domestic and international context.
Measure Environmental Impacts
Communities with older heating systems may have lower air quality at times when they are in high use. Home heating fuel data are used to develop an inventory of the national aggregate emissions of each greenhouse gas and to research and report on the relationships among different development patterns (including housing and travel information) and public health and pollution (Clean Air Act, Clean Water Act).

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Home Value and Rent asked since 1940.

18 a. What is the monthly rent for this
house, apartment, or mobile home? Monthly amount – Dollars

$

,

.00

b. Does the monthly rent include any meals?
□ Yes □ No

19 About how much do you think this
house and lot, apartment, or mobile home (and lot, if owned) would sell for if it were for sale? Amount – Dollars

$,

,

.00

QUESTIONS ABOUT THE MONTHLY RENT AMOUNT OR HOW MUCH THE HOME AND PROPERTY ARE WORTH ARE USED TO PRODUCE STATISTICS ABOUT RENT AND HOME VALUE.
These data are used in government programs that analyze whether adequate housing is affordable for residents and provide and fund housing assistance programs. These statistics are also used to enforce laws, regulations, and policies designed to eliminate discrimination in private-market housing, government programs, and in society.
HOME VALUE AND RENT DATA HELP COMMUNITIES:
Provide Adequate Housing
Knowing the different types of households in a community (single people, couples, families, roommates, etc.) helps communities understand whether available housing meets the needs of residents. Housing costs in combination with relationship and combined income of all people in a household helps communities understand whether housing is affordable.

When rental housing is not affordable, rent data are used to identify rental distribution of housing units (the standard cost of different types of housing in different areas of the country) and to determine Fair Market Rents, which the Department of Housing and Urban Development uses to determine the amount of tenant subsidies in housing assistance programs.
When housing is not sufficient or not affordable, housing cost data can help communities enroll eligible households in programs designed to assist them and can help communities qualify for grants from the Community Development Block Grant, HOME Investment Partnership Program, Emergency Solutions Grants, Housing Opportunities for Persons With AIDS, and other programs.
Plan Community Development
Knowing how the balance of rented homes, mortgaged homes, and owned homes changes over time can help communities understand changes in local housing markets and identify opportunities to improve tax, assistance, and zoning policies.
Ensure Equal Opportunity
Knowing more about people who rent and people who own homes in the community in combination with age, sex, race, Hispanic origin, disability, and other data, helps government and communities enforce laws, such as the 1968 Fair Housing Act designed to eliminate discrimination in housing.

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Income asked since 1940.

INCOME IN THE PAST 12 MONTHS
Mark (X) the "Yes" box for each type of income this person received, and give your best estimate of the TOTAL AMOUNT during the PAST 12 MONTHS. (NOTE: The "past 12 months " is the period from today's date one year ago up through today.)
Mark (X) the "No " box to show types of income NOT received.
If net income was a loss, mark the "Loss" box to the right of the dollar amount.
For income received jointly, report the appropriate share for each person - or, if that's not possible, report the whole amount for only one person and mark the "No " box for the other person.

a. Wages, salary, commissions, bonuses, or tips from all jobs. Report amount before deductions for taxes, bonds, dues, or other items.

□ Yes ➔ I$

.ool

□ No .___~ __ __,____

_J_

TOTALAMOUNT for past 12 months

b. Self-employment income from own nonfarm businesses or farm businesses, including proprietorships and partnerships. Report NET income after business expenses.

□ Yes ➔ I$ .ool □ No .___~ __ __,____

_J_

□

TOTALAMOUNT for past

Loss

12 months

c. Interest, dividends, net rental income, royalty income, or income from estates and trusts. Report even small amounts credited to an account.

□ Yes ➔ I$
□ No .___ _,___ __,___

.ool ____J

□

TOTALAMOUNT for past

Loss

12 months

d. Social Security or Railroad Retirement.

□ Yes ➔ I$

.olo

□ No .____ _,____

___J _

TOTALAMOUNT for past 12 months

e. Supplemental Security Income (SSI).

□ Yes ➔ I$

□ No

L..__ __

.i..._ ___

.olo _j

TOTALAMOUNT for past 12 months

f. Any public assistance or welfare payments from the state or local welfare office.

□ Yes ➔ I$

.olo

□ No

'-----'-----_j

TOTALAMOUNT for past

12 months

g. Retirement income, pensions, survivor or disability income . Include income from a previous employer or union, or any regular withdrawals or distributions from IRA, Roth IRA, 401(k), 403(b) or
other accounts specifically designed for retirement. Do not include Social Security.

□ Yes ➔ I$

.ool

□ No ._____

_,____

___J_

TOTALAMOUNT for past 12 months

h. Any other sources of income received regularly such as Veterans' (VA) payments, unemployment compensation, child support or alimony . Do NOT include lump sum payments such as money from an inheritance or the sale of a home .

□ Yes ➔ I$

.ool

□ No

'------'-----_J

TOTALAMOUNT for past

12 months

What was this person's total income during the
PAST 12 MONTHS? Add entries in questions 43a to 43h; subtract any losses. If net income was a Joss, enter the amount and mark (X) the "Loss" box next to the dollar amount.

□ oR ~I$~'---------'---___□J.ool

None

Loss

TOTALAMOUNT for past

12 months

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Questions Planned for the 2020 Census and American Community Survey 47

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Income asked since 1940—Con.

QUESTIONS ABOUT THE FUNDS A PERSON RECEIVES FROM VARIOUS SOURCES ARE USED TO CREATE STATISTICS ABOUT INCOME, ASSISTANCE, EARNINGS, AND POVERTY STATUS.
Income data are used in planning and funding government programs that provide economic assistance for populations in need and measure the economic well-being of the nation. Income and poverty estimates are often part of allocation formulas that determine how food, health care, job training, housing, and other assistance are distributed.
INCOME DATA HELP COMMUNITIES:
Provide Adequate Housing
Knowing the combined income of all people in a household in combination with housing costs helps communities understand whether housing is affordable for residents. When housing is not sufficient or not affordable, income data can help communities enroll eligible households in programs designed to assist them and can help communities qualify for grants from the Community Development Block Grant, HOME Investment Partnership Program, Emergency Solutions Grant, Housing Opportunities for Persons With AIDS, and other programs.
Provide Assistance to Older Americans
Knowing how many older people in a community are living in poverty in combination with other information, such as age and disability status of other family members, can help communities ensure these residents receive appropriate assistance, such as financial assistance with utilities (Low Income Home Energy Assistance Program).

Provide Assistance to Children and Families
Knowing household income in combination with other information, such as the number and age of children in families, health insurance status, and poverty status, can help communities enroll eligible families in programs designed to assist them. For example, income data are used to identify eligibility and provide funding in programs like Medicaid, the Child and Adult Care Food Program, and Head Start.
Educate Children and Adults
Knowing how many children and adults depend on services through schools helps school districts make long-term building, staffing, and funding decisions. Household income and family composition determine poverty status, which is used along with school enrollment, information on disability status, and language spoken at home, to help schools understand the needs of their students and qualify for grants that help fund programs for students with needs for additional services or assistance, including free/reduced price school lunches (Elementary and Secondary Education Act of 1965).
Plan Community Development
Knowing more about the financial situation of residents, including income, employment, and housing costs, can help communities qualify for loan and grant programs designed to stimulate economic recovery, improve housing, run job-training programs, and define areas as empowerment or enterprise zones.

48 Questions Planned for the 2020 Census and American Community Survey

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Industry, asked since 1820.1 Occupation,aaskneddsince 1850. Class of Worker asked since 1910.

42 DESCRIPTION OF EMPLOYMENT The next series of questions is about the type of employment this person had last week. If this person had more than one job, describe the one at which the most hours were worked. If this person did not work last week, describe the most recent employment in the past five years.

a. Which one of the following best describes this

person’s employment last week or the most

recent employment in the past 5 years?

43

Mark (X) ONE box.

PRIVATE SECTOR EMPLOYEE

□ For-profit company or organization

□

Non-profit organization (including tax-exempt and charitable organizations)

GOVERNMENT EMPLOYEE

□

Local government (for example: city or county school district)

□

State government (including state colleges/universities)

□

Active duty U.S. Armed Forces or Commissioned Corps

□ Federal government civilian employee

SELF-EMPLOYED OR OTHER

□

Owner of non-incorporated business, professional practice, or farm

□

Owner of incorporated business, professional practice, or farm

□

Worked without pay in a for-profit family business or farm for 15 hours or

more per week

b. What was the name of this person’s employer, business, agency, or branch of the Armed Forces?

c. What kind of business or industry was this? Include the main activity, product, or service provided at the location where employed. (For example: elementary school, residential construction)

d. Was this mainly – Mark (X) ONE box.

□ manufacturing?

□ wholesale trade?

□ retail trade?

□

other (agriculture, construction, service, government, etc.)?

e. What was this person’s main occupation? (For example: 4th grade teacher, entry-level plumber)
f. Describe this person’s most important activities or duties. (For example: instruct and evaluate students and create lesson plans, assemble and install pipe sections and review building plans for work details)
INCOME IN THE PAST 12 MONTHS
QUESTIONS ABOUT A PERSON’S EMPLOYER, THE KIND OF BUSINESS OR INDUSTRY OF THAT EMPLOYER, THE KIND OF WORK A PERSON DOES, AND THAT PERSON’S MOST IMPORTANT ACTIVITIES ARE USED TO PRODUCE INDUSTRY, OCCUPATION, AND CLASS OF WORKER STATISTICS.
These data are used to provide information about the labor force to evaluate government programs and policies to ensure they fairly and equitably serve the needs of all groups, and to enforce laws, regulations, and policies against discrimination in society.1
1 Industry asked in 1820, 1840, and 1910 to present.

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, Industry asked since 1820—Con.
Occupation,aaskneddsince 1850—Con. Class of Worker asked since 1910—Con.

INDUSTRY, OCCUPATION, AND CLASS OF WORKER DATA HELP COMMUNITIES:
Provide Employment Opportunities
Knowing whether programs designed to employ specific groups, such as people with disabilities or veterans, are succeeding is important to employers, federal agencies, and federal government contractors (Vietnam Era Veterans’ Readjustment Assistance Act, Rehabilitation Act of 1973). Industry, occupation, and class of worker data provide additional detail about the jobs and careers pursued by people participating in these programs.
State and local agencies use these statistics to identify labor surplus areas (areas with people available for hiring and training), plan workforce development programs including job fairs and training programs, and promote business opportunities.

Ensure Equal Employment Opportunity
Knowing more about people who are employed or looking for work in combination with educational attainment, age, sex, race, Hispanic origin, disability status, veteran status, and other data, helps governments and communities enforce civil rights laws against employment discrimination. For example, these data are used to enforce nondiscrimination in employment by federal agencies, private employers, employment agencies, and labor organizations (Civil Rights Act of 1964).
Understand Changes
Knowing the characteristics of growing or declining industries and occupations is an important part of estimating changes in the economy. Labor force estimates are used in funding decisions; to ensure surveys are accurate, including surveys that provide official labor market estimates; and to understand change in other data (Wagner-Peyser Act and Workforce Investment Act).
Class of worker data, in particular, are used by the National Institute of Food and Agriculture to understand changes in farm workers and agriculture.

50 Questions Planned for the 2020 Census and American Community Survey

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Labor Force Status asked since 1890.

30 a. LAST WEEK, did this person work for pay at a job (or business)?
□ Yes ➔ SKIP to question 31 □ No – Did not work (or retired)
b. LAST WEEK, did this person do ANY work for pay, even for as little as one hour?
□ Yes □ No ➔ SKIP to question 36a

36 a. LAST WEEK, was this person on layoff from a job?

□ Yes ➔ SKIP to question 36c □ No

b. LAST WEEK, was this person TEMPORARILY absent from a job or business?

□

Yes, on vacation, temporary illness, maternity leave, other family/personal

reasons, bad weather, etc. ➔ SKIP to

question 39

□ No ➔ SKIP to question 37

• c. Has this person been informed that he or she will be recalled to work within the next 6 months OR been given a date to return to work?
D Yes ➔ SKIPto question 38
□ No
During the LAST 4 WEEKS, has this person been ACTIVELY looking for work?
D Yes D No ➔ SKIPto question 39
LAST WEEK, could this person have started a job if offered one, or returned to work if recalled?
D Yes, could have gone to work D No, because of own temporary illness D No, because of all other reasons (in school, etc.)

QUESTIONS ABOUT WHETHER A PERSON WORKED LAST WEEK AND, IF THE ANSWER IS NO, WHETHER HE/SHE WAS LOOKING FOR WORK, WHETHER HE/SHE PLANS TO RETURN TO WORK, AND HOW MUCH THEY WORKED IN THE PAST YEAR ARE USED TO PRODUCE STATISTICS ABOUT THE LABOR FORCE, INCLUDING UNEMPLOYMENT STATISTICS.

Labor force data are used in planning and funding government programs that provide unemployment assistance and services. These data are also used to evaluate other government programs and policies to ensure they fairly and equitably serve the needs of all groups, and to enforce laws, regulations, and policies against discrimination in society.

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Labor Force Status asked since 1890—Con.

LABOR FORCE DATA HELP COMMUNITIES:
Provide Employment Opportunities
Knowing whether programs designed to employ specific groups, such as people with disabilities or veterans, are succeeding is important to employers, federal agencies, and federal government contractors (Vietnam Era Veterans’ Readjustment Assistance Act, Rehabilitation Act of 1973).
State and local agencies use these statistics to identify labor surplus areas (areas with people available for hiring and training), plan workforce development programs, including job fairs and training programs, and to promote business opportunities.

Ensure Equal Opportunity
Knowing more about people who are employed or looking for work in combination with age, sex, race, Hispanic origin, disability status, veteran status, and other data, helps governments and communities enforce laws, regulations, and policies against discrimination in employment. For example, labor force data are used to enforce nondiscrimination in employment by federal agencies, private employers, employment agencies, and labor organizations (Civil Rights Act of 1964).
Understand Changes
Knowing the characteristics of people who are working or looking for work is an important part of estimating changes in the economy. Labor force estimates are used in funding decisions; to ensure surveys are accurate, including surveys that provide official labor market estimates; and to understand change in other data (Wagner-Peyser Act and Workforce Investment Act).

52 Questions Planned for the 2020 Census and American Community Survey

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Language Spoken at Home asked since 1890.1

14 a. Does this person speak a language other than English at home?
□ Yes □ No ➔ SKIP to question 15a
b. What is this language?
For example: Korean, Italian, Spanish, Vietnamese c. How well does this person speak English?
□ Very well □ Well □ Not well □ Not at all
QUESTIONS ABOUT WHETHER A PERSON SPEAKS A LANGUAGE OTHER THAN ENGLISH AT HOME, WHAT LANGUAGE HE/SHE SPEAKS, AND HOW WELL HE/SHE SPEAKS ENGLISH ARE USED TO CREATE STATISTICS ABOUT LANGUAGE AND ABILITY TO SPEAK ENGLISH.
Language data are used in planning government programs for adults and children who do not speak English well. These data are also used to ensure that information about public health, law, regulations, voting, and safety is communicated in languages that community members understand.1
1 Language spoken at home was not asked in 1950.

LANGUAGE SPOKEN AT HOME DATA HELP COMMUNITIES:
Educate Children
Knowing how many children and youth with limited English-speaking abilities depend on services through schools helps school districts make long-term staffing and funding decisions. Language spoken at home in combination with other information, such as disability status, school enrollment, and poverty status, helps schools understand the needs of their students and qualify for grants that help fund programs for those students (Elementary and Secondary Education Act of 1965).
Ensure Equal Opportunity
Knowing the languages spoken by people in the community in combination with information about housing, voting, employment, and education, helps the government and communities enforce laws, regulations, and policies against discrimination based on national origin. For example, language data are used to support the enforcement responsibilities under the Voting Rights Act to investigate differences in voter participation rates and to enforce laws and policies related to bilingual requirements.
Knowing languages spoken in a community also helps federal agencies identify needs for services for people with limited English proficiency under Executive Order 13166.
Understand Changes
Knowing whether people who speak languages other than English have the same opportunities in education, employment, voting, homeownership, and many other areas is of interest to researchers, advocacy groups, and policymakers. For example, language data are used with age and ancestry data to address language and cultural diversity needs in health care plans for the older population.

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Marital Status aasnkedd since 1880. Marital History asked since 1850.

A premium

21 What is this person’s marital status?

□ Now married □ Widowed □ Divorced □ Separated □ Never married ➔ SKIP to J

22 In the PAST 12 MONTHS did this person get – Yes No

a. Married?

□ □

b. Widowed?

□ □

c. Divorced?

□ □

23 How many times has this person been married?

□ Once □ Two times □ Three or more times
24 In what year did this person last get married? Year

QUESTIONS ABOUT WHETHER A PERSON IS CURRENTLY MARRIED, WIDOWED, DIVORCED, SEPARATED, OR NEVER MARRIED; WHETHER HIS/ HER MARITAL STATUS CHANGED IN THE PAST 12 MONTHS; AND LIFETIME MARRIAGES ARE USED TO CREATE STATISTICS ABOUT CURRENT MARITAL STATUS AND MARITAL HISTORY.
Marital status and marital history data help federal agencies understand marriage trends, forecast future needs of programs that have spousal benefits, and measure the effects of policies and programs that focus on the well-being of families, including tax policies and financial assistance programs.

MARITAL STATUS AND MARITAL HISTORY DATA HELP COMMUNITIES:
Provide Benefits to Spouses and Survivors
Knowing more about how many spouses and ex-spouses may qualify for programs with spousal benefits, including veteran and social security programs, can help federal agencies ensure adequate funding and facilities for these programs and can help communities determine where gaps in benefits and services might exist.
Provide Assistance to Families
Knowing more about families, particularly blended and single-parent families, along with data about the presence of children, labor force status, and poverty status, can help communities enroll eligible families in programs designed to assist them, such as the Children’s Health Insurance Program, and can help communities qualify for grants to fund these programs. These data are also used to evaluate programs like Temporary Assistance for Needy Families.
Understand Changing Households
Knowing more about community marriage trends (whether people are marrying later in life, not getting married, or marrying again) in combination with information about age, presence of children, income, etc., can help communities understand if the available housing, job training, rental assistance, and administrative services and programs are meeting residents’ needs during their major life changes. These data also help the federal government plan for the future. For example, the Social Security Administration estimates future program needs based on the current relationships of working people.

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Migration (Previous Residence)/Residence 1 Year Ago
asked since 1930.

a. Did this person live in this house or apartment 1 year ago?
D Person is under 1 year old ➔ SKIP to question 16
D Yes, this house ➔ SKIP to question 16 D No, outside the United States and
Puerto Rico- Print name of foreign country,
or U.S. Virgin Islands, Guam, etc., below; then SKIP to question 16
D No, different house in the United States or
Puerto Rico b. Where did this person live 1 year ago?
Address (Number and street name)

Name of city, town, or post office

Name of U.S. county or municipio in Puerto Rico

Name of U.S. state or Puerto Rico

ZIP Code

QUESTIONS ABOUT WHETHER A PERSON MOVED IN THE LAST YEAR AND WHERE HE OR SHE LIVED 1 YEAR AGO ARE USED TO CREATE STATISTICS ABOUT WHERE PEOPLE ARE MOVING (TO/FROM FOREIGN COUNTRIES AND WITHIN THE UNITED STATES).
Migration (residence 1 year ago) data are used in planning government programs. The characteristics of people who have moved are also an important part of estimating population changes. These population estimates are used in funding decisions, to ensure surveys are accurate, to understand change in other data, and to produce official international migration estimates.
MIGRATION/RESIDENCE 1 YEAR AGO DATA HELP COMMUNITIES:
Understand Changes
Knowing the characteristics of people who have moved and the patterns of migration (where people move to and from) is an important part of estimating population changes. Population estimates are used in funding decisions, to ensure surveys are accurate, to understand change in other data, and to produce international migration estimates. These data also help agencies assess residential stability and the effects of migration on urban and rural areas.
Knowing where certain populations move to and from helps federal agencies assess the needs of counties with large refugee populations and the effects of immigration on local areas.
Knowing the characteristics of people who live or have lived in certain areas is important to understand the relationships among different development patterns, including housing and travel information, public health, and pollution. These data may also assist state and local agencies in developing programs that attract new residents or employers.

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Place of Birth,asked since 1850. Citizenship,aaskneddsince 1820.1 Year of Entry asked since 1890.2

7 Where was this person born?
□ In the United States – Print name of state.

□

Outside the United States – Print name of foreign country, or Puerto Rico, Guam, etc.

8 Is this person a citizen of the United States?

□

Yes, born in the United States ➔ SKIP to question 10a

□

Yes, born in Puerto Rico, Guam, the U.S. Virgin Islands, or Northern Marianas

□

Yes, born abroad of U.S. citizen parent or parents

□

Yes, U.S. citizen by naturalization – Print year of naturalization

□ No, not a U.S. citizen
9 When did this person come to live in the United States? If this person came to live in the
United States more than once, print latest year. Year
I_ J_I __ ~

QUESTIONS ABOUT A PERSON’S PLACE OF BIRTH, CITIZENSHIP, AND YEAR OF ENTRY INTO THE UNITED STATES ARE USED TO CREATE DATA ABOUT CITIZENS, NONCITIZENS, AND THE FOREIGN-BORN POPULATION.
These statistics are essential for agencies and policymakers setting and evaluating immigration policies and laws; seeking to understand the experience of different immigrant groups; and enforcing laws, policies, and regulations against discrimination based on national origin. These statistics are also used to tailor services to accommodate cultural differences.
1 Citizenship asked 1820, 1830, 1870, and 1890 to present. 2 Year of entry asked 1890–1930 and 1970 to present.

PLACE OF BIRTH, CITIZENSHIP, AND YEAR OF ENTRY DATA HELP COMMUNITIES:
Ensure Equal Opportunity
Knowing how many people in the community are born in other countries in combination with information about housing, voting, language, employment, and education, helps the government and communities to enforce laws, regulations, and policies against discrimination based on national origin. For example, these data are used to support the enforcement responsibilities under the Voting Rights Act to investigate differences in voter participation rates and to enforce other laws and policies regarding bilingual requirements.
Educate Children
Knowing how many foreign-born children depend on services through schools helps school districts make staffing and funding decisions. Place of birth, citizenship, and year of entry statistics in combination with other information, such as language spoken at home, help schools understand the needs of their students and qualify for grants that help fund programs for those students (Elementary and Secondary Education Act of 1965).
Understand Changes
Knowing whether people of different races or countries of birth have the same opportunities in education, employment, voting, homeownership, and many other areas is of interest to researchers, advocacy groups, and policymakers. These data may also help communities with large refugee populations that qualify for financial assistance (Immigration Nationality Act).

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Plumbing Facilities,asked since 1940. Kitchen Facilities,aaskneddsince 1940. Telephone Service asked since 1960.

7 Does this house, apartment, or mobile

home have –

Yes No

a. hot and cold running water?

□ □

b. a bathtub or shower?

□ □

c. a sink with a faucet?

□ □

d. a stove or range?

□ □

e. a refrigerator?

□ □

8 Can you or any member of this household both make and receive phone calls when at this house, apartment, or mobile home? Include calls using cell phones, land lines, or other phone devices.
□ Yes □ No

QUESTIONS ABOUT THE PRESENCE OF HOT AND COLD RUNNING WATER, A BATHTUB OR SHOWER, A SINK WITH A FAUCET, A STOVE OR RANGE, A REFRIGERATOR, AND TELEPHONE SERVICE ARE USED TO CREATE DATA ABOUT INDICATORS OF HOUSING QUALITY.
These data are used in planning and funding government programs that identify areas eligible for housing assistance, rehabilitation loans, and other programs that help people access and afford decent, safe, and sanitary housing. Public health officials may also use this information to locate areas in danger of groundwater contamination and waterborne diseases.

PLUMBING FACILITIES, KITCHEN FACILITIES, AND TELEPHONE SERVICE DATA HELP COMMUNITIES:
Provide Adequate Housing
Knowing more about the quality of housing in a community helps communities understand whether available housing meets the needs of residents. When housing is not sufficient or not affordable, data on household facilities can help communities enroll eligible households in programs designed to assist them, and can help communities qualify for grants from the Community Development Block Grant, HOME Investment Partnership Program, Emergency Solutions Grant, Housing Opportunities for Persons With AIDS, and other programs.
Plan Community Development
Knowing how the quality of different types of homes in combination with whether they are occupied or vacant, can help communities identify opportunities to improve tax, assistance, and zoning policies and to reduce tax revenue losses from vacant or abandoned properties. These data may also be useful in identifying types of homes in disaster-prone areas during emergency planning and preparation.
Ensure Residents Can Communicate
Measuring the extent of telephone service helps communities ensure their residents have universal access to assistance programs, emergency services, and important information.
Measure Environmental Impacts
Substandard plumbing systems may impact the local water supply. Understanding where these systems are concentrated helps communities research their wastewater infrastructure needs and work to improve their systems.

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Race asked since 1790.

What is Person 1 's race? Mark (X) one or more boxes AND print origins.
□ White - Print, for example, German, Irish, English, Italian, Lebanese,
Egyptian, etc. "i1
□ Black or African Am. - Print, for example, African American, Jamaican ,
Haitian, Nigerian, Ethiopian, Somali, etc. "i1
□ American Indian or Alaska Native - Print name of enrolled or principal tribe(s), for example, Navajo Nation, Blackfeet Tribe, Mayan, Aztec, Native Village of Barrow lnupiat Traditional Government, Nome Eskimo Community, etc. "i1

□ Chinese □ Filipino □ Asian Indian □ Other Asian -
Print, for example,
Pakistani, Cambodian,
Hmong, etc. "i1

□ Vietnamese □ Korean □ Japanese

□ Native Hawaiian □ Samoan □ Chamorro □ Other Pacific Islander -
Print, for example,
Tongan, Fijian ,
Marsha/Iese, etc. "i1

□ Some other race - Print race or origin. "i1

A QUESTION ABOUT A PERSON’S RACE IS USED TO CREATE STATISTICS ABOUT RACE AND TO PRESENT OTHER ESTIMATES BY RACE GROUPS.
These data are required for federal, state, and tribal programs and are critical factors in the basic research behind numerous policies, particularly for civil rights. Race data are used in planning and funding government programs that provide funds or services for specific groups. These data are also used to evaluate government programs and policies to ensure they fairly and equitably serve the needs

of all racial groups and to monitor compliance with antidiscrimination laws, regulations, and policies.
The U.S. Census Bureau collects race data in accordance with the 1997 Office of Management and Budget standards on race and ethnicity. The categories on race are based on self-identification and generally reflect a social definition of race. The categories are not an attempt to define race biologically, anthropologically, or genetically.
RACE DATA HELP COMMUNITIES:
Ensure Equal Opportunity
Knowing the races of community members in combination with information about housing, voting, language, employment, and education,

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Race asked since 1790—Con.

helps government and communities enforce antidiscrimination laws, regulations, and policies. For example, race data are used in the following ways:
• Establish and evaluate the guidelines for federal affirmative action plans under the Federal Equal Opportunity Recruitment Program.
• Monitor compliance with the Voting Rights Act and enforce bilingual election requirements.
• Monitor and enforce equal employment opportunities under the Civil Rights Act of 1964.
• Identify segments of the population who may not be getting needed medical services under the Public Health Service Act.
• Allocate funds to school districts for bilingual services under the Bilingual Education Act.
Understand Changes
Knowing if people of different races have the same opportunities in education, employment, voting, homeownership, and many other areas is of interest

to researchers, advocacy groups, and policymakers. The National Science Foundation uses data on race to provide information on people of different racial backgrounds in the science and engineering workforce. Several federal agencies use race data to investigate whether housing or transportation improvements have unintended consequences for specific race groups. Data on race are used with age and language data to address language and cultural diversity needs in health care plans for the older population.
Administer Programs for Specific Groups
Knowing how many people are eligible to participate in certain programs helps communities, including tribal governments, ensure that programs are operating as intended. For example, the Indian Housing Block Grant program, Indian Community Development Block Grant program, and Indian Health Service all depend on accurate estimates of American Indians and Alaska Natives. Data for the American Indian and Alaska Native population come from the question about a person’s race.

64 Questions Planned for the 2020 Census and American Community Survey

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Relationship asked since 1880.

2 How is this person related to Person 1? Mark (X) ONE box.

2

□ Opposite-sex husband/wife/spouse □ Opposite-sex unmarried partner □ Same-sex husband/wife/spouse □ Same-sex unmarried partner □ Biological son or daughter □ Adopted son or daughter □ Stepson or stepdaughter □ Brother or sister

□ Father or mother □ Grandchild □ Parent-in-law □ Son-in-law or daughter-in-law □ Other relative □ Roommate or housemate □ Foster child □ Other nonrelative

A QUESTION ABOUT THE RELATIONSHIP OF EACH PERSON IN A HOUSEHOLD TO ONE CENTRAL PERSON IS USED TO CREATE ESTIMATES ABOUT FAMILIES, HOUSEHOLDS, AND OTHER GROUPS, AND TO PRESENT OTHER DATA AT A HOUSEHOLD LEVEL.
Relationship data are used in planning and funding government programs that provide funds or services for families, people living or raising children alone, grandparents living with grandchildren, or other households that qualify for additional assistance.
RELATIONSHIP DATA HELP COMMUNITIES:
Provide Adequate Housing
Knowing about the different types of households in a community (single people, couples, families, roommates, etc.) helps communities understand whether available housing meets the needs of residents. Information about the relationships among people in a household, in combination with housing costs and the combined income of all people in a household, helps communities understand whether housing is affordable for residents.

When housing is not sufficient or not affordable, relationship data can help communities enroll eligible households in programs designed to assist them, and can help communities qualify for grants from the Community Development Block Grant, HOME Investment Partnership Program, Emergency Solutions Grant, Housing Opportunities for Persons With AIDS, and other programs.
Provide Assistance to Families
Knowing more about families, such as the ages of children, household income, health insurance status, and poverty status, can help communities enroll eligible families in programs designed to assist them, such as Head Start and the Children’s Health Insurance Program, and can help communities qualify for grants to fund these programs. Relationship data are also used to ensure that programs like Temporary Assistance for Needy Families are making a difference for families.
Understand Changing Households
Information about living arrangements and how they are changing, including whether older residents are staying in their homes as they age, whether young people are living with parents or moving in with roommates, and which kinds of households include young children, can help communities plan future programs and services for residents. For example, the Social Security Administration estimates future program needs based on the current relationships of working people.

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School Enrollment, asked since 1850. Educational Attainment, aaskneddsince 1940. Undergraduate Field of Degree asked since 2009.

1 a. At any time IN THE LAST 3 MONTHS, has this person attended school or college? Include only nursery or preschool, kindergarten, elementary school, home school, and schooling which leads to a high school diploma or a college degree.
11 D No, has not attended in the last 3 months ➔ SKIP to question
D Yes, public school, public college □ Yes, private school, private college,
home school
b. What grade or level was this person attending? Mark (X) ONE box.
D Nursery school, preschool
D Kindergarten D Grade 1 through 12 - Specify
grade 1- ✓
[J
D College undergraduate years (freshman to senior) □ Graduate or professional school beyond a
bachelor's degree (for example: MA or PhD program, or medical or Jaw school)

What is the highest degree or level of school this person has COMPLETED? Mark (X) ONE box. If currently enrolled, mark the previous grade or highest degree received.
NO SCHOOLING COMPLETED
D No schooling completed
NURSERY OR PRESCHOOL THROUGH GRADE 12
D Nursery school
D Kindergarten
1-7 D Grade 1 through 11 - Specify grade [J
□ 12th grade - NO DIPLOMA
HIGH SCHOOL GRADUATE
D Regular high school diploma
D GED or alternative credential
COLLEGE OR SOME COLLEGE
D Some college credit, but less than 1 year of college credit
D 1 or more years of college credit, no degree
D Associate's degree (for example: AA, AS)
D Bachelor's degree (for example: BA, BS)
AFTER BACHELOR'S DEGREE
D Master's degree (for example: MA, MS, MEng, MEd, MSW, MBA)
D Professional dl:l91eebeyond a bachelor's degree (for example: MD, DDS, DVM, LLB, JD)
D Doctorate degree (for example: PhD, EdD)

This question focuses on this person's BACHELOR'S DEGREE. Please print below the specific major(s) of any BACHELOR'S DEGREES this person has received. (For example: chemical engineering, elementary teacher education, organizational psychology)

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School Enrollment asked since 1850—Con. Educational Attainment asked since 1940—Con. Undergraduate Field of Degree asked since 2009—Con.

QUESTIONS ABOUT WHETHER A PERSON IS ATTENDING SCHOOL OR COLLEGE, THE HIGHEST LEVEL OF EDUCATION HE/SHE HAS COMPLETED, AND THE FIELD OF ANY COMPLETED UNDERGRADUATE COLLEGE DEGREES ARE USED TO CREATE DATA ABOUT EDUCATION.
These statistics are used to analyze the characteristics and needs of school-aged children and to understand the continuing education needs of adults.
SCHOOL ENROLLMENT, EDUCATIONAL ATTAINMENT, AND UNDERGRADUATE FIELD OF DEGREE DATA HELP COMMUNITIES:
Educate Children and Adults
Knowing how many children and adults depend on services through schools helps school districts make long-term building, staffing, and funding decisions. School enrollment in combination with other information, such as disability status, language spoken at home, and poverty status, helps schools understand the needs of their students and qualify for grants that help fund programs for those students (Elementary and Secondary Education Act of 1965).

Knowing how many adults do not have a high school diploma or equivalent helps schools understand the needs of adult students and qualify for grants that help fund programs for these students (Workforce Investment Act).
Knowing the major fields of study of adults with bachelor’s degrees enables efforts to develop the nation’s science, technology, engineering, and mathematics labor force (America COMPETES Reauthorization Act of 2010).
Ensure Equal Opportunity
Understanding more about the characteristics of people enrolled or not enrolled in school helps government and communities enforce laws, regulations, and policies against discrimination in education (Civil Rights Act of 1964).
Knowing the educational attainment of workers compared to those seeking employment in combination with age, sex, race, Hispanic origin, disability, and other data, helps enforce nondiscrimination in employment by federal agencies, private employers, employment agencies, and labor organizations (Civil Rights Act of 1964).

68 Questions Planned for the 2020 Census and American Community Survey

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Selected Monthly Owner Costs (Cost of Utilities, Condominium and Mobile Home Fees, Taxes, Insurance, and Mortgages).1

14 a. LAST MONTH, what was the cost of electricity for this house, apartment, or mobile home? Last month’s cost – Dollars

$,

.00

OR

□ Included in rent or condominium fee □ No charge or electricity not used

b. LAST MONTH, what was the cost of gas for this house, apartment, or mobile home? Last month’s cost – Dollars

or heating this pipes serving the

$,

.00

OR

□ Included in rent or condominium fee

□

Included in electricity payment entered above

□ No charge or gas not used

c. IN THE PAST 12 MONTHS, what was the cost of water and sewer for this house, apartment, or mobile home? If you have lived here less than 12 months, estimate the cost.
Past 12 months’ cost – Dollars

$,

.00

OR

□ Included in rent or condominium fee

□ No charge

d. IN THE PAST 12 MONTHS, what was the cost of oil, coal, kerosene, wood, etc., for this house, apartment, or mobile home? If you have lived here less than 12 months, estimate the cost.
Past 12 months’ cost – Dollars

$,

.00

OR

□ Included in rent or condominium fee □ No charge or these fuels not used

1
1 Cost of utilities asked since 1940, condominium and mobile home fees asked since 1990, taxes asked in 1940 and since 1980, insurance cost asked since 1980, and mortgages cost asked in 1940 and since 1980.

16 Is this house, apartment, or mobile home part of a condominium?

□

Yes ➔ What is the monthly condominium fee? For renters,

answer only if you pay the

condominium fee in addition to

your rent; otherwise, mark the

"None" box.

Monthly amount – Dollars

$,

.00

OR

□ No

□ None

20 What are the annual real estate taxes on THIS property? Annual amount – Dollars

$

,

.00

OR
□ None

21 What is the annual payment for fire, hazard, and flood insurance on THIS property? Annual amount – Dollars

$,

.00

OR

□ None

22 a. Do you or any member of this

23

household have a mortgage, deed of

trust, contract to purchase, or similar

debt on THIS property?

□

Yes, mortgage, deed of trust, or similar debt

□ Yes, contract to purchase

□ No ➔ SKIP to question 23a

b. How much is the regular monthly mortgage payment on THIS property? Include payment only on FIRST mortgage or contract to purchase.
Monthly amount – Dollars

$

,

.00

OR

□

No regular payment required ➔ SKIP to question 23a

c. Does the regular monthly mortgage

payment include payments for real

estate taxes on THIS property?

D

□

Yes, taxes included in mortgage payment

□

No, taxes paid separately or taxes not required

24 d. Does the regular monthly mortgage
payment include payments for fire, hazard, or flood insurance on THIS property?

□

Yes, insurance included in mortgage payment

□

No, insurance paid separately or no insurance

24 What are the total annual costs for personal property taxes, site rent, registration fees, and license fees on

23 a. Do you or any member of this household have a second mortgage or a home equity loan on THIS

THIS mobile home and its site?

property?

Exclude real estate taxes.

Yes, mortgage, deed of trust, or similar Annual costs – Dollars

□ Yes, home equity loan

$

,

.00

□ Yes, second mortgage

□

Yes, second mortgage and home equity loan

□ No ➔ SKIP to D

SKIP to

b. How much is the regular monthly payment on all second or junior mortgages and all home equity loans on THIS property? Monthly amount – Dollars

$

,

.00

OR

□ No regular payment required

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Selected Monthly Owner Costs (Cost of Utilities, Condominium and Mobile Home Fees, Taxes, Insurance, and Mortgages)—Con.

QUESTIONS ABOUT THE USE AND COST OF COMMON UTILITIES, ANY APPLICABLE CONDOMINIUM AND MOBILE HOME FEES, TAXES, MORTGAGES, AND HOME LOANS ARE USED TO PRODUCE STATISTICS ABOUT SELECTED MONTHLY OWNER COSTS.
These data are used in government programs that analyze whether adequate housing is affordable for residents and to provide and fund housing assistance programs. These statistics are also used to enforce laws, regulations, and policies against discrimination in government programs and in society.
SELECTED MONTHLY OWNER COSTS DATA HELP COMMUNITIES:
Provide Adequate Housing
Comparing housing costs to household income (the combined income of everyone in the household) helps communities understand whether housing is affordable for residents.

When housing is not sufficient or not affordable, housing cost data can help communities enroll eligible households in programs designed to assist them, and can help communities qualify for grants from the Community Development Block Grant, HOME Investment Partnerships Program, Emergency Solutions Grants, Housing Opportunities for Persons With AIDS, and other programs.
Plan Community Development
Knowing how housing costs change over time can help communities understand changes in local housing markets and to identify opportunities to improve tax, assistance, and zoning policies.
Ensure Equal Opportunity
Knowing more about the housing costs of people who own homes in the community in combination with age, sex, race, Hispanic origin, disability, and other data about the household residents, helps government and communities enforce laws designed to eliminate discrimination in housing (Fair Housing Act of 1968).

70 Questions Planned for the 2020 Census and American Community Survey

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Sex asked since 1790.

3 What is Person 1’s sex? Mark (X) ONE box.

Male

Female

A QUESTION ABOUT THE SEX OF EACH PERSON IS USED TO CREATE STATISTICS ABOUT MALES AND FEMALES AND TO PRESENT OTHER DATA, SUCH AS OCCUPATION, BY SEX.
Data disaggregated by sex are used in planning and funding government programs and in evaluating other government programs and policies to ensure they fairly and equitably serve the needs of males and females. These statistics are also used to enforce laws, regulations, and policies against discrimination in government programs and in society.
DATA DISAGGREGATED BY SEX HELP COMMUNITIES:
Ensure Equal Opportunity
Knowing the distribution of men and women in the community in combination with information about housing, voting, language, employment, and education,

helps government and communities enforce laws, regulations, and policies against discrimination on the basis of sex. For example, sex-disaggregated data are used to enforce laws against discrimination based on sex in education programs and activities receiving federal financial assistance (Title IX of the Education Amendments of 1972).
Understand Changes
Knowing whether men and women have the same opportunities in education, employment, voting, homeownership, and many other areas is of interest to researchers, advocacy groups, and policymakers. For example, the National Science Foundation uses data disaggregated by sex to provide information on women in the science and engineering workforce, and several agencies use sex-disaggregated data to investigate whether women, including women who are military veterans, have similar employment opportunities as men.

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Supplemental Nutrition Assistance Program (SNAP)/ Food Stamps asked since 2005.

15 IN THE PAST 12 MONTHS, did you or
any member of this household receive benefits from the Food Stamp Program or SNAP (the Supplemental Nutrition Assistance Program)? Do NOT include WIC, the School Lunch Program, or assistance from food banks.
□ Yes □ No

QUESTIONS ABOUT A HOUSEHOLD’S RECEIPT OF FOOD STAMPS/ SUPPLEMENTAL NUTRITION ASSISTANCE PROGRAM (SNAP)1 ARE USED TO CREATE STATISTICS ABOUT PARTICIPATION IN FOOD ASSISTANCE PROGRAMS.
SNAP data are used in planning and funding government programs that provide food assistance and in evaluating other government programs.1
SNAP DATA HELP COMMUNITIES:
Provide Food Assistance to School Children
Knowing more about food assistance program participation in combination with school enrollment, income, and poverty status, can help communities streamline administration of the National School Lunch Program and School Breakfast Program by replacing administrative paperwork with American Community Survey estimates of students eligible for free and reduced-price meals.

Evaluate SNAP
Knowing more about food assistance program participation helps the U.S. Department of Agriculture to evaluate SNAP and award bonuses to communities that administer SNAP funds well.
Understand Changes
State and local agencies use these statistics to assess state food assistance needs and participation rates for eligible families and individuals and to determine gaps in services and programs. Faith-based and other nonprofit organizations use information about food assistance needs to determine where food banks, food kitchens, and other programs could be beneficial and how the needs of their communities can be met with additional resources and services.

1 In 2008, the food stamp program was renamed SNAP, but the question uses both program names to minimize confusion.

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Tenure (Owner/Renter) asked since 1890.

17 Is this house, apartment, or mobile home – Mark (X) ONE box.

, what was the

□

Owned by you or someone in this household with a mortgage or

loan? Include home equity loans.

□

Owned by you or someone in this household free and clear (without a

mortgage or loan)?

□ Rented?

□

Occupied without payment of
rent? ➔ SKIP to C on the next page

A QUESTION ABOUT WHETHER A HOME IS OWNED OR RENTED IS USED TO CREATE DATA ABOUT TENURE, RENTERS, AND HOMEOWNERSHIP.
Tenure is the most basic characteristic to assess housing inventory. Tenure data are used in government programs that analyze whether adequate housing is affordable for residents. Tenure data are also used to provide and fund housing assistance programs. These statistics are also used to enforce laws, regulations, and policies against discrimination in private-market housing, government programs, and in society.
TENURE DATA HELP COMMUNITIES:
Provide Adequate Housing
Knowing the different types of households in a community (single people, couples, families, roommates, etc.) and rates of home rental and ownership helps communities understand whether available housing meets the needs of residents. Data about owners and renters, in combination with housing costs and the combined income of all people in a household, help communities understand whether housing is affordable for residents.

When housing is not sufficient or not affordable, data about owners and renters can help communities enroll eligible households in programs designed to assist them, and can help communities qualify for grants from the Community Development Block Grant, HOME Investment Partnership Program, Emergency Solutions Grants, Housing Opportunities for Persons With AIDS, and other programs.
Plan Community Development
Knowing how the balance of rented homes, mortgaged homes, and homes owned free and clear changes over time can help communities understand changes in local housing markets; identify opportunities to improve tax, assistance, and zoning policies; and reduce tax revenue losses from vacant or abandoned properties. Tenure is also used in formulas that communities use to determine housing assistance funding (Fair Market Rents).
Ensure Equal Opportunity
Knowing the characteristics of people who rent and people who own homes in the community, such as age, sex, race, Hispanic origin, and disability, helps government and communities enforce laws designed to eliminate discrimination in housing (Fair Housing Act of 1968).
Understand Changing Households
Knowing whether older residents are staying in homes as they age or moving into rented homes, and whether young people are staying with parents, renting with roommates, or buying homes, can help governments and communities distribute funds appropriately between homeownership and rental housing programs and services for residents.

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Units in Structure, asked since 1940. Rooms,aaskneddsince 1940. Bedrooms asked since 1960.

1 Which best describes this building? Include all apartments, flats, etc., even if vacant.

□ A mobile home

□

A one-family house detached from any other house

□

A one-family house attached to one or more houses

□ A building with 2 apartments

□ A building with 3 or 4 apartments

□ A building with 5 to 9 apartments

□ A building with 10 to 19 apartments

□ A building with 20 to 49 apartments

□ A building with 50 or more apartments

□ Boat, RV, van, etc.

6 a. How many separate rooms are in this house, apartment, or mobile home? Rooms must be separated by built-in archways or walls that extend out at least 10 6 inches and go from floor to ceiling.
• INCLUDE bedrooms, kitchens, etc. • EXCLUDE bathrooms, porches, balconies,
foyers, halls, or unfinished basements.
Number of rooms
D
b. How many of these rooms are bedrooms? Count as bedrooms those rooms you would 11 list if this house, apartment, or mobile home were for sale or rent. If this is an efficiency/studio apartment, print "0".
Number of bedrooms
D

QUESTIONS ABOUT THE TYPE OF BUILDING, UNITS IN THE STRUCTURE, NUMBER OF ROOMS, AND NUMBER OF BEDROOMS ARE USED TO CREATE DATA ABOUT HOUSING TYPES AND HOUSING DENSITY.
These data are used in government programs that analyze whether adequate housing is available and affordable for residents, and provide and fund housing assistance programs. The number of rooms in combination with the number of people living in a unit provides a ratio of people to rooms, which can be used to measure the extent of overcrowding among our nation’s households. These statistics are also used to enforce laws, policies, and regulations against discrimination in government programs and in society.
UNITS IN STRUCTURE, ROOMS, AND BEDROOMS DATA HELP COMMUNITIES:
Provide Adequate Housing
Knowing the different types of housing, and how many people occupy that housing, helps communities understand whether available housing meets the needs of residents. For example, these data are used to measure overcrowding in communities and are used as integral components to set Fair Market Rents for all areas of the country.

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Units in Structure asked since 1940—Con. Rooms asked since 1940—Con. Bedrooms asked since 1960—Con.

When housing is not sufficient, data can help communities enroll eligible households in programs designed to assist them (such as the Low Income Home Energy Assistance Program), and can help communities qualify for grants from the Community Development Block Grant, HOME Investment Partnerships Program, Emergency Solutions Grants, Housing Opportunities for Persons With AIDS, and other programs.

These data provide benchmark statistics that measure progress toward the Congressional declaration of goals for a national housing policy—a decent home and suitable living environment for every American family.
Plan Community Development
These data are used to identify adequate housing and may be useful in identifying types of structures in disaster-prone areas during emergency planning and preparation.

78 Questions Planned for the 2020 Census and American Community Survey

U.S. Census Bureau

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Vehicles Available asked since 1960.

12 How many automobiles, vans, and trucks of one-ton capacity or less are kept at home for use by members of this household?
□ None □ 1 □ 2 □ 3 □ 4 □ 5 □ 6 or more

A QUESTION ABOUT THE VEHICLES AVAILABLE TO EACH HOUSEHOLD IS USED TO CREATE DATA ABOUT VEHICLE ACCESS.
Vehicle data are used in planning and funding for improvements to road and highway infrastructure, developing transportation plans and services, and understanding how people are traveling in the course of a normal day. These data are also used to evaluate pollution and access to transportation in emergencies.
VEHICLE AVAILABILITY DATA HELP COMMUNITIES:
Improve Transportation
Knowing how many households have access to vehicles, in combination with where people commute to and from, and whether they commute with a personal vehicle helps transportation planners create mass transportation and metropolitan plans that are compliant with various regulations.

Local agencies and organizations use these data to plan programs and services for the disabled population, bicycle commuters, carpools and ridesharers, and many other groups; and to predict future use of new or updated transportation systems based on their understanding of the current users of various transportation options.
Understand Changes in Vehicle Use
Understanding vehicle availability and use helps communities understand exposure to air pollution and plan programs to help people without vehicles move about the community. Knowing whether people could evacuate using their personal vehicles in an emergency also helps communities plan emergency response.

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Veteran Status,asked since 1890.1 Period of Military Service,aaskneddsince 1890.1 Department of Veterans Affairs (VA) Service-Connected
Disability Rating asked since 2008.

27 Has this person ever served on active duty in the U.S. Armed Forces, Reserves, or National Guard? Mark (X) ONE box.

□

Never served in the military ➔ SKIP to question 30a

□

Only on active duty for training in the Reserves or National Guard ➔ SKIP to question 29a

□ Now on active duty □ On active duty in the past, but not now

28 When did this person serve on active duty in the U.S. Armed Forces? Mark (X) a box for EACH period
in which this person served, even if just for part of the period.

□ September 2001 or later

□

August 1990 to August 2001 (including Persian Gulf War)

□ May 1975 to July 1990 □ Vietnam era (August 1964 to April 1975) □ February 1955 to July 1964 □ Korean War (July 1950 to January 1955) □ January 1947 to June 1950 □ World War II (December 1941 to December 1946) □ November 1941 or earlier

QUESTIONS ABOUT A PERSON’S MILITARY SERVICE AND SERVICECONNECTED DISABILITY RATING ARE USED TO CREATE ESTIMATES OF VETERANS AND THEIR NEEDS AT THE COMMUNITY LEVEL.
Data about veterans are used in planning and funding government programs that provide funds or services for veterans and in evaluating other government programs and policies to ensure they fairly and equitably serve the needs of veterans. These statistics are also used to enforce laws, policies, and regulations
1 Veteran status and period of service were not asked in 1920.

29 a. Does this person have a VA service-connected disability rating?

□ Yes (such as 0%, 10%, 20%, ... , 100%) □ No ➔ SKIP to question 30a

b. What is this person’s service-connected disability rating?

□ 0 percent

□ 10 or 20 percent

□ 30 or 40 percent

□ 50 or 60 percent

□ 70 percent or higher

K

against discrimination in society. Though the VA maintains veterans’ records, these statistics do not provide federal program planners, policymakers, and researchers with additional statistics about all veterans, regardless of whether they use VA services.
VETERAN STATUS, PERIOD OF SERVICE, AND VA SERVICE-CONNECTED DISABILITY RATING DATA HELP COMMUNITIES:
Administer Programs for Veterans
Knowing the numbers and characteristics of veterans eligible for federal programs benefiting veterans, such as the VA Home Loan Guarantee program, the Post9/11 GI Bill, and job training and hiring preference programs can help communities and the federal government estimate the future demand for these programs and services. These data are also used to evaluate these programs to determine whether they are benefiting veterans as intended.
Provide Health Care for Veterans
Knowing the number of veterans eligible to use VA health care in combination with age, disability, and service-connected disability ratings, can help communities and the federal government estimate

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Veteran Status asked since 1890—Con. Period of Military Service asked since 1890—Con. Department of Veterans Affairs (VA) Service-Connected
Disability Rating asked since 2008—Con.

the future demand for health care services and facilities. Communities in need of major VA medical facilities throughout the country make a case for new construction projects using these data to estimate the expected usage of new facilities.
Plan End-of-Life Options for Veterans
Knowing where veterans are living toward the end of their lives is important, as the VA estimates the number of nursing home and domiciliary beds needed based on the concentrations of eligible veterans over age 65. These data are also important for the VA National Cemetery Administration, whose goal is to have a VA burial option within 75 miles of a veteran’s residence. These data are used to plan construction of new cemeteries near the communities where veterans choose to live.

Ensure Equal Opportunity
Knowing the veteran and service-connected disability rating status of people in the community in combination with information about housing, voting, employment, and education, helps government and communities enforce against discrimination based on veteran or disability status.
Understand New Challenges for Veterans
Knowing more about the characteristics of veterans returning to civilian life is also important to combat specific problems they may face. For example, these data are used in research to understand why veteran status is a predictor of homelessness. Such data have been combined with administrative data produced by shelters in an attempt to understand and document which interventions reduce homelessness among veterans.

82 Questions Planned for the 2020 Census and American Community Survey

U.S. Census Bureau

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Work Status Last Year asked since 1880.

• When did this person last work, even for a few days?
D Within the past 12 months
D 1 to 5 years ago ➔ SKIPto M
D Over 5 years ago or never worked ➔ SKIPto
question 43
' I a. During the PAST 12 MONTHS (52 weeks), did this person work EVERY week? Count paid vacation, paid sick leave, and military service as work.
D Yes ➔ SKIPto question 41 0 No
b. During the PAST 12 MONTHS (52 weeks), how many WEEKS did this person work? Include paid time off and include weeks when the person only worked for a few hours.
Weeks
[J
During the PAST 12 MONTHS, in the WEEKS WORKED, how many hours did this person usually work each WEEK?
Usual hours worked each WEEK
CJ
QUESTIONS ABOUT HOW MANY WEEKS A PERSON WORKED IN THE LAST YEAR AND HOW MANY HOURS HE OR SHE WORKED EACH WEEK ARE USED TO PRODUCE STATISTICS ABOUT FULL-TIME AND PART-TIME WORKERS, AS WELL AS YEAR-ROUND AND SEASONAL WORKERS.

Data on work status last year are used in planning and funding government programs that provide unemployment assistance and services, and to understand trends and difference in wages, benefits, work hours, and seasonal work. These data are also used to evaluate other government programs and policies to ensure they fairly and equitably serve the needs of all groups, and to enforce laws, regulations, and policies against discrimination in society.
WORK STATUS LAST YEAR DATA HELP COMMUNITIES:
Provide Employment Opportunities
Knowing whether programs designed to employ specific groups, such as people with disabilities or veterans, are succeeding is important to employers, federal agencies, and federal government contractors (Vietnam Era Veterans’ Readjustment Assistance Act, Rehabilitation Act of 1973).
State and local agencies use these statistics to identify labor surplus areas (areas with people available for hiring and training), plan workforce development programs including job fairs and training programs, and promote business opportunities.
Ensure Equal Opportunity
Knowing more about people who are employed or looking for work, in combination with age, sex, race, Hispanic origin, disability status, veteran status, and other data, helps governments and communities enforce laws, policies, and regulations against discrimination in employment. For example, data on work status last year are used to enforce laws against discrimination in employment by federal agencies, private employers, employment agencies, and labor organizations (Civil Rights Act of 1964).
Understand Changes
Knowing the characteristics of people who are working or looking for work is an important part of estimating changes in the economy. Estimates of work status last year are used in funding decisions; to ensure surveys are accurate, including surveys that provide official labor market estimates; and to understand change in other data (Wagner-Peyser Act and Workforce Investment Act).

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Year Built aasnkedd since 1940. Year Moved In asked since 1960.

Spe/ About when was this building first built?
D 2000 or later -

I

I

□ 1990 to 1999 □ 1980 to 1989 □ 1970 to 1979 □ 1960 to 1969 □ 1950 to 1959 □ 1940 to 1949 □ 1939 or earlier

When did PERSON 1 (listed on page 2) move into thi s hou se, apartment, or mobile home?

[]~I Month

Year
~

QUESTIONS ABOUT WHEN A BUILDING WAS BUILT AND WHEN A PERSON MOVED INTO THAT HOME ARE USED TO CREATE DATA ABOUT HOUSING AGE AND AVAILABILITY.
These data are used in government programs that analyze whether adequate housing is available and affordable for residents, provide and fund housing assistance programs, and measure neighborhood stability.

YEAR BUILT AND YEAR MOVED IN DATA HELP COMMUNITIES:
Provide Adequate Housing
Knowing the ages of housing in a community helps communities understand whether available housing meets the needs of residents.
When housing is not sufficient or older than a certain age, housing data can help communities enroll eligible households in programs designed to assist them (such as the Low Income Home Energy Assistance Program), and can help communities qualify for grants from the Community Development Block Grant, HOME Investment Partnerships Program, Emergency Solutions Grants, Housing Opportunities for Persons With AIDS, and other programs.
Plan Community Development
Knowing how the balance of different ages of homes in combination with whether they are occupied or vacant, can help communities identify opportunities to improve tax, assistance, and zoning policies and to reduce tax revenue losses from vacant or abandoned properties. These data may also be useful in identifying older structures in disaster-prone areas during emergency planning and preparation.
Knowing more about the age of the housing stock in combination with the financial situation of residents, including income, employment, and housing costs, can help communities qualify for loan and grant programs designed to stimulate economic recovery, improve housing, run job-training programs, and define areas as empowerment or enterprise zones.

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Operational Questions for use in the American Community Survey.

C) Please print today's date.

Month

Day

Year

□ DI~

C) Please print the name and telephone number of the person who is filling out this form. We will only contact you if needed for official Census Bureau business.
Last Name

First Name
Area Code + Number
CJ CJ

Ml
J
.____I____,

C) How many people are living or staying at this address?
• INCLUDE everyone who is living or staying here for more than 2 months . • INCLUDE yourself if you are living here for more than 2 months. • INCLUDE anyone else staying here who does not have another place to
stay, even if they are here for 2 months or less. • DO NOT INCLUDE anyone who is living somewhere else for more than
2 months, such as a college student living away or someone in the Armed Forces on deployment.
Number of people
D

What is Person 1 's name?

Last Name (Please print)

First Name

Ml

J

MEETING FEDERAL NEEDS
Some operational questions will appear on the 2020 ACS that will not result in published estimates. These questions are asked to better administer the data collection process, ensure response accuracy and completeness, and for contacting respondents

with incomplete or missing information. Contact information is not part of published estimates and is carefully protected, as mandated by federal law, to protect the personal information of respondents.

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Appendix A: Year the Planned Questions Were First Asked in the Decennial Census Program

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Year the Planned Questions Were First Asked in the Decennial Census Program

Questions Planned for 2020 Census and/or ACS
Acreage Age Agricultural Sales Ancestry Bedrooms Citizenship Class of Worker Commuting (Journey to Work) Computer and Internet Use Condominium and Mobile Home Fees Cost of Utilities Department of Veterans Affairs (VA) Service-Connected
Disability Rating Disability Educational Attainment Fertility Grandparent Caregivers Health Insurance Coverage Health Insurance Premiums and Subsidies Hispanic Origin Home Heating Fuel Home Value and Rent Income Industry Insurance Kitchen Facilities Labor Force Status Language Spoken at Home Marital History Marital Status Migration Mortgages Occupation Period of Military Service Place of Birth Plumbing Facilities Race Relationship Rooms

Year Question First Asked in Decennial Census or ACS 1960 1790 1960 1980 1960 1820 1910 1960 2013 1990 1940 2008
1830 1940 1890 2000 2008 2019 1970 1940 1940 1940 1820 1980 1940 1890 1890 1850 1880 1930 1940 1850 1890 1850 1940 1790 1880 1940

Years Not Asked 1840–1860, 1880
1830, 1850–1900 1950
1950–1970 1920

U.S. Census Bureau

Questions Planned for the 2020 Census and American Community Survey A3

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Year Current Questions Planned First Asked in Decennial Census Program—Con.

Questions Planned for 2020 Census and/or ACS
School Enrollment Sex Supplemental Nutrition Assistance Program (SNAP)/
Food Stamps Taxes Telephone Service Tenure (Owner/Renter) Undergraduate Field of Degree Units in Structure Vehicles Veteran Status Work Status Last Year Year Built Year Moved In Year of Entry

Year Question First Asked in Decennial Census or ACS 1850 1790 2005
1940 1960 1890 2009 1940 1960 1890 1880 1940 1960 1890

Years Not Asked 1950–1970 1920 1940–1960

A4 Questions Planned for the 2020 Census and American Community Survey

U.S. Census Bureau

Case 1:18-cv-02711-DLF Document 8-4 Filed 01/18/19 Page 107 of 178
Exhibit 3

Case 1:18-cv-02711-DLF Document 8-4 Filed 01/18/19 Page 108 of 178
L. Sweeney, Simple Demographics Often Identify People Uniquely. Carnegie Mellon University, Data Privacy Working Paper 3. Pittsburgh 2000.
Simple Demographics Often Identify People Uniquely
Latanya Sweeney
Carnegie Mellon University latanya@andrew.cmu.edu

This work was funded in part by H. John Heinz III School of Public Policy and Management at Carnegie Mellon University and by a grant from the U.S. Bureau of Census.
Copyright © 2000 by Latanya Sweeney. All rights reserved.

Sweeney

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L. Sweeney, Simple Demographics Often Identify People Uniquely. Carnegie Mellon University, Data Privacy Working Paper 3. Pittsburgh 2000.
1. Abstract
In this document, I report on experiments I conducted using 1990 U.S. Census summary data to determine how many individuals within geographically situated populations had combinations of demographic values that occurred infrequently. It was found that combinations of few characteristics often combine in populations to uniquely or nearly uniquely identify some individuals. Clearly, data released containing such information about these individuals should not be considered anonymous. Yet, health and other person-specific data are publicly available in this form. Here are some surprising results using only three fields of information, even though typical data releases contain many more fields. It was found that 87% (216 million of 248 million) of the population in the United States had reported characteristics that likely made them unique based only on {5-digit ZIP, gender, date of birth}. About half of the U.S. population (132 million of 248 million or 53%) are likely to be uniquely identified by only {place, gender, date of birth}, where place is basically the city, town, or municipality in which the person resides. And even at the county level, {county, gender, date of birth} are likely to uniquely identify 18% of the U.S. population. In general, few characteristics are needed to uniquely identify a person.
2. Introduction
Data holders often collect person-specific data and then release derivatives of collected data on a public or semi-public basis after removing all explicit identifiers, such as name, address and phone number. Evidence is provided in this document that this practice of de-identifying data and of ad hoc generalization are not sufficient to render data anonymous because combinations of attributes often combine uniquely to re-identify individuals.
2.1. Linking to re-identify de-identified data
In this subsection, I will demonstrate how linking can be used to re-identify de-identified data. The National Association of Health Data Organizations (NAHDO) reported that 44 states have legislative mandates to collect hospital level data and that 17 states have started collecting ambulatory care data from hospitals, physicians offices, clinics, and so forth [1]. These data collections often include the patient’s ZIP code, birth date, gender, and ethnicity but no explicit identifiers like name or address. The leftmost circle in Figure 1 contains some of the data elements collected and shared.
For twenty dollars I purchased the voter registration list for Cambridge Massachusetts and received the information on two diskettes [2]. The rightmost circle in Figure 1 shows that these data included the name, address, ZIP code, birth date, and gender of each voter. This information can be linked using ZIP, birth date and gender to the medical information, thereby linking diagnosis, procedures, and medications to particularly named individuals. The question that remains of course is how unique would such linking be.
In general I can say that the greater the number and detail of attributes reported about an entity, the more likely that those attributes combine uniquely to identify the entity. For example, in the voter list, there were 2 possible values for gender and 5 possible five-digit ZIP codes; birth dates were within a range of 365 days for 100 years. This gives 365,000 unique values, but there were only 54,805 voters.

Sweeney

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L. Sweeney, Simple Demographics Often Identify People Uniquely. Carnegie Mellon University, Data Privacy Working Paper 3. Pittsburgh 2000.

Ethnicity

Visit date Diagnosis Procedure Medication

ZIP
Birth date
Sex

Name
Address
Date registered
Party affiliation

Total charge Medical Data

Date last voted Voter List

Figure 1 Linking to re-identify data

2.2. Publicly and semi-publicly available health data

As mentioned in the previous subsection, most states (44 of 50 or 88%) collect hospital discharge data [3]. Many of these states have subsequently distributed copies of these data to researchers, sold copies to industry and made versions publicly available. While there are many possible sources of patient-specific data, these represent a class of data collections that are often publicly and semi-publicly available.

# Field description Size 1 HOSPITAL ID NUMBER 12 2 PATIENT DATE OF BIRTH (MMDDYYYY) 8 3 SEX 1 4 ADMIT DATE (MMDYYYY) 8 5 DISCHARGE DATE (MMDDYYYY) 8 6 ADMIT SOURCE 1 7 ADMIT TYPE 1 8 LENGTH OF STAY (DAYS) 4 9 PATIENT STATUS 2 10 PRINCIPAL DIAGNOSIS CODE 6 11 SECONDARY DIAGNOSIS CODE - 1 6 12 SECONDARY DIAGNOSIS CODE - 2 6 13 SECONDARY DIAGNOSIS CODE - 3 6 14 SECONDARY DIAGNOSIS CODE - 4 6 15 SECONDARY DIAGNOSIS CODE - 5 6 16 SECONDARY DIAGNOSIS CODE - 6 6 17 SECONDARY DIAGNOSIS CODE - 7 6 18 SECONDARY DIAGNOSIS CODE - 8 6 19 PRINCIPAL PROCEDURE CODE 7 20 SECONDARY PROCEDURE CODE - 1 7 21 SECONDARY PROCEDURE CODE - 2 7 22 SECONDARY PROCEDURE CODE - 3 7 23 SECONDARY PROCEDURE CODE - 4 7 24 SECONDARY PROCEDURE CODE - 5 7 25 DRG CODE 3

# Field description Size 26 MDC CODE 2 27 TOTAL CHARGES 9 28 ROOM AND BOARD CHARGES 9 29 ANCILLARY CHARGES 9 30 ANESTHESIOLOGY CHARGES 9 31 PHARMACY CHARGES 9 32 RADIOLOGY CHARGES 9 33 CLINICAL LAB CHARGES 9 34 LABOR-DELIVERY CHARGES 9 35 OPERATING ROOM CHARGES 9 36 ONCOLOGY CHARGES 9 37 OTHER CHARGES 9 38 NEWBORN INDICATOR 1 39 PAYER ID 1 9 40 TYPE CODE 1 1 41 PAYER ID 2 9 42 TYPE CODE 2 1 43 PAYER ID 3 9 44 TYPE CODE 3 1 45 PATIENT ZIP CODE 5 46 Patient Origin COUNTY 3 47 Patient Origin PLANNING AREA 3 48 Patient Origin HSA 2 49 PATIENT CONTROL NUMBER 50 HOSPITAL HSA 2

Figure 2 IHCCCC Research Health Data

The Illinois Health Care Cost Containment Council (IHCCCC) is the organization in the State of Illinois that collects and disseminates health care cost data on hospital visits in Illinois. IHCCCC reports more than 97% compliance by Illinois hospitals in providing the information

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L. Sweeney, Simple Demographics Often Identify People Uniquely. Carnegie Mellon University, Data Privacy Working Paper 3. Pittsburgh 2000.

[4]. Figure 2 contains a sample of the kinds of fields of information that are not only collected, but also disseminated.

Of the states mentioned in the NAHDO report, 22 of these states contribute to a national database called the State Inpatient Database (SID) sponsored by the Agency for Healthcare Research and Quality (AHRQ). A copy of each patient’s hospital visit in these states is sent to AHRQ for inclusion in SID. Some of the fields provided in SID are listed in Figure 3 along with the compliance of the 13 states that contributed to SID’s 1997 data [5].

Field
Patient Age Patient Date of birth Patient Gender Patient Racial background Patient ZIP Patient ID Admission date Admission day of week Admission source Birth weight Discharge date Length of stay Discharge status Diagnosis Codes Procedure Codes Hospital ID Hospital county Primary payer Charges

Comments years month, year
5-digit encrypted (or scrambled) month, year
emergency, court/law, etc for newborns month, year
routine, death, nursing home, etc ICD9, from 10 to30 from 6 to 21 AHA#
Medicare, insurance, self-pay, etc from 1 to 63 categories

#states
13 5
13 11
9 3 8 12 13 5 7 13 13 13 13 12 12 13 11

%states
100% 38%
100% 85% 69% 23% 62% 92%
100% 38% 54%
100% 100% 100% 100%
92% 92% 100% 85%

Figure 3 Some data elements for AHRQ’s State Inpatient Database (13 participating states)

State

Month and Year of Birth date

Age

Arizona

Yes

Yes

California

Yes

Colorado

Yes

Florida

Yes

Iowa

Yes

Yes

Massachusetts

Yes

Maryland

Yes

New Jersey

Yes

New York

Yes

Yes

Oregon

Yes

Yes

South Carolina

Yes

Washington

Yes

Wisconsin

Yes

Yes

Figure 4 Age information provided by states to SID

Figure 4 lists the states reported in Figure 3 that provide the month and year of birth and the age for each patient.

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L. Sweeney, Simple Demographics Often Identify People Uniquely. Carnegie Mellon University, Data Privacy Working Paper 3. Pittsburgh 2000.
The remainder of this document provides experimental results from summary data that show how demographics often combine to make individuals unique or almost unique in data like these.
2.3. A single attribute

The frequency with which a single characteristic occurs in a population can help identify individuals based on unusual or outlying information. Consider a frequency distribution of birth years found in the list of registered voters. It is not surprising to see fewer people present with earlier birth years. Clearly, a person born in 1900 is unusual and by implication less anonymous in data.
2.4. More than one attribute

What may be more surprising is that combinations of characteristics can combine to occur even less frequently than the characteristics appear alone.
ZIP Birth Gender Race 60602 7/15/54 m Caucasian 60140 2/18/49 f Black
I62052 I3/12/50 I f IAsian
Figure 5 Data that looks anonymous

Consider Figure 5. If the three records shown were part of a large and diverse database of information about Illinois residents, then it may appear reasonable to assume that these three records would be anonymous. However, the 1990 federal census [6] reports that the ZIP (postal code) 60602 consisted primarily of a retirement community in the Near West Side of Chicago and therefore, there were very few people (less than 12) of an age under 65 living there. The ZIP code 60140 is the postal code for Hampshire, Illinois in Dekalb county and reportedly there were only two black women who resided in that town. Likewise, 62052 had only four Asian families. In each of these cases, the uniqueness of the combinations of characteristics found could help reidentify these individuals.

Race Black Black Black Black Black Black White White White White White White

Birth 09/20/65 02/14/65 10/23/65 08/24/65 11/07/64 12/01/64 10/23/64 03/15/65 08/13/64 05/05/64 02/13/67 03/21/67

Gender ZIP Problem m 02141 short of breath m 02141 chest pain f 02138 hypertension f 02138 hypertension f 02138 obesity f 02138 chest pain m 02138 chest pain f 02139 hypertension m 02139 obesity m 02139 short of breath m 02138 chest pain m 02138 chest pain

Figure 6 De-identified data

Sweeney

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L. Sweeney, Simple Demographics Often Identify People Uniquely. Carnegie Mellon University, Data Privacy Working Paper 3. Pittsburgh 2000.
As another example, Figure 6 contains de-identified data. Each row contains information about a distinct person, so information about 12 people is reported. The table contains the following fields of information {Race/Ethnicity, Date of Birth, Gender, ZIP, Medical Problem}.
In Figure 6, there is information about an equal number of African Americans (listed as Black) as there are Caucasian Americans (listed as White) and an equal number of men (listed as m) as there are women (listed as f), but in combination, there appears only one Caucasian female.
2.5. Learned from the examples
These examples demonstrate that in general, the frequency distributions of combinations of characteristics have to be examined in combination with respect to the entire population in order to determine unusual values and cannot be generally predicted from the distributions of the characteristics individually. Of course, obvious predictions can be made from extreme distributions --such as values that do not appear in the data will not appear in combination either.
3. Background of definitions and terms
Definition (informal). Person-specific data Collections of information whose granularity of details are specific to an individual are termed person-specific data. More generally, in entity-specific data, the granularity of details is specific to an entity.
Example. Person-specific data
Figure 5 and Figure 6 provide examples of person-specific data. Each row of these tables contains information related to one person.
The idea of anonymous data is a simple one. The term "anonymous" means that the data cannot be linked or manipulated to confidently identify the individual who is the subject of the data.
Definition (informal). Anonymous data Anonymous data implies that the data cannot be manipulated or linked to confidently identify the entity that is the subject of the data.
Most people understand that there exist explicit identifiers, such as name and address, which can provide a direct means to communicate with the person. I term these explicit identifiers; see the informal definition below.
Definition (informal). Explicit identifier An explicit identifier is a set of data elements, such as {name, address} or {name, phone number}, for which there exists a direct communication method, such as email, telephone, postal mail, etc., where with no additional information, the designated person could be directly and uniquely contacted.
A common incorrect belief is that removing all explicit identifiers such as name, address and phone number from the data renders the result anonymous. I refer to this instead as deidentified data; see the informal definition below.

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Definition (informal). De-identified data De-identified data result when all explicit identifiers, such as name, address, or phone number are removed, generalized or replaced with a made-up alternative.
Example. De-identified data
Figure 5 and Figure 6 provide examples of de-identified person-specific data. There are no explicit identifiers in these data.
Because a combination of characteristics can combine uniquely for an individual, it can provide a means of recognizing a person and therefore serve as an identifier. In the literature, such combinations were nominally introduced as quasi-identifiers [7] and identificates [3-58] with no supporting evidence provided as to how identifying specific combinations might be. Extending beyond the literature and its casual use in the literature, I term such a combination a quasi-identifier and informally define it below. I then examine specific quasi-identifiers found within publicly and semi-publicly available data and compute their general ability to uniquely associate with particular persons in the U.S. population.
Definition (informal). Quasi-identifier A quasi-identifier is a set of data elements in entity-specific data that in combination associates uniquely or almost uniquely to an entity and therefore can serve as a means of directly or indirectly recognizing the specific entity that is the subject of the data.
Example. Quasi-identifier
A quasi-identifier whose values are unique for all the records in Figure 6 is {ZIP, gender, Birth}.
In the next section, I will show that {ZIP, gender, Birth} is a unique quasi-identifier for most people in the U.S. population.
The term table is really quite simple and is synonymous with the casual use of the term data collection. It refers to data that are conceptually organized as a 2-dimensional array of rows (or records) and columns (or fields). A database is considered to be a set of one or more tables.
Definition (informal). Table, tuple and attribute A table conceptually organizes data as a 2-dimensional array of rows (or records) and columns (or fields). Each row (or record) is termed a tuple. A tuple contains a relationship among the set of values associated with an entity. Tuples within a table are not necessarily unique. Each column (also known as a field or data element) is called an attribute and denotes a field or semantic category of information that is a set of possible values; therefore, an attribute is also a domain. Attributes within a table are unique. So by observing a table, each row is an ordered n-tuple of values <d1, d2, …, dn> such that each value dj is in the domain of the j-th column, for j=1, 2, …, n where n is the number of columns.
In mathematical set theory, a relation corresponds with this tabular presentation; the only difference is the absence of column names. Ullman provides a detailed discussion of relational database concepts [9].

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Examples of tables
Figure 5 provides an example of a person-specific table with attributes {ZIP, Birth, Gender, Race}. Each tuple concerns information about a single person. Figure 6 provides an example of a person-specific table with attributes {Race, Birth, Gender, ZIP, Problem}.
Unfortunately, the terminology with respect to data collections is not the same across communities and diverse communities have an interest in this work. In order to accommodate these different vocabularies, I provide the following thesaurus of interchangeable terms. In general, data collection, data set and table refer to the same representation of information though a data collection may have more than one table. The terms record, row and tuple all refer to same kind of information. Finally, the terms data element, field, column and attribute refer to the same kind of information. For brevity, from this point forward, I will use the more formal database terms of table, tuple and attribute. I do allow the tuples of a table to appear in a “sorted” order on occasion and such cases pose a slight deviation from its more formal meaning. These uses are explicitly noted.
4. Methods
4.1. Census Tables
Information from the 1990 US Census made available on the Web [10] and on CDROM [11] and from the U.S. Postal Service [12] was loaded into Microsoft Access and the following tables produced and used with Microsoft Excel.
1. ZIP census table provides 1990 federal census information summarized by each ZIP (postal code) in the United States.
2. Place census table provides 1990 federal census information summarized by place name (town, city, municipality, or postal facility name).
3. County census table provides 1990 federal census information summarized by US counties.
Figure 7 contains a list of attributes (or data elements) for each of these tables. The name and description of each attribute is listed and a “yes” appears in the column that associates the attribute to the ZIP, Place or County table in which the attribute appears. Information for all 50 states and the District of Columbia were provided. For example, values associated with the attribute Tot_pop in the ZIP table are the total numbers of individuals reported as living in each corresponding ZIP. Each tuple (or row) in the table corresponds to a unique ZIP.
Given a particular geographical specification such as ZIP, place or county, the number of people reported as residing in the noted geographical area is reported by age subdivision in the ZIP, Place and County tables. The age subdivisions are: under 12 years of age (denoted as Aunder12), between 12 and 18 years of age (denoted as A12to18), between 19 and 24 years of age (denoted as A19to24), between 25 and 34 years of age (denoted as A25to34), between 35 and 44 years of age (denoted as A35to44), between 45 and 54 years of age (denoted as A45to54),

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between 55 and 64 years of age (denoted as A55to64) or more than 65 years of age (denoted as A65Plus).

Field
StateID ZIP Place CoName Tot_Pop AUnder12 A12to18 A19to24 A25to34 A35to44 A45to54 A55to64 A65Plus

Description
State Code 5-digit ZIP Name of Incorporated Place County Name Total Population Population Under Age 12 Years Population Age 12-18 Years Population Age 19-24 Years Population Age 25-34 Years Population Age 35-44 Years Population Age 45-54 Years Population Age 55-64 Years Population Age 65 Years and up

ZIP PLACE COUNTY

yes yes

yes

yes NO

NO

NO yes

NO

NO NO

yes

yes yes

yes

yes yes

yes

yes yes

yes

yes yes

yes

yes yes

yes

yes yes

yes

yes yes

yes

yes yes

yes

yes yes

yes

Figure 7 1990 Census attributes in ZIP, Place, County tables

4.2. ZIPNameGIS Table

ZIP information provided from the U.S. Postal Service included place, which is a name of a town, city, municipality or postal facility uniquely assigned to a ZIP code. This information was loaded directly to provide the ZIPNameGIS table. The attributes (or data elements) for the ZIPNameGIS table are {StateID, ZIP, State, POName, longitude, latitude, population}.
The Place table was constructed by linking the ZIP table to the ZIPNameGIS table on ZIP. Results were then grouped by POName (respecting state designations) so that population information from multiple ZIP codes were grouped together by the city or town in which the ZIP code referred. Finally, the Place table was generated by collapsing these groupings into single entries that contained the sum of the population values reported for all ZIP codes corresponding to the same place.
During the process, 3 ZIP codes were found to cross state lines and therefore, be listed in two states. To avoid this duplication, the following assignments were made: (1) ZIP code 32530 refers to Pinetta in both Florida and Georgia. The Georgia entry was removed from Place; (2) ZIP code 42223 refers to Fort Campbell in both Kentucky and Tennessee. The Tennessee entry was removed from Place; and, (3) ZIP code 63673 refers to Saint Mary in both Illinois and Missouri. The Missouri entry was removed from Place.
4.2.1. Schemas of shared data

Figure 2 and Figure 3 contain descriptions of publicly and semi-publicly available hospital discharge data. Below are some quasi-identifiers found in those data that also appear in the census data. The experiments reported in this document estimate the uniqueness of values associated with these quasi-identifiers given the occurrences reported in the census data.
1. Illinois Research Health Data. The Illinois Research Health Data (Rrod) is described in Figure 2. Among the attributes listed there, I consider QIrod = {date of birth, gender, 5-digit ZIP} to be a quasi-identifier within Rrod.

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2. AHRQ’s State Inpatient Database The Agency for Healthcare Research and Quality’s State Inpatient Database (RSID) is described in part in Figure 3. Among the attributes listed there, I consider QISID1 = {month and year of birth, gender, 5-digit ZIP} to be a quasi-identifier within data released by some states and I consider QISID2 = {age, gender, 5-digit ZIP} to be a quasi-identifier within data released by other states.
4.3. Design and procedures
The experiments reported in the next section can be generally described in terms of values attributes can assume. Let T(A1,…,An) be an entity-specific table and let QT be a quasiidentifier of T. QT is represented as a finite set of attributes {Ai,…,Aj} ⊆ {A1,…,An}. I write |Am| to represent the finite number of values Am can assume. So, the number of distinct possible values that be assigned to QT, written |QT|, is: |QT| = |Ai| * |Ai+1| * … * |Aj| .
Example. Given Qdob={date of birth, gender}, then |Qdob| = 365 * 76 * 2 = 55,480 because there are 365 days in a year, an expected lifetime of 76 years, and 2 genders.
In this document, I am concerned with a person-specific table T(A1,…,Z,…,An) that includes a geographic attribute Z. Values assigned to a geographic attribute are specific to the residences of people. Examples of geographic attributes include 5-digit ZIP codes, names of cities and towns, and names of counties in which people reside. Let U be the universe of all people and the person-specific table Geo[zi, Ar, …, As) contain all or almost all of the people of U having Z=zi. I say Geozi is a population register for zi. And, T[A1,…Zi,…An] is a pseudo-random sample drawn from Geo[zi, Ar, …, As]. Unique and unusual combinations of characteristics found in Geo with respect to zi can be no less unique or unusual when recorded in T. Therefore, the probability distribution of combinations of characteristics found in Geo limits the values those combinations of characteristics can assume in T. Determining unique and unusual combinations of characteristics within a residential domain is a counting problem.
Theorem. Generalized Dirichlet drawer principle [13] (also known as the Generalized pigeonhole principle)
If N objects are distributed in k boxes, then there is at least one box containing at least ⎡N / k⎤ objects.
Proof. Suppose that none of the boxes contain more than ⎡N / k⎤ -1 objects. Then, the total number of objects is at most: k *( ⎡N / k⎤ -1) < k *( ((N / k) + 1) -1) = N This has the inequality ⎡N / k⎤ < (N / k) + 1 This is a contradiction because there are a total of N objects.
Example. Given a random sample of 500 people, there are at least ⎡500 / 365⎤ = 2 people with the same birthday because there are 365 possible birthdays.

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Let zi be a 5-digit ZIP code. I write population(zi) to denote the number of people who reside in zi and population(zi) ≡ |Geozi|. If population(Zi) > |Qdob|, then by the generalized pigeonhole principle, a tuple t∈Rrod[date of birth, gender, zi] would not uniquely correspond to one person. In these cases, I say t[A1, …, date of birth, gender, zi, …, An] is not likely to be uniquely identifiable. On the other hand, if population(zi) ≤ |Qdob| then by the generalized pigeonhole principle, a tuple t∈Rrod[date of birth, gender, zi] would likely relate to only one person. In these cases, I say t[A1, …, date of birth, gender, zi, …, An] is likely to be uniquely identifiable. This is the general approach to the experiments reported in the next section though each differs in terms of attribute specification.
4.3.1. Subdivision analyses
The analyses of the identifiability of geographically situated populations are based on age-based divisions within a geographic attribute. Let age subdivision a be either Aunder12, A12to18, A19to24, A25to34, A35to44, A45to54, A55to64, or A65Plus. The quasi-identifier Qa has the same attributes as Qdob but values which date of birth can assume are limited by a. That is, |Qa| is the number of possible distinct values that can be assigned to Qa. I say |Qa| is the threshold for Qdob with respect to age subdivision a.
Example. Given Qdob={date of birth, gender} and age subdivision a = A19to24, then |Qa| = 365 * 2 * 6 = 4380 because there are 365 birthdays, 2 genders and 6 years between the ages of 19 to 24, inclusive.

Number of subjects uniquely identified in a subdivision of a geographical area (IDaZi)

Given a value for a geographic attribute, written zi, and an age subdivision a, I write population(zi, a) as the number of people residing in zi with an age within a. The number of people considered uniquely identified by a and Zi, written IDaZi, is determined by the rule:
if population(zi, a) ≥ |Qa|, then IDaZi= population(zi, a) else IDaZi = 0.

By extension, the percentage of people residing in zi considered uniquely identified (written IDzi) with respect to the set of age subdivisions is computed as:

∑ A65Plus

population(zi ) −

IDaZi

IDZi =

a= AUnder12
population(zi )

4.3.2. Statistics on geographical areas

Statistics are reported on geographic regions. Given a geographic attribute Z, let RegionZ = {zi | zi ∈ Z } and AgeDivs = {Aunder12, A12to18, A19to24, A25to34, A35to44, A45to54,
A55to64, A65Plus}. That is, RegionZ is a set of values that can be assigned to the geographic

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attribute Z and AgeDivs is a set of age subdivisions. RegionZ is partitioned into NotIDSet and IDSet based on age subdivision a∈AgeDivs such that:
NotIDSetZa = {(zi,a) | zi ∈ RegionZ and population(zi, a) > |Qa| } IDSetZa = {(zi,a) | zi ∈ RegionZ and population(zi, a) ≤ |Qa| }
The population of NotIDSetZ is not considered uniquely identifiable by values of Qdob. The population of IDSetZ is considered uniquely identifiable by values of Qdob. In the experiments, the following statistics are reported.

Maximum subpopulation(NotIDSetZa) = max(population(z1, a), …, population(zy, a) ), where (zi,a)∈NotIDSetZa

Maximum subpopulation(IDSetZa) = max(population(z1, a), …, population(zy, a) ), where (zi,a)∈IDSetZa

Minimum subpopulation(NotIDSetZa) = min(population(z1, a), …, population(zy, a) ), where (zi,a)∈NotIDSetZa

Minimum subpopulation(IDSetZa) = min(population(z1, a), …, population(zy, a) ), where (zi,a)∈IDSetZa

∑ population(zi , a)

( ) Average

subpopulation NotIDSet Za

= ( zi ,a)∈NotIDSet NotIDSet Za

∑ population(zi , a)

( ) Average

subpopulation IDSet Za

= ( zi ,a)∈IDSet IDSet Za

Number of geographical areas(NotIDSetZa ) = NOTIDSetZa

Number of geographical areas(IDSetZa ) = IDSetZa

I I Percentage of

geographical

areas(NotIDSet Za ) =

NotIDSet Za NotIDSet Za + IDSet Za

I I Percentage of

geographical areas(IDSet Za ) =

IDSet Za NotIDSet Za + IDSet Za

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State
AL AK AZ AR CA CO CT DE DC FL GA HI ID IL IN IA KS KY LA ME MD MA MI MN MS

4,040,587 544,698
3,665,228 2,350,725 29,755,274 3,293,771 3,287,116
666,168 606,900 12,686,788 6,478,847 1,108,229 1,006,749 11,429,942 5,543,954 2,776,442 2,474,885 3,673,969 4,219,973 1,226,626 4,771,143 6,011,978 9,295,222 4,370,288 2,573,216

AUnder12
699,554 123,789 678,439 410,665 5,436,303 599,278 517,724 113,963
80,760 1,931,088 1,171,969
195,278 207,979 2,012,780 975,582 487,879 457,755 626,236 836,481 210,082 812,147 933,306 1,671,777 815,963 495,074

A12to18
425,425 53,662
352,557 246,486 2,722,076 305,595 275,158
58,980 45,404 1,041,486 659,386 98,594 115,708 1,102,499 568,654 271,630 236,911 383,356 458,677 117,015 409,957 506,033 930,841 409,705 298,599

A19to24
369,639 46,478
333,055 197,424 2,904,739 282,268 295,271
64,726 71,605 1,010,156 623,625 104,537 81,770 1,021,458 510,374 240,359 216,092 337,585 387,821 104,754 431,840 613,116 850,016 377,084 240,546

A25to34
652,466 111,790 639,702 361,268 5,738,645 617,333 588,185 119,782 122,777 2,102,614 1,182,367 203,466 154,087 2,003,217 919,924 430,947 416,003 610,721 710,773 205,713 901,956 1,104,645 1,583,364 783,562 403,754

A35to44
585,299 101,699 530,192 328,397 4,645,553 570,797 509,760 100,110
94,984 1,778,994 1,014,579
178,406 149,338 1,702,509 819,577 397,287 363,571 549,204 606,119 194,139 774,414 914,852 1,408,199 666,480 351,197

A45to54
422,565 55,887
354,711 244,096 2,955,455 340,276 360,488
68,367 62,648 1,283,728 678,987 109,493 98,910 1,179,345 572,585 272,959 234,451 380,791 412,186 123,745 528,246 605,951 950,316 428,315 249,684

Figure 8 Population by state and age group, part 1

A55to64
363,033 29,236
299,372 212,573 2,231,171 249,924 294,866
59,570 51,050 1,235,820 495,259 93,778 77,819 974,035 481,329 249,594 208,146 320,712 340,483 108,198 395,946 514,398 793,711 343,315 213,117

A65Plus
522,606 22,157
477,200 349,816 3,121,332 328,300 445,664
80,670 77,672 2,302,902 652,675 124,677 121,138 1,434,099 695,929 425,787 341,956 465,364 467,433 162,980 516,637 819,677 1,106,998 545,864 321,245

State MO MT NE NV NH NJ NM NY NC ND OH OK OR PA RI SC SD TN TX UT VT VA WA WV WI WY
USA

5,113,266 799,065
1,577,600 1,201,833 1,109,252 7,730,188 1,515,069 17,990,026 6,628,637
637,713 10,846,581
3,145,585 2,842,321 11,881,643 1,003,211 3,486,703
695,133 4,896,046 16,984,748 1,722,850
562,758 6,184,493 4,866,692 1,792,969 4,891,452
453,588

AUnder12
897,590 150,406 294,659 208,695 195,970 1,217,936 307,898 2,891,618 1,074,691 119,767 1,899,661 563,941 495,834 1,892,957 155,439 616,373 137,110 812,832 3,320,887 430,959
99,365 1,030,088
878,141 279,885 887,426
92,123

A12to18
490,067 83,457
156,790 100,891
98,977 681,960 160,598 1,615,696 637,603
65,036 1,064,732
318,809 265,630 1,074,128
86,271 363,140
71,070 484,155 1,776,426 226,933
53,099 564,690 444,693 192,881 472,270
49,716

A19to24
436,468 57,351
130,613 102,609 100,411 664,059 123,983 1,664,461 662,849
57,151 957,750 267,411 225,488 1,041,626 102,680 339,600
56,976 452,701 1,578,004 167,637
53,049 616,835 417,468 148,808 437,743
33,980

A25to34
855,640 123,913 259,709 223,599 205,815 1,366,267 259,975 3,148,965 1,152,229 104,833 1,805,063 514,663 455,371 1,918,168 174,149 596,534 109,919 823,042 3,118,515 275,853
95,880 1,147,609
861,441 262,961 825,056
75,462

A35to44
734,252 128,067 229,478 192,324 183,649 1,200,167 229,577 2,720,452 1,008,277
90,808 1,619,291
452,308 476,343 1,739,212 146,571 526,103
96,063 740,485 2,548,657 224,715
92,804 991,563 804,413 270,784 726,753
74,182

A45to54
524,756 81,522
148,720 138,893 111,387 850,983 149,712 1,944,539 705,099
56,215 1,115,355
326,770 297,101 1,224,867
97,958 357,747
61,962 530,654 1,649,538 139,656
57,274 670,457 504,238 191,957 478,819
45,541

A55to64
457,095 67,930
134,711 107,621
88,059 718,589 120,808 1,642,487 585,832
53,132 978,701 278,089 235,423 1,160,974
89,156 291,077
59,623 433,773 1,284,825 107,405
45,118 500,955 380,725 176,960 412,492
35,539

A65Plus
717,398 106,419 222,920 127,201 124,984 1,030,227 162,518 2,361,808 802,057
90,771 1,406,028
423,594 391,131 1,829,711 150,987 396,129 102,410 618,404 1,707,896 149,692
66,169 662,296 575,573 268,733 650,893
47,045

248,418,140 43,454,102 23,694,112 22,614,049 43,429,692 37,582,954 25,435,905 21,083,554 31,123,772

Figure 9 Population by state and age group, part 2

Different experiments have different age and geographic attributes. See Figure 11 for a
list of all 13 experiments identified as A through M. So, Qdob and Zi, as used above, are representative of several quasi-identifiers that have varying specifications. In experiment B through experiment E, Zi ∈{ZIP codes in USA in which people reside}. In experiment F through experiment I, Zi ∈{Cities, municipalities, towns and recognized post office names in the USA}. Finally, in experiment J through experiment M, Zi ∈{Counties in the USA}. Similarly, in experiments B, F, and J, Qdob = {date of birth, gender}. In experiments C, G and K, Qdob = {month and year of birth, gender}. In experiments D, H and L, Qdob = {year of birth, gender}. Finally, in experiments E, I and M, Qdob = {2 year age subdivision, gender}.

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For completeness, Figure 8 and Figure 9 report the total population per state of each age group. These values are used to compute percentages throughout this document unless otherwise noted.
4.4. Special data elements
This section compares age and year of birth values, as well as, 5-digit ZIP codes, places and counties.
4.4.1. Age versus Year of Birth
Values for an age attribute do not necessarily translate to known values for a year of birth attribute. There are two cases to consider. If there exists a date to which values for age can be referenced, then corresponding values for year of birth can be confidently computed. For example, in SID, states calculate the patient's age in years at the time of admission [14]. Because both the computed age and the date of admission are released, the patient's year of birth can be confidently determined. In experiment D, H and L, I examine age as providing a distinct year of birth, and so QISID2 = {age, gender, 5-digit ZIP} can be considered as QISID2 = {year of birth, gender, 5-digit ZIP}.
On the other hand, if values for date of admission were not released, values for age would be calendar year specific. In such cases, data are collected with respect to a particular calendar year (that is known) but not a particular day within that year. As a result, each value for age corresponds to two possible values for each person's year of birth. During any given calendar year, a person reports two ages. The first age occurs before the person's birthday and the second occurs on and after the person's birthday. Because each person's birthday can appear at any time during the calendar year (in contrast to societies in which everyone's "birthday", in terms of determining age, occurs on the same day), two values can be inferred for year of birth from a recorded value for age. In the experiment E, I and M, I examine {2 yr age subdivision, gender, 5digit ZIP} in which the birth year is within a known 2-year range.
4.4.2. Comparison of 5-digit ZIP codes, Places and Counties
Figure 10 shows a comparison of 5-digit ZIP codes, places and counties in the United States. There are a total of 29,343 ZIP codes, 25,688 places and 3,141 counties. The state having the largest number of counties was Texas (with 254). The District of Columbia had the fewest number of counties (with 1). The average number of counties per state was 62 and the standard deviation was 47.

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State
AL AK AZ AR CA CO CT DE DC FL GA HI ID IL IN IA KS KY LA ME MD MA MI MN MS

Number 5-digit ZIPs
567 195 270 578 1,515 414 263
53 24 804 636 80 244 1,236 675 922 713 810 469 410 419 473 875 877 363

Number Places
511 183 178 563 1,071 330 224 46
2 463 561 70 233 1,147 597 889 646 772 408 408 378 404 768 809 342

Number Counties State
67 MO 25 MT 15 NE 75 NV 58 NH 63 NJ
8 NM 3 NY 1 NC 67 ND 159 OH 5 OK 44 OR 102 PA 92 RI 99 SC 105 SD 120 TN 64 TX 16 UT 24 VT 14 VA 83 WA 87 WV 82 WI
WY

Number digit ZIPs
993 315 572 104 218 540 276 1,594 705 387 1,007 586 384 1,458
69 350 383 583 1,672 205 243 820 484 655 714 141

Number Number

Places Counties

899

115

309

57

518

93

66

17

212

10

490

21

258

33

1,369

62

624

100

384

53

854

88

511

77

344

36

1,369

67

52

5

313

46

377

66

505

95

1,234

254

181

29

243

14

729

136

397

39

646

55

666

72

135

23

USA

29,343 25,688

3,141

max min avg stdev

1,672

1,369

254

24

2

1

575

504

62

401

337

47

Figure 10 Number of 5-digit ZIP codes, Places and Counties by State

5. Results

In the previous sections, I defined terminology and introduced the materials that will be used. In this section, I report on experiments I conducted to estimate the number of unique occurrences for various combinations of demographic attributes that are typically released in publicly and semi-publicly available data.
Experiment A: Uniqueness of {ZIP, gender, date of birth} assume uniform age distribution Experiment B: Uniqueness of {ZIP, gender, date of birth} based on actual age distribution Experiment C: Uniqueness of {ZIP, gender, month and year of birth} Experiment D: Uniqueness of {ZIP, gender, age} Experiment E: Uniqueness of {ZIP, gender, 2yr age range} Experiment F: Uniqueness of {place/city, gender, date of birth} Experiment G: Uniqueness of {place/city, gender, month and year of birth} Experiment H: Uniqueness of {place/city, gender, age} Experiment I: Uniqueness of {place/city, gender, 2yr age range} Experiment J: Uniqueness of {county, gender, date of birth} Experiment K: Uniqueness of {county, gender, month and year of birth} Experiment L: Uniqueness of {county, gender, age} Experiment M: Uniqueness of {county, gender, 2yr age range}
Figure 11 List of 13 experiments

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A total of 13 experiments were conducted [15]. These are identified below. Only experiment B, C, D, F and J are briefly reported in this document. Figure 32 contains a summary of results from all 13 experiments.
5.1. Experiment B: Uniqueness of {ZIP, gender, date of birth}

Recall, Illinois Research Health Data named ROD provides an example of shared data that contains demographic attributes; in particular, QIrod = {date of birth, gender, 5-digit ZIP}. This experiment shows that medical conditions included in these data can be attributed uniquely to one person in most cases.
5.1.1. Experiment B Design

Step 1. Use ZIP table for each of the 50 states and the District of Columbia. Step 2. Figure 12 contains the thresholds for Q={gender, date of birth} specific to each age subdivision. Step 3. Report statistical measurements computed from the table in step 1 using the thresholds determined in step 2. Figure 13 and Figure 14 report the results.

Q = {gender, date of birth}

|QAUnder12|

= 2 * 365 * 12 = 8,760

|QA12to18|

= 2 * 365 * 7 = 5,110

|QA19to24|

= 2 * 365 * 6 = 4,380

|QA25to34|

= 2 * 365 * 10 = 7,300

|QA35to44|

= 2 * 365 * 10 = 7,300

|QA45to54|

= 2 * 365 * 10 = 7,300

|QA55to64|

= 2 * 365 * 10 = 7,300

|QA65Plus|

= 2 * 365 * 12 = 8,760

Figure 12 Number of possible values for each age subdivision {gender, date of birth}

5.1.2. Experiment B Results

Figure 13 and Figure 14 show the results from applying the 3 steps of experiment B to each state, the District of Columbia and the entire United States. The percentages computed for each locale appear in the column named “RANGE %ID_pop.” The last row in Figure 14 reports the results of applying the 3 steps of experiment B to all ZIP codes in the United States. As shown, 87.1% of the population of the United States is likely to be uniquely identified by values of {gender, date of birth, ZIP} when age subdivisions are considered.
During the analysis of experiment B, many interesting ZIP codes were found. Here are a few. The ZIP code 11794 in the State of New York is small and extremely homogenous. 4666 of its total population of 5418 (or 86%) are in the age subdivision of 19 to 24. This is the home of the State University of New York at Sony Brook. The ZIP code 10475 in the State of New York reportedly has a larger population of 37077, but people are distributed somewhat evenly across the age subdivisions making the population in each range less than its corresponding threshold. The ZIP code 01701 in the Commonwealth of Massachusetts reportedly has a population of 65,001, which is the largest population for a ZIP code in the state. In experiment A, any person residing in that ZIP code would NOT have been considered likely to be uniquely identified by {gender, date of birth, ZIP}; however, only the subpopulation between the ages of 19 and 44 in

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that ZIP code is large enough not to be considered uniquely identified by {gender, date of birth, ZIP}. Persons residing in that ZIP code, who are not in that age subdivision, are less common and considered likely to be uniquely identified by {gender, date of birth, ZIP} even though the population in the entire ZIP code is the largest in the state.

State AL AK AZ AR CA CO CT DE DC FL GA HI ID IL IN IA KS KY LA ME MD MA MI MN MS

#ZIPs Population

567 4,040,587

195

544,698

270 3,665,228

578 2,350,725

1,515 29,755,274

414 3,293,771

263 3,287,116

53

666,168

24

606,900

804 12,686,788

636 6,478,847

80 1,108,229

244 1,006,749

1,236 11,429,942

675 5,543,954

922 2,776,442

713 2,474,885

810 3,673,969

469 4,219,973

410 1,226,626

419 4,771,143

473 6,011,978

875 9,295,222

877 4,370,288

363 2,573,216

RANGE %population
99% 100%
82% 98% 71% 92% 91% 91% 64% 91% 90% 74% 99% 75% 94% 98% 98% 98% 91% 98% 83% 91% 85% 95% 98%

AUnder12 100.0% 100.0% 82.3% 97.8% 62.4% 89.7% 94.3% 100.0% 62.0% 93.9% 90.4% 62.5% 100.0% 73.0% 94.3% 100.0% 100.0% 100.0% 89.8% 100.0% 84.8% 95.7% 80.5% 96.2% 98.2%

A12to18 100.0% 100.0% 90.1% 100.0% 73.1% 96.2% 98.1% 100.0% 74.9% 95.8% 93.5% 94.4% 100.0% 76.4% 95.2% 100.0% 100.0% 100.0% 91.7% 100.0% 94.1% 97.9% 84.7% 100.0% 98.1%

A19to24 A25to34 89.7% 98.7%
100.0% 100.0% 67.4% 64.3% 87.1% 95.3% 54.9% 47.2% 85.0% 81.1% 76.1% 76.2% 72.0% 66.7% 32.5% 47.6% 87.5% 85.2% 80.4% 77.8% 56.7% 55.9% 85.6% 100.0% 59.2% 60.1% 80.4% 85.4% 78.9% 98.0% 83.1% 94.1% 85.7% 97.5% 80.4% 83.6% 86.3% 96.3% 79.2% 63.7% 73.5% 74.8% 72.5% 74.5% 81.8% 87.7% 88.3% 100.0%

A35to44 100.0% 100.0% 88.8% 100.0% 70.0% 92.1% 88.9% 100.0% 55.3% 94.3% 87.6% 71.9% 100.0% 73.9% 94.7% 100.0% 100.0% 98.6% 93.0% 100.0% 80.2% 92.8% 83.2% 97.4% 97.8%

A45to54 100.0% 100.0% 100.0% 100.0% 96.8% 100.0% 100.0% 100.0% 100.0% 98.6% 100.0% 100.0% 100.0% 90.3% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 93.8% 100.0% 98.2% 100.0% 100.0%

A55to64 100.0% 100.0% 100.0% 100.0% 99.6% 100.0% 100.0% 100.0% 84.9% 99.2% 100.0% 100.0% 100.0% 93.9% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 99.1% 100.0% 100.0%

A65Plus 100.0% 100.0% 80.7% 100.0% 96.8% 100.0% 97.8% 100.0% 85.1% 83.6% 100.0% 83.7% 100.0% 86.7% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 88.7% 98.8% 98.3% 100.0% 100.0%

Figure 13 Uniqueness of {ZIP, Gender, Date of birth} respecting age distribution, part 1

State MO MT NE NV NH NJ NM NY NC ND OH OK OR PA RI SC SD TN TX UT VT VA WA WV WI WY

#ZIPs Population

993 5,113,266

315

799,065

572 1,577,600

104 1,201,833

218 1,109,252

540 7,730,188

276 1,515,069

1,594 17,990,026

705 6,628,637

387

637,713

1,007 10,846,581

586 3,145,585

384 2,842,321

1,458 11,881,643

69 1,003,211

350 3,486,703

383

695,133

583 4,896,046

1,672 16,984,748

205 1,722,850

243

562,758

820 6,184,493

484 4,866,692

655 1,792,969

714 4,891,452

141

453,588

RANGE %population
94% 98% 99% 86% 97% 92% 88% 76% 94% 96% 92% 97% 97% 91% 92% 91% 96% 93% 88% 87% 98% 87% 92% 97% 92% 98%

AUnder12 94.4%
100.0% 100.0%
79.5% 100.0%
92.6% 86.1% 74.3% 98.1% 100.0% 92.2% 96.7% 100.0% 90.5% 94.4% 90.0% 92.7% 93.7% 85.0% 75.8% 100.0% 88.2% 94.6% 96.7% 88.9% 100.0%

A12to18 98.8%
100.0% 100.0%
94.3% 100.0%
93.1% 89.0% 77.3% 96.4% 100.0% 94.7% 100.0% 100.0% 94.0% 100.0% 95.1% 100.0% 94.8% 89.1% 80.0% 100.0% 91.6% 100.0% 96.4% 97.7% 100.0%

A19to24 A25to34 86.9% 86.8% 78.9% 100.0% 90.2% 100.0% 79.5% 66.9% 94.1% 88.5% 88.0% 79.8% 88.6% 71.6% 64.1% 60.0% 77.5% 86.4% 68.5% 91.9% 82.4% 82.5% 85.2% 93.5% 89.5% 90.6% 80.1% 82.2% 71.1% 84.2% 74.8% 79.5% 81.4% 91.6% 80.5% 87.1% 78.8% 76.5% 78.0% 90.2% 80.1% 100.0% 71.9% 75.5% 82.8% 82.5% 90.2% 95.7% 77.6% 86.4% 79.2% 100.0%

A35to44 92.1%
100.0% 100.0%
88.3% 100.0%
92.9% 82.4% 72.1% 96.5% 100.0% 93.6% 96.7% 93.1% 90.3% 94.9% 95.0% 100.0% 93.5% 90.0% 92.6% 100.0% 82.7% 87.2% 96.4% 92.6% 100.0%

A45to54 100.0% 100.0% 100.0% 94.6% 100.0% 99.1% 100.0% 88.3% 98.8% 100.0% 100.0% 100.0% 100.0% 99.3% 100.0% 97.9% 100.0% 100.0% 100.0% 100.0% 100.0% 97.8% 100.0% 100.0% 100.0% 100.0%

A55to64 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 93.4% 100.0% 100.0% 100.0% 100.0% 100.0% 99.4% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

A65Plus 97.3%
100.0% 100.0% 100.0% 100.0%
94.1% 100.0%
85.5% 100.0% 100.0%
98.5% 100.0% 100.0%
94.3% 94.2% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 96.5% 100.0% 100.0%

USA 29,343 248,418,140

87%

85.8%

90.2%

75.0% 75.1% 87.0% 97.8% 99.0% 95.3%

Figure 14 Uniqueness of {ZIP, Gender, Date of birth} respecting age distribution, part 2

Figure 15 plots the percentage of the population considered identifiable in each ZIP code in the United States based on experiment B’s criteria. The horizontal axis represents the

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L. Sweeney, Simple Demographics Often Identify People Uniquely. Carnegie Mellon University, Data Privacy Working Paper 3. Pittsburgh 2000.
population that resides in the ZIP code. The vertical axis represents the percentage of the population considered uniquely identified by values of Q={date of birth, gender, 5-digit ZIP} for a particular ZIP code. The criteria for computing the percentage of the population considered identifiable in experiment B is based on binary decisions, where each decision considers whether a sufficient number of people in a particular age subdivision reside in a particular ZIP code. If so, that sub-population is not considered identifiable; otherwise, its entire sub-population is considered identifiable.
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100000 120000

Figure 15 Percentage of Population Identifiable Based on Age subdivisions in ZIP Population

Most ZIP codes (27697 of 29212 or 95%) in the United States that have people listed as residing within them do not have enough people in any age subdivision to consider any such subpopulation as identifiable. This is evidenced in Figure 15 by the appearance of dots where the %pop identifiable is 1. The largest population having %pop identifiable = 1 consists of 48,549 total people. There are very few ZIP codes (15 of 29212) in Figure 15 having sufficient numbers of people in each age subdivision that each such sub-population is not considered uniquely identifiable. This is evidenced in Figure 15 by the appearance of dots where the %pop identifiable is 0. The largest population having %pop identifiable = 0 has 99,995 people and the smallest has 73,321.
The ZIP code having the largest population, ZIP 60623 with 112,167 people, has a percentage of its population considered identifiable in Figure 15 as being only 11%. It is not 0% because there are insufficient numbers of people above the age of 55 living there despite the large number of people residing in the ZIP code. The point representing this ZIP code in Figure 15 is the rightmost point shown.
The lowest leftmost point shown in Figure 15 corresponds to ZIP 11794, which was discussed earlier. It has a total population of 5418 people and consists primarily of people between the ages of 19 and 24 (4666 of 5418 or 86%). Despite having a small population, the people residing there are very homogenous in terms of age and so the percentage of its population

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L. Sweeney, Simple Demographics Often Identify People Uniquely. Carnegie Mellon University, Data Privacy Working Paper 3. Pittsburgh 2000.
considered identifiable based on experiment B’s criteria is only 13%. It is clear from these examples that population size alone is not an absolute predictor of the identifiability of the people residing within. Care must be taken to model the population as precisely as possible to insure privacy protection.

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Figure 16 Percentage of Age-based Populations Identifiable within ZIP Population, Part 1

Recall the computation of the percentage of the population considered uniquely identified by values of Q={date of birth, gender, 5-digit ZIP} for a particular ZIP code in experiment B is based on a composite of binary decisions. Each binary decision concerns the number of people residing within a specific ZIP code in a particular age subdivision. Figure 16 and Figure 17 show plots of the percentage of sub-populations considered identifiable in each ZIP code in the United States based on experiment B’s criteria. The horizontal axis represents the population that resides in the ZIP code. The vertical axis represents the percentage of the population considered uniquely identified by values of Q={date of birth, gender, 5-digit ZIP} for a particular ZIP code and a particular age subdivision. If a sufficient number of people within an age subdivision are reported as residing in a particular ZIP code, then that sub-population is considered identifiable; otherwise, the entire sub-population is not considered identifiable.
Figure 18 provides statistical highlights from the plots in Figure 16 and Figure 17. The topmost table provides statistics on ZIP codes in which the number of people within the noted age subdivision is less than or equal to the threshold for that subdivision. In these cases, the subpopulation within the ZIP code is considered uniquely identifiable; that is, %pop_Identifiable = 1 for that age subdivision and ZIP code. The bottom table provides statistics in cases where %pop_Identifiable < 1. In these ZIP codes, the number of people within the noted age subdivision

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L. Sweeney, Simple Demographics Often Identify People Uniquely. Carnegie Mellon University, Data Privacy Working Paper 3. Pittsburgh 2000.
is greater than the threshold for that subdivision; therefore, this subdivision is not considered uniquely identifiable.

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Figure 17 Percentage of Age-based Populations Identifiable within ZIP Population, Part 2

Sub-population considered uniquely identifiable (<= threshold, IDSet )

Max ZIP population Min ZIP population Average ZIP population standard deviation Number of ZIP codes Percentage ZIP codes

AUnder12 107197 1 7615 19452 28675 98.2%

A12to18 107197 1 7873 10915 28860 98.8%

A19to24 66722 1 7332 10070 28352 97.1%

A25to34 60388 1 6911 9227 28105 96.2%

A35to44 62031 1 7596 10393 28665 98.1%

A45to54 99420 1 8358 11938 29148 99.8%

A55to64 112167 1 8442 12165 29187 99.9%

A65Plus 112167 1 8311 11956 29081 99.6%

Sub-population NOT considered uniquely identifiable (> threshold, NotIDSet )

Max ZIP population Min ZIP population Average ZIP population standard deviation Number of ZIP codes Percentage ZIP codes

AUnder12 112167 28294 55958 12770 537 1.8%

A12to18 112167 35092 60254 13036 352 1.2%

A19to24 112167 5418 47153 17178 860 2.9%

A25to34 112167 20211 48944 12681 1107 3.8%

A35to44 112167 30577 56072 13157 547 1.9%

A45to54 112167 34860 74798 15961 64 0.2%

A55to64 107197 60388 80513 12304 25 0.1%

A65Plus 107197 12890 51313 20367 131 0.4%

Figure 18 Statistical highlights from Figure 16 and Figure 17

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5.2. Experiment C: Uniqueness of {ZIP, gender, month and year of birth}

This experiment (referred to as experiment C) is motivated by the Agency for Healthcare Research and Quality’s State Inpatient Database (RSID), which is described in part in Figure 3. Among the attributes listed there, I consider QISID1 = {month and year of birth, gender, 5-digit ZIP} to be a quasi-identifier within data released by some states. This experiment attempts to characterize the identifiability of QISID1.
5.2.1. Experiment C Design

Step 1. Use ZIP table for each of the 50 states and the District of Columbia. Step 2. Figure 19 contains the thresholds for Q={gender, month and year of birth} specific to each age subdivision. Step 3. Report statistical measurements computed from the table in step 1 using the thresholds determined in step 2. Figure 20 and Figure 21 report the results.

Q3 = {gender, month and year of birth}

|Q3AUnder12|

= 2 * 12 * 12 = 288

|Q3A12to18|

= 2 * 12 * 7 = 168

|Q3A19to24|

= 2 * 12 * 6 = 144

|Q3A25to34|

= 2 * 12 * 10 = 240

|Q3A35to44|

= 2 * 12 * 10 = 240

|Q3A45to54|

= 2 * 12 * 10 = 240

|Q3A55to64|

= 2 * 12 * 10 = 240

|Q3A65Plus|

= 2 * 12 * 12 = 288

Figure 19 Number of possible values for each age subdivision for {gender, month and year of birth}

5.2.2. Experiment C Results

Figure 20 and Figure 21 show the results of applying the 3 steps of experiment C to each state, the District of Columbia (as just reported) and the entire United States. The percentage of people residing in each locale likely to be uniquely identifiable based on {gender, month and year of birth, ZIP} appear in the column named “MonYr %ID_pop.” For example, 18.1% of the population of Iowa (see Figure 20) and 26.5% of the population of North Dakota (see Figure 21) are likely to be uniquely identifiable based on {gender, month and year of birth, ZIP}.
The next to last row in Figure 21 labeled "USA" reports the results of applying the 3 steps of experiment C to all ZIP codes in the United States. As shown, 3.7% of the population of the United States is likely to be uniquely identified by values of {gender, month and year of birth, ZIP}. The last row in Figure 21 labeled "%ID_pop" displays the percentage of people in each age subdivision who are likely to be uniquely identified by values of {gender, month and year of birth, ZIP}. For example, it reports that 5% of the population of persons residing in the United States between the ages of 45 and 54 are likely to be uniquely identifiable based on {gender, month and year of birth, ZIP}.
Figure 22 plots the percentage of the population considered identifiable in each ZIP code in the United States based on experiment C’s criteria. The horizontal axis represents the population that resides in the ZIP code. The vertical axis represents the percentage of the

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population considered uniquely identified by values of QISID1 = {month and year of birth, gender, 5-digit ZIP} for a particular ZIP code. This is the same as the approach used in experiment B.

State
AL AK AZ AR CA CO CT DE DC FL GA HI ID IL IN IA KS KY LA ME MD MA MI MN MS

MonYr %ID_pop
3.8% 10.7%
1.4% 11.4%
0.8% 3.7% 1.2% 0.9% 0.2% 0.6% 2.7% 1.6% 8.9% 4.4% 4.0% 18.1% 12.1% 8.3% 2.8% 15.5% 2.1% 1.1% 2.4% 9.0% 4.4%

AUnder12
22,253 12,416
6,804 41,221 33,588 18,174
5,203 867 275
10,862 19,935
1,767 11,922 75,604 28,592 82,724 46,345 48,404 15,800 29,727 14,087
8,446 27,008 59,128 12,939

A12to18
11,325 6,542 3,888
23,185 19,440 10,214
2,845 557 72
6,777 11,272
1,242 7,146 42,727 16,297 44,905 25,207 24,728 8,567 16,098 7,843 5,949 16,914 34,860 7,915

A19to24
10,982 4,826 4,386
20,274 16,982
8,764 3,097
257 26
6,548 11,318
1,602 6,950 40,364 17,739 34,644 20,797 23,501 8,553 14,462 8,086 5,540 18,153 28,225 8,487

A25to34
18,197 9,045 6,786
34,340 27,467 14,721
4,102 653 180
8,311 18,321
1,911 11,657 62,012 25,328 70,040 36,178 37,727 13,180 23,099 11,105
6,291 22,223 49,369 12,557

A35to44
19,285 7,633 5,968
35,164 26,335 14,523
3,675 652 95
9,208 22,193
1,795 11,988 63,393 25,849 64,634 38,319 39,465 13,922 23,470 11,093
6,191 25,106 52,048 14,378

A45to54
22,443 6,253 7,091
35,248 31,331 16,946
5,104 960 66
11,647 26,345
2,797 12,404 68,919 33,632 65,878 40,822 41,358 17,090 26,896 13,739 10,006 33,248 54,780 17,937

A55to64
24,806 5,522 7,095
35,440 33,500 17,965
7,135 715 57
11,760 31,161
3,645 12,220 70,997 34,730 65,808 41,630 43,680 18,399 26,041 16,099 12,702 37,570 53,583 18,845

A65Plus
24,254 6,063 8,120
42,675 34,743 21,333
7,514 1,627
404 13,330 34,905
3,469 15,587 77,971 36,884 72,916 49,544 46,346 22,675 30,713 20,297 12,847 40,591 60,926 20,676

Figure 20 Uniqueness of {ZIP, Gender, Month and year of birth} respecting age distribution, part 1

Of the ZIP codes reported in Figure 22, about half (13,871 of 29,212 or 47%) have sufficient numbers of people in each age subdivision so that values of QISID1 = {month and year of birth, gender, 5-digit ZIP} are not likely to be uniquely identifying; in these cases, %pop identifiable = 0. Values of QISID1 for about one third (9103 of 29212 or 31%) of the ZIP codes are considered uniquely identifying in all age subdivisions; in these cases, %pop identifiable = 1. The remaining ZIP codes (6238 of 29212 or 21%) have sub-populations in which values of QISID1 are uniquely identifiable for some age subdivisions but not for others.
Figure 23 provides statistical highlights from the plot in Figure 22. The topmost table provides statistics on ZIP codes in which the number of people within the noted age subdivision is less than or equal to the threshold for that subdivision. In these cases, the sub-population within the ZIP code is considered uniquely identifiable; that is, %pop_Identifiable = 1 for that age subdivision and ZIP code. The bottom table provides statistics in cases where %pop_Identifiable < 1. In these ZIP codes, the number of people within the noted age subdivision is greater than the threshold for that subdivision; therefore, this subdivision is not considered uniquely identifiable. The method for computing these statistics was described earlier in the Methods section (on page 11).

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State
MO MT NE NV NH NJ NM NY NC ND OH OK OR PA RI SC SD TN TX UT VT VA WA WV WI WY

MonYr %ID_pop
8.2% 15.5% 18.2%
2.0% 7.5% 0.6% 5.2% 2.3% 2.4% 26.5% 2.2% 7.1% 4.2% 3.5% 0.9% 2.3% 25.9% 3.4% 2.3% 3.4% 21.9% 4.4% 2.6% 15.5% 5.4% 10.1%

AUnder12
65,966 18,771 46,646
4,320 11,934
6,760 11,169 54,792 22,064 28,362 28,645 32,749 18,614 58,144
1,085 9,342 27,699 24,172 51,615 8,496 19,797 41,345 18,736 43,535 32,406 8,492

A12to18
37,847 11,741 27,556
2,035 7,545 4,693 6,307 33,243 11,906 16,090 14,449 20,178 9,286 32,516
642 5,171 17,147 12,553 29,794 4,844 11,196 23,241 11,083 25,866 21,664 3,943

A19to24
31,629 7,717
17,763 1,983 6,001 3,510 5,208
31,443 10,595
9,492 18,930 16,901
8,839 32,758
500 5,813 11,054 13,053 30,883 4,042 8,334 20,634 9,104 21,381 21,855 2,743

A25to34
52,566 16,581 38,678
3,341 8,773 3,811 10,048 45,160 17,177 22,535 24,301 26,174 15,741 47,305
764 8,643 25,496 18,105 45,082 7,026 16,536 30,706 14,925 36,753 31,257 6,058

A35to44
53,596 16,326 40,574
2,977 7,859 4,642 10,235 49,560 16,987 22,563 24,283 29,484 14,495 45,996 1,417 8,309 24,375 19,074 50,060 7,447 17,312 33,035 15,043 37,676 30,297 5,943

A45to54
57,098 16,280 34,699
2,516 12,067
5,846 10,844 61,882 23,559 20,666 37,395 29,507 15,766 62,507
1,025 12,372 22,171 22,832 58,173
8,832 16,075 35,263 17,563 34,584 40,576
6,251

A55to64
56,566 16,432 37,697
2,705 13,156
8,238 11,340 68,223 27,726 22,226 43,814 32,320 15,778 66,894
1,487 13,670 23,721 25,898 62,784
8,293 16,093 40,117 19,665 35,731 43,567
5,893

A65Plus
65,194 19,924 43,232
4,256 15,851
8,142 14,141 76,979 31,714 27,314 47,838 35,238 19,684 75,584
1,996 16,738 28,405 30,553 68,838 10,307 18,066 47,007 21,650 42,582 44,714
6,684

USA %ID_pop

3.7% 1,329,747 3.1%

759,051 3.2%

676,728 1,098,342 1,125,947 1,269,289 1,351,139 1,529,041

3.0%

2.5%

3.0%

5.0%

6.4%

4.9%

Figure 21 Uniqueness of {ZIP, Gender, Month and year of birth} respecting age distribution, part 2

Q)
:a

0.8

-=(ll
.::

C: Q)

0.6

"tJ

a.

0a.
~

0.4

0.2

0

0

20000

40000

60000

80000

100000

120000

ZIP po pulation

Figure 22 Percentage of Population Identifiable Based on Uniform Distribution of Ages in ZIP Population

The values reported as ZIP populations in Figure 22 are not the total number of people within the reported age subdivision residing in those ZIP codes but are just the numbers of people

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residing in the ZIP code. For example, consider the values appearing in the "Aunder12" column in Figure 22. They report information about children under the age of 12 residing in 10,852 ZIP codes in the United States that had insufficient numbers of children to render corresponding values of QISID1 = {month and year of birth, gender, 5-digit ZIP} uniquely identifiable. Of these ZIP codes, the largest number of children of under the age of 12, residing in a ZIP code was 287. Some ZIP codes, who had people residing within them, had no children in this age. The average number of children in these ZIP codes was 123 with a standard deviation of 80.

Sub-population considered uniquely identifiable (<= threshold, IDSet )

Max ZIP sub-population Min ZIP sub-population Average ZIP sub-population standard deviation Number of ZIP codes Percentage ZIP codes

AUnder12 287 0 123 80
10852 37.1%

A12to18 167 0 71 47
10725 36.7%

A19to24 143 0 53 40
12760 43.7%

A25to34 239 0 101 66
10883 37.3%

A35to44 239 0 102 66
11045 37.8%

A45to54 239 0 96 66
13202 45.2%

A55to64 239 0 95 66
14220 48.7%

A65Plus 287 0 118 80
12905 44.2%

Sub-population NOT considered uniquely identifiable (> threshold, NotIDSet )

Max ZIP sub-population Min ZIP sub-population Average ZIP sub-population standard deviation Number of ZIP codes Percentage ZIP codes

AUnder12 26914 288 2294 2530 18360 62.9%

A12to18 15352 168 1241 1327 18487 63.3%

A19to24 27123 144 1333 1690 16452 56.3%

A25to34 24587 240 2309 2632 18329 62.7%

A35to44 19543 240 2007 2096 18167 62.2%

A45to54 15544 240 1509 1419 16010 54.8%

A55to64 12205 240 1316 1174 14992 51.3%

A65Plus 25799 288 1815 1860 16307 55.8%

Figure 23 Statistical highlights from Figure 20 and Figure 21

5.3. Experiment D: Uniqueness of {ZIP, gender, age}

In this experiment, I examine the identifiability of {year of birth, gender, 5-digit ZIP} in the United States. Progressing through the results from the last three experiments, values referring to age became less specific and as expected, the values became less uniquely identifying. What may be surprising however is that these values remained uniquely identifying for some people.
The Agency for Healthcare Research and Quality’s State Inpatient Database (SID; see Figure 3) motivated this experiment as well as experiment C. In addition to QISID1 used in experiment C, SID also includes QISID2 = {age, gender, 5-digit ZIP} for some states in those data. Recall in section 4.4.1, I examine age as providing a distinct year of birth, and so QISID2 = {age, gender, 5-digit ZIP} can be considered as QISID2 = {year of birth, gender, 5-digit ZIP}.
5.3.1. Experiment D Design

Step 1. Use ZIP table for each of the 50 states and the District of Columbia. Step 2. Figure 24 contains the thresholds for Q={gender, date of birth} specific to each age subdivision. Step 3. Report statistical measurements computed from the table in step 1 using the thresholds determined in step 2. Figure 25 and Figure 26 report the results.

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Q4 = {gender, year of birth}

|Q4AUnder12|

= 2 * 12

|Q4A12to18|

= 2 * 7

|Q4A19to24|

= 2 * 6

|Q4A25to34|

= 2 * 10

|Q4A35to44|

= 2 * 10

|Q4A45to54|

= 2 * 10

|Q4A55to64|

= 2 * 10

|Q4A65Plus|

= 2 * 12

= 24 = 14 = 12 = 20 = 20 = 20 = 20 = 24

Figure 24 Number of possible values for each age subdivision for {gender, year of birth}

5.3.2. Experiment D Results

Figure 25 and Figure 26 show the results of applying the 3 steps of experiment D to each state, the District of Columbia (as just reported) and the entire United States. The percentage of people residing in each locale likely to be uniquely identifiable based on {gender, year of birth, ZIP} appears in the column named “BirthYr %ID_pop” and the number of people represented by the percentage appears in the column named "BirthYr #ID_pop". For example, 0.89% (or 5703 people) of the population of Iowa (see Figure 26) are likely to be uniquely identifiable by values of {gender, year of birth, ZIP}.

State
AL AK AZ AR CA CO CT DE DC FL GA HI ID IL IN IA KS KY LA ME MD MA MI MN MS

BirthYr %ID_pop
0.02% 0.70% 0.02% 0.09% 0.01% 0.08% 0.01% 0.02% 0.01% 0.00% 0.01% 0.01% 0.19% 0.01% 0.01% 0.11% 0.22% 0.13% 0.02% 0.19% 0.03% 0.01% 0.01% 0.06% 0.02%

BirthYr Total
918 3,809
638 2,121 4,229 2,752
474 158
46 512 780 165 1,943 1,401 746 3,106 5,482 4,722 870 2,296 1,275 499 920 2,709 462

AUnder12
105 227
68 452 541 287
69 18
6 76 83 28 259 167 82 278 575 671 118 293 152 83 124 365 54

A12to18
53 223
31 138 319 224
55 13 63 29 11 148 111 27 305 446 309 48 217 119 50 133 214 23

A19to24
89 227
23 264 362 346
36 21 -
9 91
9 205 148
54 647 924 280
75 190
96 51 134 439 21

A25to34
97 223
53 208 461 336
52 28 -
5 101
33 255 141
88 182 571 528 118 287 156
35 151 421
39

A35to44
112 315
98 248 336 201
30 36 43 56 42 258 123 84 249 594 448 84 228 179 25 71 265 26

A45to54
125 631
98 312 540 447 108
5 90 120 12 310 246 89 583 1,017 697 135 280 187 58 133 326 57

A55to64
158 804
96 349 678 426
63 10 16 121 182 20 248 255 131 535 750 966 169 331 194 100 120 335 136

A65Plus
179 1,159
171 150 992 485
61 27 24 105 118 10 260 210 191 327 605 823 123 470 192 97 54 344 106

Figure 25 Uniqueness of {ZIP, Gender, Year of birth} respecting age distribution, part 1

The next to last row in Figure 26 labeled "USA" reports the results of applying the 3 steps of experiment D to all ZIP codes in the United States. As shown, 0.04% (or 105,016 people) of the population of the United States is likely to be uniquely identified by values of {gender, year of birth, ZIP}. The last row in Figure 26 labeled "%ID_pop" displays the percentage of people in each age subdivision who are likely to be uniquely identified by values of {gender, year of birth, ZIP}. For example, it reports that 0.08% of the population of persons residing in the

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United States between the ages of 55 and 64 are likely to be uniquely identified by values of {gender, year of birth, ZIP}.

State
MO MT NE NV NH NJ NM NY NC ND OH OK OR PA RI SC SD TN TX UT VT VA WA WV WI WY

BirthYr %ID_pop
0.07% 0.43% 0.23% 0.04% 0.07% 0.01% 0.22% 0.03% 0.02% 0.89% 0.00% 0.06% 0.07% 0.03% 0.01% 0.01% 0.63% 0.02% 0.03% 0.08% 0.20% 0.06% 0.03% 0.30% 0.02% 0.41%

BirthYr Total
3,403 3,465 3,560
439 777 728 3,302 5,460 1,032 5,703 377 1,963 1,900 3,099
92 443 4,408 836 5,483 1,323 1,117 3,754 1,227 5,360 881 1,851

AUnder12
451 399 241
77 154 125 343 714 133 586
34 220 369 501 -
87 489 201 815
78 76 572 164 746 80 213

A12to18
320 263 241
35 62 62 276 469 94 476 25 135 140 201 16 291 14 383 59 63 286 85 316 101 157

A19to24
402 405 717
39 106
41 237 533
74 832 30 248 172 324 41 607 125 443 146 171 350 145 433 135 232

A25to34
312 433 325
47 56 61 395 720 134 675 37 219 258 413
9 66 544 70 641 189 54 423 138 614 130 165

A35to44
371 362 387
47 81 51 350 445 103 639 33 274 124 348 10 63 516 53 661 151 81 445 122 605 79 195

A45to54
549 534 676
62 111
96 569 804 177 932
38 336 214 429
30 85 632 165 717 230 166 483 142 874 103 361

A55to64
531 492 455
57 100 114 644 818 168 787
96 237 315 440
19 45 597 128 794 230 150 638 220 869 103 223

A65Plus
467 577 518
75 107 178 488 957 149 776
84 294 308 443
24 40 732 80 1,029 240 356 557 211 903 150 305

USA %ID_pop

0.04% 105,016

13,049 0.03%

7,879 0.03%

11,729 0.05%

11,697 0.03%

10,747 0.03%

16,121 0.06%

16,463 0.08%

17,331 0.06%

Figure 26 Uniqueness of {ZIP, Gender, Year of birth} respecting age distribution, part 2

Most ZIP codes (25,705 of 29,212 or 88%) have sufficient numbers of people in each age subdivision so that values of QISID2 = {year of birth, gender, 5-digit ZIP} are not likely to be uniquely identifying; in these cases, %pop identifiable = 0. Values of QISID2 for about one third (353 of 29212 or 1%) of the ZIP codes are considered uniquely identifying in all age subdivisions; in these cases, %pop identifiable = 1. The remaining ZIP codes (3154 of 29212 or 11%) have sub-populations in which values of QISID2 are uniquely identifiable for some age subdivisions but not for all.
Figure 27 provides statistical highlights. The topmost table provides statistics on ZIP codes in which the number of people within the noted age subdivision is less than or equal to the threshold for that subdivision. In these cases, the sub-population within the ZIP code is considered uniquely identifiable; that is, %pop_Identifiable = 1 for that age subdivision and ZIP code. The bottom table provides statistics in cases where %pop_Identifiable < 1. In these ZIP codes, the number of people within the noted age subdivision is greater than the threshold for that subdivision; therefore, this subdivision is not considered uniquely identifiable.

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Sub-population considered uniquely identifiable (<= threshold, IDSet )

Max ZIP sub-population Min ZIP sub-population Average ZIP sub-population standard deviation Number of ZIP codes Percentage ZIP codes

AUnder12 24 0 11 8
1200 4.1%

A12to18 14 0 6 5
1342 4.6%

A19to24 12 0 5 4
2309 7.9%

A25to34 20 0 10 7
1210 4.1%

A35to44 20 0 9 7
1150 3.9%

A45to54 20 0 10 7
1651 5.7%

A55to64 20 0 9 7
1798 6.2%

A65Plus 24 0 11 8
1584 5.4%

Sub-population NOT considered uniquely identifiable (> threshold, NotIDSet )

Max ZIP sub-population Min ZIP sub-population Average ZIP sub-population standard deviation Number of ZIP codes Percentage ZIP codes

AUnder12 26914 25 1551 2291 28012 95.9%

A12to18 15352 15 850 1212 27870 95.4%

A19to24 27123 13 840 1460 26903 92.1%

A25to34 24587 21 1551 2372 28002 95.9%

A35to44 19543 21 1339 1914 28062 96.1%

A45to54 15544 21 922 1284 27561 94.3%

A55to64 12205 21 768 1057 27414 93.8%

A65Plus 25799 25 1126 1652 27628 94.6%

Figure 27 Statistical highlights from Figure 25 and Figure 26

5.4. Experiment F: Uniqueness of {place/city, gender, date of birth}

This experiment examines the identifiability of {date of birth, gender, place}. While the number of places is expected to be less than the number of ZIP codes, the difference is not as dramatic as one would expect.

State
AL AK AZ AR CA CO CT DE DC FL GA HI ID IL IN IA KS KY LA ME MD MA MI MN MS

DOB %ID_pop
74.31% 67.62% 30.18% 85.73% 35.99% 40.41% 66.44% 68.04%
0.00% 44.12% 62.62% 49.94% 76.93% 60.16% 63.45% 77.50% 66.77% 78.76% 58.86% 94.22% 63.22% 73.33% 56.68% 71.55% 81.12%

AUnder12
510,294 86,943
207,821 355,634 1,705,016 221,248 355,973
78,966 -
866,146 737,096
89,975 147,599 1,205,138 610,004 375,417 295,043 513,045 474,999 201,167 542,516 738,432 912,385 582,951 386,515

A12to18
316,271 36,668
117,371 221,013 1,032,675 124,459 208,871
40,675 -
523,124 425,884
69,406 93,691 698,921 362,468 218,025 167,547 319,232 271,968 117,015 299,174 409,915 535,570 327,576 232,392

A19to24
246,921 30,801 79,857
144,471 785,915 100,826 144,966
32,116 26
416,970 331,861
41,139 50,482 490,199 272,124 141,276 111,512 234,139 196,903 82,913 256,363 351,483 393,345 213,712 164,750

A25to34
455,646 72,365
154,789 278,355 1,266,384 189,908 296,959
63,018 -
743,419 601,348
80,566 116,729 976,815 485,926 310,173 236,104 451,331 380,395 184,342 432,696 610,144 760,515 462,644 307,447

A35to44
425,871 66,328
150,173 286,099 1,411,260 196,192 320,087
69,766 -
783,719 569,614
82,216 113,067 965,017 499,979 302,724 229,189 419,197 336,651 184,857 456,506 673,586 737,677 439,233 278,994

A45to54
340,085 34,744
121,318 217,119 1,494,618 164,375 299,897
49,625 -
697,379 501,763
68,636 83,114 842,088 431,504 238,696 182,750 325,073 278,656 123,745 379,792 526,058 656,494 358,955 231,718

A55to64
290,787 18,336
116,660 197,637 1,350,466 145,456 249,481
52,013 -
690,365 393,910
55,413 66,524 731,266 366,413 219,669 160,132 277,950 233,811 108,198 307,456 440,426 551,937 299,529 197,189

A65Plus
416,713 22,157
158,254 314,833 1,663,710 188,554 307,714
67,054 -
875,685 495,444
66,056 103,285 966,748 488,978 345,691 270,086 369,257 310,514 153,502 341,639 658,804 720,202 442,243 288,516

Figure 28 Uniqueness of {Place, Gender, Date of birth} respecting age distribution, part 1

Step 1. Use ZIP table for each of the 50 states and the District of Columbia. Step 2. Figure 12 contains the thresholds for Q={gender, date of birth} specific to each age subdivision. Step 3. Report statistical measurements computed from the table in step 1 using the thresholds

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determined in step 2. Figure 28 and Figure 29 report the results of applying the 3 steps of experiment F to each state, the District of Columbia and the entire United States.

The percentage of people residing in each locale likely to be uniquely identifiable by values of {gender, date of birth, place} appear in the column named “DOB %ID_pop.” For example, 94.22% of the population of Maine (see Figure 28) and 74.99% of the population of Pennsylvania (see Figure 29) are likely to be uniquely identifiable by values of {gender, date of birth, place}. Vermont had the largest percentage of its population identifiable (98.12%). The District of Columbia had 0% identified. The state having the smallest percentage was Nevada with 26.48%. The average was 64.54% and the standard deviation was 17.88%.

State
MO MT NE NV NH NJ NM NY NC ND OH OK OR PA RI SC SD TN TX UT VT VA WA WV WI WY

DOB %ID_pop
65.98% 78.05% 60.86% 26.48% 83.26% 75.46% 58.82% 50.89% 66.99% 89.24% 65.65% 64.24% 64.29% 74.99% 55.57% 67.65% 81.02% 64.98% 44.27% 56.43% 98.12% 58.50% 53.56% 90.95% 68.27% 79.05%

AUnder12
575,534 111,323 173,370
48,890 164,556 916,586 185,741 1,510,307 748,655 108,831 1,218,515 349,375 318,531 1,427,475
83,379 404,179 108,221 529,152 1,410,090 208,964
99,365 588,706 458,232 260,338 584,155
67,039

A12to18
345,340 63,624
100,557 29,379 84,043
513,909 103,241 893,370 434,802
59,803 726,779 209,852 186,694 829,811
52,128 259,598
62,338 319,932 792,176 117,137
53,099 358,361 257,086 178,947 333,763
36,679

A19to24
253,443 30,390 63,607 17,274 75,108
459,760 70,980
734,124 352,507
33,455 536,583 141,980 120,253 674,412
46,137 178,853
36,113 243,251 561,715
81,156 42,494 294,519 168,811 125,468 235,969 20,714

A25to34
490,825 86,536
137,330 44,040
158,945 887,738 125,794 1,331,293 670,230
83,627 1,009,900
280,350 251,227 1,324,556
74,615 347,400
80,508 474,021 1,100,437 132,730
95,880 565,454 372,536 232,443 497,263
52,859

A35to44
454,370 94,856
136,238 48,251
156,196 910,504 127,320 1,394,790 637,726
83,251 1,059,754
266,557 266,919 1,288,682
83,775 357,955
80,733 459,452 1,053,590 134,699
92,804 531,480 382,178 242,711 483,528
53,145

A45to54
395,626 73,526 98,945 49,077 94,268
705,604 94,373
1,103,058 523,682 56,215 865,805 233,933 224,214
1,002,535 73,597
263,798 53,059
388,946 840,761 106,448
57,274 468,056 319,725 184,384 372,939
45,541

A55to64
347,346 67,930 92,145 36,910 79,579
615,918 78,403
955,471 455,492
53,132 737,419 212,063 180,088 960,527
65,732 240,827
51,721 320,903 735,749
84,198 45,118 357,966 272,740 169,168 334,139 35,539

A65Plus
509,243 95,497
157,885 44,428
110,913 823,232 105,250 1,231,836 617,381
90,771 965,782 326,461 279,439 1,401,861
78,157 306,073
90,508 433,014 1,025,466 106,867
66,169 453,394 375,511 237,233 497,585
47,045

USA

58.38% 24,859,832 14,572,359 10,914,146 20,826,555 20,879,466 17,343,591 15,107,247 20,512,640

%ID_pop

57.2%

61.5%

48.3%

48.0%

55.6%

68.2%

71.7%

65.9%

Figure 29 Uniqueness of {Place, Gender, Date of birth} respecting age distribution, part 2

The next to last row in Figure 29 labeled "USA" reports the results of applying the 3 steps of experiment F to all places in the United States. As shown, 58.38% of the population of the United States is likely to be uniquely identified by values of {gender, date of birth, place}. The last row in Figure 29 labeled "%ID_pop" displays the percentage of people in each age subdivision who are likely to be uniquely identified by values of {gender, date of birth, place}. For example, it reports that 71.7% of the population of persons residing in the United States between the ages of 55 and 64 are likely to be uniquely identifiable based on {gender, date of birth, place}.
The place having the largest population was Chicago, Illinois, with 2,451,767 people. The place having the smallest population was Crooked Creek, Alaska that reports only one person of age 65 or more resides there. The average population for a place is 9,710 and the standard deviation is 44,149. There are a total of 25,585 places.

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5.5. Experiment J: Uniqueness of {county, gender, date of birth}

This experiment examines the identifiability of {date of birth, gender, county}. Recall, there are a total of 29,343 ZIP codes, 25,688 places and 3,141 counties.

Step 1. Use ZIP table for each of the 50 states and the District of Columbia. Step 2. Figure 12 contains the thresholds for Q={gender, date of birth} specific to each age subdivision. Step 3. Report statistical measurements computed from the table in step 1 using the thresholds determined in step 2. Figure 30 and Figure 31 report the results of applying the 3 steps of experiment J to each state, the District of Columbia and the entire United States.

The percentage of people residing in each locale likely to be uniquely identifiable by values of {gender, date of birth, county} appear in the column named “DOB %ID_pop.” For example, 58% of the population of Mississippi (see Figure 30) and 52% of the population of Nebraska (see Figure 31) are likely to be uniquely identifiable by values of {gender, date of birth, county}. Wyoming had the largest percentage of its population identifiable (75%). Connecticut, Delaware, the District of Columbia and New Jersey had 0% identified. The average was 28% and the standard deviation was 22%.

The next to last row in Figure 31 labeled "USA" reports the results of applying the 3 steps of experiment J to all counties in the United States. As shown, 18.1% of the population of the United States is likely to be uniquely identified by values of {gender, date of birth, county}. The last row in Figure 31 labeled "%ID_pop" displays the percentage of people in each age subdivision who are likely to be uniquely identified by values of {gender, date of birth, county}. For example, it reports that 25.84% of the population of persons residing in the United States between the ages of 55 and 64 are likely to be uniquely identifiable based on {gender, date of birth, county}.

State
AL AK AZ AR CA CO CT DE DC FL GA HI ID IL IN IA KS KY LA ME MD MA MI MN MS

DOB %ID_pop
31% 43%
5% 55%
2% 16%
0% 0% 0% 5% 36% 2% 50% 15% 33% 57% 45% 55% 26% 24% 6% 1% 14% 35% 58%

DOB Total
1,239,261 231,537 168,352
1,286,703 482,182 530,181 680,438
2,335,158 24,302
504,176 1,733,651 1,805,518 1,574,848 1,117,968 2,015,672 1,103,759
289,549 288,043
30,080 1,270,356 1,545,738 1,503,027

AUnder12
203,418 39,695 23,995
204,611 74,362 94,650 -
109,084 385,475
84,045 294,307 310,118 267,585 187,792 339,649 166,000 45,914 36,084
2,997 187,954 264,233 258,287

A12to18
119,887 25,282 13,659 126,862 42,716 50,001 74,526
236,121 4,985 54,338
164,151 183,259 153,138 105,602 199,166
99,616 25,233 19,602
1,179 101,271 169,559 160,447

A19to24
100,859 18,424 8,351 85,675 33,536 38,332 59,719
182,875 3,356
27,716 119,585 129,393 102,462
71,548 162,837
76,791 25,821 20,508
914 84,202 98,392 109,981

A25to34
147,718 47,769 15,873
165,982 62,826 85,809 96,106
311,416 -
64,270 237,212 268,623 208,798 150,530 287,814 129,159
33,214 36,667
2,739 147,645 209,122 202,539

A35to44
149,568 29,382 23,248
171,952 50,565 86,915 93,589
297,509 20
70,098 225,134 228,630 216,811 142,864 264,521 151,255
34,481 32,605
3,651 144,700 217,857 185,987

A45to54
145,639 31,533 23,557
153,203 61,321 60,219 80,169
294,860 5,039
61,874 210,334 204,738 168,181 128,522 239,055 132,897
37,839 29,983
8,515 167,106 169,995 179,021

A55to64
165,943 17,293 26,589
149,635 70,890 46,794 64,489
257,992 4,127
63,762 189,098 205,590 161,950 120,241 215,956 154,279
34,151 51,224
7,345 186,504 152,615 161,836

A65Plus
206,229 22,159 33,080
228,783 85,966 67,461 -
102,756 368,910
6,775 78,073 293,830 275,167 295,923 210,869 306,674 193,762 52,896 61,370
2,740 250,974 263,965 244,929

Figure 30 Uniqueness of {County, Gender, Date of birth} respecting age distribution, part 1

The county having the largest population was Los Angeles County in California, with 8,863,164 people. The county having the smallest population was Yellowstone County in

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Montana where only 52 people reside. The average population for a county is 79,182 and the standard deviation is 263,813. There are a total of 3,141 counties.

State
MO MT NE NV NH NJ NM NY NC ND OH OK OR PA RI SC SD TN TX UT VT VA WA WV WI WY

DOB %ID_pop
35% 58% 52% 17% 14%
0% 31%
4% 26% 63% 14% 44% 16%
7% 4% 23% 73% 37% 19% 17% 59% 35% 11% 59% 25% 75%

DOB Total
1,777,250 461,847 827,590 205,707 158,917 13,203 466,942 714,072
1,718,318 401,471
1,536,542 1,395,889
468,933 868,774
36,592 792,897 506,465 1,832,875 3,185,236 296,513 329,450 2,186,920 523,874 1,059,753 1,211,247 338,752

AUnder12
299,822 79,868
148,680 39,060 18,460 55,935 86,136
242,446 65,977
244,518 214,447
58,089 143,074
7,442 115,127
96,431 296,158 555,868
58,729 48,194 327,643 66,444 168,623 190,779 57,064

A12to18
177,231 50,920 81,858 19,336 14,248 0 41,285 44,198
149,044 37,393 135,966 135,344 37,189 81,634
4,146 71,978 52,085 180,822 314,582 33,397 35,514 195,729 57,010 100,661 110,977 36,055

A19to24
117,495 26,385 48,439 13,922 10,218 37,298 48,241
126,104 19,272
102,380 106,030
25,490 65,841
53,250 32,146 134,829 220,496 21,901 24,136 180,037 36,219 72,214 71,189 20,545

A25to34
235,542 52,524
114,003 34,721 17,034 48,782 39,884
202,459 49,281
185,611 180,771
51,118 120,867
100,618
70,960 239,766 408,489
43,107 42,551 286,163 58,899 144,775 162,807 52,035

A35to44
226,741 57,155
115,534 32,791 17,684 59,912 79,329
209,646 47,612
200,338 170,655
50,034 115,691
7,157 97,592 65,236 227,196 396,535 40,697 42,821 280,550 62,605 151,174 159,047 52,251

A45to54
199,449 54,121 80,505 23,853 29,898 7,089 68,042
130,425 232,090
47,773 199,829 171,464
77,348 110,104
5,220 104,465
51,201 226,279 357,970
30,917 44,422 300,469 75,825 140,705 141,883 38,218

A55to64
201,418 58,303 86,132 18,433 27,505 6,114 65,578
139,808 249,455
53,295 190,210 164,825
76,465 109,679
4,929 111,669
50,256 223,498 372,889
26,743 36,277 262,255 83,264 128,935 157,036 35,539

A65Plus
319,552 82,571
152,439 23,591 23,870 90,110
146,051 307,074
80,868 277,690 252,353
93,200 121,884
7,698 138,198
88,150 304,327 558,407
41,022 55,535 354,074 83,608 152,666 217,529 47,045

USA %ID_pop

18.1% 45,076,528 7,265,269 4,329,202 3,175,354 5,854,598 5,787,325 5,543,164 5,448,813 7,672,803

16.72% 18.27%

14.04%

13.48%

15.40%

21.79%

25.84%

24.65%

Figure 31 Uniqueness of {County, Gender, Date of birth} respecting age distribution, part 2

6. Discussion

Figure 32 contains a summary of the results reported in the previous section. A description of each reported percentage is provided in the following paragraphs. These percentages demonstrate how combinations of characteristics can combine to narrow the number of possible people under consideration as the subject of de-identified person-specific data.

County Place ZIP

18.1 58.4 87.1 DOB

0.04 3.6 3.7 Mon/Year

0.00004 0.04 0.04
BirthYear

0.00000* 0.01 0.01
2yr Age

Figure 32 Percentage of US population identified with gender as geography and age vary

Experiment B reported that 87.1% (216 million of 248 million) of the population in the United States had characteristics that were likely made them unique based only on {5-digit ZIP, gender, date of birth}. Experiment C reported that 3.7% of the population in the United States had characteristics that were likely made them unique based only on {5-digit ZIP, gender, Month and year of birth}. Experiment D reported that 0.04% of the population in the United States had characteristics that were likely made them unique based only on {5-digit ZIP, gender, Year of birth}. Experiment E reported that 0.01% of the population in the United States had characteristics that were likely made them unique based only on {5-digit ZIP, gender, 2year age range}.

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Experiment F reported that 58.4% of the population in the United States had characteristics that were likely made them unique based only on {Place, gender, date of birth}. Experiment G reported that 3.6% of the population in the United States had characteristics that were likely made them unique based only on {Place, gender, Month and year of birth}. Experiment H reported that 0.04% of the population in the United States had characteristics that were likely made them unique based only on {Place, gender, Year of birth}. Experiment I reported that 0.01% of the population in the United States had characteristics that were likely made them unique based only on {Place, gender, 2year age range}.
Experiment J reported that 18.1% of the population in the United States had characteristics that were likely made them unique based only on {County, gender, date of birth}. Experiment K reported that 0.04% of the population in the United States had characteristics that were likely made them unique based only on {County, gender, Month and year of birth}. Experiment L reported that 0.00004% of the population in the United States had characteristics that were likely made them unique based only on {County, gender, Year of birth}. Experiment M reported that 0.00000% of the population in the United States had characteristics that were likely made them unique based only on {County, gender, 2year age range}, but despite it being a very small number, it is not 0.∗
As the number of possible values a quasi-identifier can assume decreases, the percentage of the population in the United States who had characteristics that were likely unique based on those values decreases. This is evidenced by each row in Figure 32. Moving from left to right within each row of Figure 32, the numbers of possible combinations decrease and the corresponding percentages decrease. Aggregating the geographical specification to county resulted in far fewer possible combinations than available with place or ZIP codes. This is evidenced within each column in Figure 32. Notice however that the differences between the number of places and the number of ZIP codes are not as dramatic, and as a result, neither are the corresponding percentages.
6.1. Predicting the number of people that can be identified in a release
It was already shown that de-identified releases of person-specific data that contain no explicit identifiers such as name, address or phone number, is not necessarily anonymous [16]. The maximum number of patients who could be identified in a public or semi-public release of health data is the number of patients who were hospitalized and whose information is therefore included in the data. Many possible combinations of attributes can combine to form a quasiidentifier useful for linking the de-identified data to explicitly identified data. The number of hospitalizations reported in the IHCCCC's Rrod data (see Figure 2) in one year is estimated to be 1 million based on the average statistic that 1:12 people are hospitalized each year.
However, the actual number of patients that could be re-identified in publicly and semipublicly released health data is not necessarily every patient and the actual number is likely to differ among releases due to varying quasi-identifiers available. The results from the experiments reported in this document can help predict a minimum level of identifiability based on a combination of three demographics.

∗ In Loving County, Texas, 6 of 107 people are likely to be uniquely identified by values of {gender, 2yr age range, county}. All of these 6 people are between the ages of 12 and 18 years.

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6.1.1. Illinois Research Health Data

As shown in Figure 2, Rrod includes the full date of birth, gender, and the patient’s 5-digit residential ZIP. Figure 13 reports that 75.3% of the population of Illinois is likely to be uniquely identified by {5-digit ZIP, gender, date of birth}. That corresponds to 753,000 patients being identified per year in Rrod.
6.1.2. AHRQ’s State Inpatient Database

As shown in Figure 3, SID includes the month and year of birth, gender, and the patient’s 5-digit residential ZIP for some states. Figure 33 estimates that 112,595 patients per year are likely to be uniquely identified by {ZIP, Gender, Month and year of birth} in SID. The five states known to report the month and year of the birth date of each patient to SID were introduced in Error! Reference source not found.. The populations for each of these states according to the 1990 Census data [17] were reported in Figure 8 and Figure 9. It is estimated that 1:12 people are hospitalized each year. These values are summarized in Figure 33.

State Population Hospitalized Unique PopID

AZ 3,665,228

305,436 1.4% 4,276

IA 2,776,442

231,370 18.1% 41,878

NY 17,990,026 1,499,169 2.3% 34,481

OR 2,842,321

236,860 4.2% 9,948

WI 4,891,452

407,621 5.4% 22,012

Total per year 112,595

Figure 33 Estimated Uniqueness of {ZIP, Gender, Month and year of birth} in SID

State Population Hospitalized Unique

AZ 3,665,228

305,436 0.02%

CA 29,755,274 2,479,606 0.01%

CO 3,293,771

274,481 0.08%

FL 12,686,788 1,057,232 0.00%

IA 2,776,442

231,370 0.11%

MA 6,011,978

500,998 0.01%

MD 4,771,143

397,595 0.03%

NJ 7,730,188

644,182 0.01%

NY 17,990,026 1,499,169 0.03%

OR 2,842,321

236,860 0.07%

SC 3,486,703

290,559 0.01%

WA 4,866,692

405,558 0.03%

WI 4,891,452

407,621 0.02%

Total per year

PopID 61
248 220
42 255
50 119
64 450 166
29 122
82
1,907

Figure 34 Estimated Uniqueness of {ZIP, Gender, Year of birth} in SID

As shown in Figure 3, SID includes the year of birth (by way of age[18]), gender, and the patient’s 5-digit residential ZIP for some states. Figure 34 estimates that 1,907 patients per year are likely to be uniquely identified by {ZIP, Gender, Year of birth} in SID. The 13 states known to report the year of the birth date of each patient to SID were introduced in Error! Reference source not found.. The populations for each of these states according to the 1990 Census data [19] were reported in Figure 8 and Figure 9. It is estimated that 1:12 people are hospitalized each year. These values are summarized in Figure 34.

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There are many ways to misunderstand these values. These values are not to be considered an estimate of the uniqueness of Rrod or SID. There may exist other quasi-identifiers that may consist of more and different attributes that can link to other available data and thereby render the released health data even more identifiable. Such quasi-identifiers may use the hospital identifying number or discharge status or payment information. The estimates reported in this document are just approximations based on the demographic quasi identifiers stated. Therefore, these estimates should be viewed as a minimal estimate of the identifiability of these data. Clearly, these data are not anonymous.
6.2. Unique and unusual information found in data
A significant problem with producing anonymous data concerns unique and unusual information appearing within the data themselves. Instances of uniquely occurring characteristics found within the original data can be used by a reporter, private investigator and others to discredit the anonymity of the released data even when these instances are not unique in the general population. Unusual cases are often unusual in other sources of data as well making them easier to identify.
Importantly, close examination of the particulars of a database provides the best basis for determining uniquely identifying information and quasi-identifiers. In this document, I have examined outside information without examining the values of the released data themselves. The analysis is based on the fact that a combination of characteristics that makes one unique in a geographic population, for example, results in uniqueness in all other data that includes that geographic specification. An examination of the data however can reveal other kinds of unusual information that can be found in other sources of data making more patients easier to identify.
In an interview, for example, a janitor may recall an Asian patient whose last name was Chan and who worked as a stockbroker because the patient gave the janitor some good investing tips. Any single uniquely occurring value or group of values can be used to identify an individual. Remember that the unique characteristic may not be known beforehand. It could be based on diagnosis, treatment, birth year, visit date, or some other little detail or combination of details available to the memory of a patient or a doctor, or knowledge about the database from some other source.
As another example, consider the medical records of a pediatric hospital in which only one patient is older than 45 years of age. Suppose a de-identified version of the hospital’s records is to be released for public-use that includes age and city of residence but not birth date or zip code. Many may believe the resulting data would be anonymous because there are thousands of people of age 45 living in that city. However, the rare occurrence of a 45 year-old pediatric patient at that facility can become a focal point for anyone seeking to discredit the anonymity of the data. Nurses, clerks and other hospital personnel will often remember unusual cases and in interviews may provide additional details that help identify the patient.
6.3. Future Work
Below are proposed projects of varying degrees of difficulties and skill requirements that extend this work.

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In this document, I have demonstrated how combinations of characteristics can combine to narrow the number of possible people under consideration. However, knowing that there exist a one or a few people that share particular characteristics and explicitly identifying those people are not exactly the same. These combinations of characteristics must be linked to explicitly identified information to reveal the identities of the individuals. Further demonstrate the identifiability of these data by providing population registers to which the data could be linked to re-identify the noted individuals.
In an earlier document [20], privacy risk measures were computed on the data sets Rrod and SID based on the assumption that the entire populations within those data were identifiable. While that may be correct, use the findings reported in this document, which are based only on basic demographic attributes and do not include other attributes within those data that could be used for re-identification, and re-compute the measures of risk for those collections. Make an argument as to why these re-computed risk measurements should be considered "minimal" risk values.
7. References
1 National Association of Health Data Organizations, NAHDO Inventory of State-wide Hospital Discharge Data Activities (Falls Church: National Association of Health Data Organizations, May 2000).
2 Cambridge Voters List Database. City of Cambridge, Massachusetts. Cambridge: February 1997. 3 Supra note 1 NAHDO. 4 State of Illinois Health Care Cost Containment Council, Data release overview. (Springfield: State of
Illinois Health Care Cost Containment Council, March 1998). 5 Agency for Healthcare Research and Quality, Healthcare Cost and Utilization Project: Central
Distributor (April, 2000) available at http://www.ahcpr.gov/data/hcup/hcup-pkt.htm. 6 1990 U.S. Census Data, Database C90STF3B. U.S. Bureau of the Census. Available at
http://venus.census.gov and http://www.census.gov. Washington: 1993. 7 T. Dalenius. Finding a needle in a haystack – or identifying anonymous census record. Journal of
Official Statistics, 2(3):329-336, 1986. 8 G. Smith. Modeling security-relevant data semantics. In Proceedings of the 1990 IEEE Symposium on
Research in Security and Privacy, May 1990. 9 J. Ullman. Principles of Database and Knowledge Base Systems. Computer Science Press, Rockville,
MD. 1988. 10 Supra note 6 U.S. Bureau of the Census. 11 “Census Counts 90,” U.S. Bureau of the Census. (Available on CDROM.) Washington: 1993. 12 "1996 National Five-Digit ZIP Code and Post Office Directory," U.S. Postal Service. Washington:
1996. Also available at http://www.usps.gov. 13 Brualdi, R.A., Introductory Combinatorics, North-Holland, New York, 1977. 14 Supra note 5 AHRQ. 15 L. Sweeney. Inferences from unusual values in statistical data. Carnegie Mellon Data Privacy Center
Working Paper 3. 16 L. Sweeney. Weaving technology and policy together to maintain confidentiality. Journal of Law,
Medicine and Ethics, 25(2-3):98-110, 1997. 17 Supra note 6 and note 11 U.S. Census. 18 Supra section 4.4.1 Age versus Year of Birth 19 Supra note 6 and note 11 U.S. Census. 20 L. Sweeney. Towards all the data on all the people. Formal publication forthcoming. Earlier version
available as Carnegie Mellon Data Privacy Center Working Paper 2.

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Exhibit 4

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UNITED STATES DEPARTMENT OF COMMERCE Economics and Statistics Administration U.S. Census Bureau Was hington, DC 20233-000 1

January 19, 2018

MEMORANDUM FOR:

Wilbur L. Ross, Jr. Secretary of Commerce

Through:

Karen Dunn Kelley Performing the Non-Exclusive Functions and Duties of the Deputy Secretary

Ron S. Jarmin Performing the Non-Exclusive Functions and Duties of the Director

Enrique Lamas Performing the Non-Exclusive Functions and Duties of the Deputy Director

From:

John M. Abowd Chief Scientist and Associate Director for Research and Methodology

Subject:

Technical Review of the Department of Justice Request to Add Citizenship Question to the 2020 Census

The Department of Justice has requested block-level citizen voting-age population estimates by OMBapproved race and ethnicity categories from the 2020 Census of Population and Housing. These estimates are currently provided in two related data products: the PL94-171 redistricting data, produced by April 1st of the year following a decennial census under the authority of 13 U.S.C. Section 141, and the Citizen Voting Age Population by Race and Ethnicity (CVAP) tables produced every February from the most recent five-year American Community Survey data. The PL94-171 data are released at the census block level. The CVAP data are released at the census block group level.

We consider three alternatives in response to the request: (A) no change in data collection, (B) adding a citizenship question to the 2020 Census, and (C) obtaining citizenship status from administrative records for the whole 2020 Census population.

We recommend either Alternative A or C. Alternative C best meets DoJ’s stated uses, is comparatively far less costly than Alternative B, does not increase response burden, and does not harm the quality of the census count. Alternative A is not very costly and also does not harm the quality of the census count. Alternative B better addresses DoJ’s stated uses than Alternative A. However, Alternative B is very costly, harms the quality of the census count, and would use substantially less accurate citizenship status data than are available from administrative sources.

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Description
Impact on 2020 Census Quality of Citizen Voting-Age Population Data Other Advantages
Shortcomings

Summary of Alternatives

Alternative A

Alternative B

No change in data

Add citizenship

collection

question to the 2020

Census (i.e., the DoJ

request), all 2020

Census microdata

remain within the

Census Bureau

None Status quo
Lowest cost alternative

Major potential quality and cost disruptions Block-level data improved, but with serious quality issues remaining Direct measure of selfreported citizenship for the whole population

Citizen voting-age population data remain the same or are improved by using small-area modeling methods

Citizenship status is misreported at a very high rate for noncitizens, citizenship status is missing at a high rate for citizens and noncitizens due to reduced self-response and increased item nonresponse, nonresponse followup costs increase by at least $27.5M, erroneous enumerations increase, whole-person census imputations increase

Alternative C Leave 2020 Census questionnaire as designed and add citizenship from administrative records, all 2020 Census microdata and any linked citizenship data remain within the Census Bureau None
Best option for blocklevel citizenship data, quality much improved
Administrative citizenship records more accurate than selfreports, incremental cost is very likely to be less than $2M, USCIS data would permit record linkage for many more legal resident noncitizens Citizenship variable integrated into 2020 Census microdata outside the production system, Memorandum of Understanding with United States Citizen and Immigration Services required to acquire most up-to-date naturalization data

Approved: _______________________________ Date: __________ John M. Abowd, Chief Scientist and Associate Director for Research and Methodology

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Detailed Analysis of Alternatives
The statistics in this memorandum have been released by the Census Bureau Disclosure Review Board with approval number CBDRB-2018-CDAR-014.
Alternative A: Make no changes
Under this alternative, we would not change the current 2020 Census questionnaire nor the planned publications from the 2020 Census and the American Community Survey (ACS). Under this alternative, the PL94-171 redistricting data and the citizen voting-age population (CVAP) data would be released on the current schedule and with the current specifications. The redistricting and CVAP data are used by the Department of Justice to enforce the Voting Rights Act. They are also used by state redistricting offices to draw congressional and legislative districts that conform to constitutional equal-population and Voting Rights Act nondiscrimination requirements. Because the block-group-level CVAP tables have associated margins of error, their use in combination with the much more precise block-level census counts in the redistricting data requires sophisticated modeling. For these purposes, most analysts and the DoJ use statistical modeling methods to produce the block-level eligible voter data that become one of the inputs to their processes.
If the DoJ requests the assistance of Census Bureau statistical experts in developing model-based statistical methods to better facilitate the DoJ’s uses of these data in performing its Voting Rights Act duties, a small team of Census Bureau experts similar in size and capabilities to the teams used to provide the Voting Rights Act Section 203 language determinations would be deployed.
We estimate that this alternative would have no impact on the quality of the 2020 Census because there would be no change to any of the parameters underling the Secretary’s revised life-cycle cost estimates. The estimated cost is about $350,000 because that is approximately the cost of resources that would be used to do the modeling for the DoJ.
Alternative B: Add the question on citizenship to the 2020 Census questionnaire
Under this alternative, we would add the ACS question on citizenship to the 2020 Census questionnaire and ISR instrument. We would then produce the block-level citizen voting-age population by race and ethnicity tables during the 2020 Census publication phase.
Since the question is already asked on the American Community Survey, we would accept the cognitive research and questionnaire testing from the ACS instead of independently retesting the citizenship question. This means that the cost of preparing the new question would be minimal. We did not prepare an estimate of the impact of adding the citizenship question on the cost of reprogramming the Internet Self-Response (ISR) instrument, revising the Census Questionnaire Assistance (CQA), or redesigning the printed questionnaire because those components will not be finalized until after the March 2018 submission of the final questions. Adding the citizenship question is similar in scope and cost to recasting the race and ethnicity questions again, should that become necessary, and would be done at the same time. After the 2020 Census ISR, CQA and printed questionnaire are in final form, adding the citizenship question would be much more expensive and would depend on exactly when the implementation decision was made during the production cycle.
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For these reasons, we analyzed Alternative B in terms of its adverse impact on the rate of voluntary cooperation via self-response, the resulting increase in nonresponse followup (NRFU), and the consequent effects on the quality of the self-reported citizenship data. Three distinct analyses support the conclusion of an adverse impact on self-response and, as a result, on the accuracy and quality of the 2020 Census. We assess the costs of increased NRFU in light of the results of these analyses.
B.1. Quality of citizenship responses
We considered the quality of the citizenship responses on the ACS. In this analysis we estimated item nonresponse rates for the citizenship question on the ACS from 2013 through 2016. When item nonresponse occurs, the ACS edit and imputation modules are used to allocate an answer to replace the missing data item. This results in lower quality data because of the statistical errors in these allocation models. The analysis of the self-responses responses is done using ACS data from 2013-2016 because of operational changes in 2013, including the introduction of the ISR option and changes in the followup operations for mail-in questionnaires.
In the period from 2013 to 2016, item nonresponse rates for the citizenship question on the mail-in questionnaires for non-Hispanic whites (NHW) ranged from 6.0% to 6.3%, non-Hispanic blacks (NHB) ranged from 12.0% to 12.6%, and Hispanics ranged from 11.6 to 12.3%. In that same period, the ISR item nonresponse rates for citizenship were greater than those for mail-in questionnaires. In 2013, the item nonresponse rates for the citizenship variable on the ISR instrument were NHW: 6.2%, NHB: 12.3% and Hispanic: 13.0%. By 2016 the rates increased for NHB and especially Hispanics. They were NHW: 6.2%, NHB: 13.1%, and Hispanic: 15.5% (a 2.5 percentage point increase). Whether the response is by mail-in questionnaire or ISR instrument, item nonresponse rates for the citizenship question are much greater than the comparable rates for other demographic variables like sex, birthdate/age, and race/ethnicity (data not shown).
B.2. Self-response rate analyses
We directly compared the self-response rate in the 2000 Census for the short and long forms, separately for citizen and noncitizen households. In all cases, citizenship status of the individuals in the household was determined from administrative record sources, not from the response on the long form. A noncitizen household contains at least one noncitizen. Both citizen and noncitizen households have lower selfresponse rates on the long form compared to the short form; however, the decline in self-response for noncitizen households was 3.3 percentage points greater than the decline for citizen households. This analysis compared short and long form respondents, categories which were randomly assigned in the design of the 2000 Census.
We compared the self-response rates for the same household address on the 2010 Census and the 2010 American Community Survey, separately for citizen and noncitizen households. Again, all citizenship data were taken from administrative records, not the ACS, and noncitizen households contain at least one noncitizen resident. In this case, the randomization is over the selection of household addresses to receive the 2010 ACS. Because the ACS is an ongoing survey sampling fresh households each month, many of the residents of sampled households completed the 2010 ACS with the same reference address as they used for the 2010 Census. Once again, the self-response rates were lower in the ACS than in the 2010 Census for both citizen and noncitizen households. In this 2010 comparison, moreover, the decline in selfresponse was 5.1 percentage points greater for noncitizen households than for citizen households.
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In both the 2000 and 2010 analyses, only the long-form or ACS questionnaire contained a citizenship question. Both the long form and the ACS questionnaires are more burdensome than the shortform. Survey methodologists consider burden to include both the direct time costs of responding and the indirect costs arising from nonresponse due to perceived sensitivity of the topic. There are, consequently, many explanations for the lower self-response rates among all household types on these longer questionnaires. However, the only difference between citizen and noncitizen households in our studies was the presence of at least one noncitizen in noncitizen households. It is therefore a reasonable inference that a question on citizenship would lead to some decline in overall self-response because it would make the 2020 Census modestly more burdensome in the direct sense, and potentially much more burdensome in the indirect sense that it would lead to a larger decline in self-response for noncitizen households.
B.3. Breakoff rate analysis
We examined the response breakoff paradata for the 2016 ACS. We looked at all breakoff screens on the ISR instrument, and specifically at the breakoffs that occurred on the screens with the citizenship and related questions like place of birth and year of entry to the U.S. Breakoff paradata isolate the point in answering the questionnaire where a respondent discontinues entering data—breaks off—rather than finishing. A breakoff is different from failure to self-respond. The respondent started the survey and was prepared to provide the data on the Internet Self-Response instrument, but changed his or her mind during the interview.
Hispanics and non-Hispanic non-whites (NHNW) have greater breakoff rates than non-Hispanic whites (NHW). In the 2016 ACS data, breakoffs were NHW: 9.5% of cases while NHNW: 14.1% and Hispanics: 17.6%. The paradata show the question on which the breakoff occurred. Only 0.04% of NHW broke off on the citizenship question, whereas NHNW broke off 0.27% and Hispanics broke off 0.36%. There are three related questions on immigrant status on the ACS: citizenship, place of birth, and year of entry to the United States. Considering all three questions Hispanics broke off on 1.6% of all ISR cases, NHNW: 1.2% and NHW: 0.5%. A breakoff on the ISR instrument can result in follow-up costs, imputation of missing data, or both. Because Hispanics and non-Hispanic non-whites breakoff much more often than non-Hispanic whites, especially on the citizenship-related questions, their survey response quality is differentially affected.
B.4. Cost analysis
Lower self-response rates would raise the cost of conducting the 2020 Census. We discuss those increased costs below. They also reduce the quality of the resulting data. Lower self-response rates degrade data quality because data obtained from NRFU have greater erroneous enumeration and whole-person imputation rates. An erroneous enumeration means a census person enumeration that should not have been counted for any of several reasons, such as, that the person (1) is a duplicate of a correct enumeration; (2) is inappropriate (e.g., the person died before Census Day); or (3) is enumerated in the wrong location for the relevant tabulation (https://www.census.gov/coverage_measurement/definitions/). A whole-person census imputation is a census microdata record for a person for which all characteristics are imputed.
Our analysis of the 2010 Census coverage errors (Census Coverage Measurement Estimation Report: Summary of Estimates of Coverage for Persons in the United States, Memo G-01) contains the relevant data. That study found that when the 2010 Census obtained a valid self-response (219 million persons),
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the correct enumeration rate was 97.3%, erroneous enumerations were 2.5%, and whole-person census imputations were 0.3%. All erroneous enumeration and whole-person imputation rates are much greater for responses collected in NRFU. The vast majority of NRFU responses to the 2010 Census (59 million persons) were collected in May. During that month, the rate of correct enumerations was only 90.2%, the rate of incorrect enumeration was 4.8%, and the rate of whole-person census imputations was 5.0%. June NRFU accounted for 15 million persons, of whom only 84.6% were correctly enumerated, with erroneous enumerations of 5.7%, and whole-person census imputations of 9.6%. (See Table 19 of 2010 Census Memorandum G-01. That table does not provide statistics for all NRFU cases in aggregate.)
One reason that the erroneous enumeration and whole-person imputation rates are so much greater during NRFU is that the data are much more likely to be collected from a proxy rather than a household member, and, when they do come from a household member, that person has less accurate information than selfresponders. The correct enumeration rate for NRFU household member interviews is 93.4% (see Table 21 of 2010 Census Memorandum G-01), compared to 97.3% for non-NRFU households (see Table 19). The information for 21.0% of the persons whose data were collected during NRFU is based on proxy responses. For these 16 million persons, the correct enumeration rate is only 70.1%. Among proxy responses, erroneous enumerations are 6.7% and whole-person census imputations are 23.1% (see Table 21).
Using these data, we can develop a cautious estimate of the data quality consequences of adding the citizenship question. We assume that citizens are unaffected by the change and that an additional 5.1% of households with at least one noncitizen go into NRFU because they do not self-respond. We expect about 126 million occupied households in the 2020 Census. From the 2016 ACS, we estimate that 9.8% of all households contain at least one noncitizen. Combining these assumptions implies an additional 630,000 households in NRFU. If the NRFU data for those households have the same quality as the average NRFU data in the 2010 Census, then the result would be 139,000 fewer correct enumerations, of which 46,000 are additional erroneous enumerations and 93,000 are additional whole-person census imputations. This analysis assumes that, during the NRFU operations, a cooperative member of the household supplies data 79.0% of the time and 21.0% receive proxy responses. If all of these new NRFU cases go to proxy responses instead, the result would be 432,000 fewer correct enumerations, of which 67,000 are erroneous enumerations and 365,000 are whole-person census imputations.
For Alternative B, our estimate of the incremental cost proceeds as follows. Using the analysis in the paragraph above, the estimated NRFU workload will increase by approximately 630,000 households, or approximately 0.5 percentage points. We currently estimate that for each percentage point increase in NRFU, the cost of the 2020 Census increases by approximately $55 million. Accordingly, the addition of a question on citizenship could increase the cost of the 2020 Census by at least $27.5 million. It is worth stressing that this cost estimate is a lower bound. Our estimate of $55 million for each percentage point increase in NRFU is based on an average of three visits per household. We expect that many more of these noncitizen households would receive six NRFU visits.
We believe that $27.5 million is a conservative estimate because the other evidence cited in this report suggests that the differences between citizen and noncitizen response rates and data quality will be amplified during the 2020 Census compared to historical levels. Hence, the decrease in self-response for citizen households in 2020 could be much greater than the 5.1 percentage points we observed during the 2010 Census.
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Alternative C: Use administrative data on citizenship instead of add the question to the 2020 Census
Under this alternative, we would add the capability to link an accurate, edited citizenship variable from administrative records to the final 2020 Census microdata files. We would then produce block-level tables of citizen voting age population by race and ethnicity during the publication phase of the 2020 Census using the enhanced 2020 Census microdata.
The Census Bureau has conducted tests of its ability to link administrative data to supplement the decennial census and the ACS since the 1990s. Administrative record studies were performed for the 1990, 2000 and 2010 Censuses. We discuss some of the implications of the 2010 study below. We have used administrative data extensively in the production of the economic censuses for decades. Administrative business data from multiple sources are a key component of the production Business Register, which provides the frames for the economic censuses, annual, quarterly, and monthly business surveys. Administrative business data are also directly tabulated in many of our products.
In support of the 2020 Census, we moved the administrative data linking facility for households and individuals from research to production. This means that the ability to integrate administrative data at the record level is already part of the 2020 Census production environment. In addition, we began regularly ingesting and loading administrative data from the Social Security Administration, Internal Revenue Service and other federal and state sources into the 2020 Census data systems. In assessing the expected quality and cost of Alternative C, we assume the availability of these record linkage systems and the associated administrative data during the 2020 Census production cycle.
C.1. Quality of administrate record versus self-report citizenship status
We performed a detailed study of the responses to the citizenship question compared to the administrative record citizenship variable for the 2000 Census, 2010 ACS and 2016 ACS. These analyses confirm that the vast majority of citizens, as determined by reliable federal administrative records that require proof of citizenship, correctly report their status when asked a survey question. These analyses also demonstrate that when the administrative record source indicates an individual is not a citizen, the self-report is “citizen” for no less than 23.8% of the cases, and often more than 30%.
For all of these analyses, we linked the Census Bureau’s enhanced version of the SSA Numident data using the production individual record linkage system to append an administrative citizenship variable to the relevant census and ACS microdata. The Numident data contain information on every person who has ever been issued a Social Security Number or an Individual Taxpayer Identification Number. Since 1972, SSA has required proof of citizenship or legal resident alien status from applicants. We use this verified citizenship status as our administrative citizenship variable. Because noncitizens must interact with SSA if they become naturalized citizens, these data reflect current citizenship status albeit with a lag for some noncitizens.
For our analysis of the 2000 Census long-form data, we linked the 2002 version of the Census Numident data, which is the version closest to the April 1, 2000 Census date. For 92.3% of the 2000 Census longform respondents, we successfully linked the administrative citizenship variable. The 7.7% of persons for whom the administrative data are missing is comparable to the item non-response for self-responders in the mail-in pre-ISR-option ACS. When the administrative data indicated that the 2000 Census respondent was a citizen, the self-response was citizen: 98.8%. For this same group, the long-form response was
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noncitizen: 0.9% and missing: 0.3%. By contrast, when the administrative data indicated that the respondent was not a citizen, the self-report was citizen: 29.9%, noncitizen: 66.4%, and missing: 3.7%.
In the same analysis of 2000 Census data, we consider three categories of individuals: the reference person (the individual who completed the census form for the household), relatives of the reference person, and individuals unrelated to the reference person. When the administrative data show that the individual is a citizen, the reference person, relatives of the reference person, and nonrelatives of the reference person have self-reported citizenship status of 98.7%, 98.9% and 97.2%, respectively. On the other hand, when the administrative data report that the individual was a noncitizen, the long-form response was citizen for 32.9% of the reference persons; that is, reference persons who are not citizens according to the administrative data self-report that they are not citizens in only 63.3% of the long-form responses. When they are reporting for a relative who is not a citizen according to the administrative data, reference persons list that individual as a citizen in 28.6% of the long-form responses. When they are reporting for a nonrelative who is not a citizen according to the administrative data, reference persons list that individual as a citizen in 20.4% of the long-form responses.
We analyzed the 2010 and 2016 ACS citizenship responses using the same methodology. The 2010 ACS respondents were linked to the 2010 version of the Census Numident. The 2016 ACS respondents were linked to the 2016 Census Numident. In 2010, 8.5% of the respondents could not be linked, or had missing citizenship status on the administrative data. In 2016, 10.9% could not be linked or had missing administrative data. We reached the same conclusions using 2010 and 2016 ACS data with the following exceptions. When the administrative data report that the individual is a citizen, the self-response is citizen on 96.9% of the 2010 ACS questionnaires and 93.8% of the 2016 questionnaires. These lower selfreported citizenship rates are due to missing responses on the ACS, not misclassification. As we noted above, the item nonresponse rate for the citizenship question has been increasing. These item nonresponse data show that some citizens are not reporting their status on the ACS at all. In 2010 and 2016, individuals for whom the administrative data indicate noncitizen respond citizen in 32.7% and 34.7% of the ACS questionnaires, respectively. The rates of missing ACS citizenship response are also greater for individuals who are noncitizens in the administrative data (2010: 4.1%, 2016: 7.7%). The analysis of reference persons, relatives, and nonrelatives is qualitatively identical to the 2000 Census analysis.
In all three analyses, the results for racial and ethnic groups and for voting age individuals are similar to the results for the whole population with one important exception. If the administrative data indicate that the person is a citizen, the self-report is citizen at a very high rate with the remainder being predominately missing self-reports for all groups. If the administrative data indicate noncitizen, the self-report is citizen at a very high rate (never less than 23.8% for any racial, ethnic or voting age group in any year we studied). The exception is the missing data rate for Hispanics, who are missing administrative data about twice as often as non-Hispanic blacks and three times as often as non-Hispanic whites.
C.2. Analysis of coverage differences between administrative and survey citizenship data
Our analysis suggests that the ACS and 2000 long form survey data have more complete coverage of citizenship than administrative record data, but the relative advantage of the survey data is diminishing. Citizenship status is missing for 10.9 percent of persons in the 2016 administrative records, and it is missing for 6.3 percent of persons in the 2016 ACS. This 4.6 percentage point gap between administrative and survey missing data rates is smaller than the gap in 2000 (6.9 percentage points) and 2010 (5.6
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percentage points). Incomplete (through November) pre-production ACS data indicate that citizenship item nonresponse has again increased in 2017. There is an important caveat to the conclusion that survey-based citizenship data are more complete than administrative records, albeit less so now than in 2000. The methods used to adjust the ACS weights for survey nonresponse and to allocate citizenship status for item nonresponse assume that the predicted answers of the sampled non-respondents are statistically the same as those of respondents. Our analysis casts serious doubt on this assumption, suggesting that those who do not respond to either the entire ACS or the citizenship question on the ACS are not statistically similar to those who do; in particular, their responses to the citizenship question would not be well-predicted by the answers of those who did respond. The consequences of missing citizenship data in the administrative records are asymmetric. In the Census Numident, citizenship data may be missing for older citizens who obtained SSNs before the 1972 requirement to verify citizenship, naturalized citizens who have not confirmed their naturalization to SSA, and noncitizens who do not have an SSN or ITIN. All three of these shortcomings are addressed by adding data from the United States Citizen and Immigration Services (USCIS). Those data would complement the Census Numident data for older citizens and update those data for naturalized citizens. A less obvious, but equally important benefit, is that they would permit record linkage for legal resident aliens by allowing the construction of a supplementary record linkage master list for such people, who are only in scope for the Numident if they apply for and receive an SSN or ITIN. Consequently, the administrative records citizenship data would most likely have both more accurate citizen status and fewer missing individuals than would be the case for any survey-based collection method. Finally, having two sources of administrative citizenship data permits a detailed verification of the accuracy of those sources as well.
C.3. Cost of administrative record data production For Alternative C, we estimate that the incremental cost, except for new MOUs, is $450,000. This cost estimate includes the time to develop an MOU with USCIS, estimated ingestion and curation costs for USCIS data, incremental costs of other administrative data already in use in the 2020 Census but for which continued acquisition is now a requirement, and staff time to do the required statistical work for integration of the administrative-data citizenship status onto the 2020 Census microdata. This cost estimate is necessarily incomplete because we have not had adequate time to develop a draft MOU with USCIS, which is a requirement for getting a firm delivery cost estimate from the agency. Acquisition costs for other administrative data acquired or proposed for the 2020 Census varied from zero to $1.5M. Thus the realistic range of cost estimates, including the cost of USCIS data, is between $500,000 and $2.0M
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Questions on the Jan 19 Draft Census Memo on the DoJ Citizenship Question Reinstatement Request

1. With respect to Alternatives B and C, what is the difference, if any, between the time when the data collected under each alternative would be available to the public?

Since the collection of this data, whether from administrative records or from an enumerated question, occurs prior to the creation of the Microdata Detail File (MDF) from which all tabulations will be performed, there is no difference in the timing of when the data collected under either alternative B or C could be made available to the public. The exact date for completion of the MDF is still being determined as the 2020 Census schedule is matured. However, the 2020 Census is working towards publishing the first postapportionment tabulation data products as early as the first week of February 2021.
2. What is the “2020 Census publication phase” (page 1 of the Detailed Analysis for Alternative B) versus Alternative C? Would there be any difference?

The 2020 Census publication phase is a broad window stretching from the release of the apportionment counts by December 31, 2020 through the last data product or report published in FY 2023, the final year of decennial funding for the 2020 Census. However, as stated in the answer to question 1, these data could be made available to the public on the same schedule as any other post-apportionment tabulated data product regardless of whether alternative B or C is used in its collection.
3. What is the non-response rate for: (A) each question on the 2000 and 2010 Decennial Census short form and (B) each question on the 2010 ACS and most recent ACS?

The table below shows the item non-response (INR) rate for each question on the 2000 and 2010 Decennial Census short form. This is the percentage of respondents who did not provide an answer to an item.

Item Nonresponse Rates for 2000 and 2010 Short Form Person Questions

Relationship Sex

Age

Hispanic Race

Origin

2010 1.5
I I 2000 1.3

1.5

3.5

3.9

I I I 1.1

3.7

3.1

3.3
I 2.9 I

Source: Rothhaas, Lestina and Hill (2012) Tables

Tenure
4.5 4.1

Notes and Soucre: Rothhaas, C., Lestina, F. and Hill, J. (2012) “2010 Decennial Census Item Nonresponse and Imputation Assessment Report” 2010 Census Program for Evaluations and Experiments,
January 24, 2012.

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From report:
The INR rate is essentially the proportion of missing responses before pre-editing or imputation procedures for a given item (i.e., the respondent did not provide an answer to the item). For INR, missing values are included in the rates, but inconsistent responses (i.e., incompatible with other responses) are considered non-missing responses.
Online link to 2010 report that has 2000 information as well. https://www.census.gov/2010census/pdf/2010_Census_INR_Imputation_Assessment.pdf
See attached spreadsheet for the item allocation rates by questions for the ACS for 2010, 2013, and 2016.
4. What was the total survey response rate (i.e., percentage of complete questionnaires) for the 2000 long form and the 2000 short form? Of the incomplete long forms, what percentage left the citizenship question blank? Of the completed long forms, what percentage (if known) contained incorrect responses to the citizenship question?
We do not have measures of total survey response rates from the 2000 long form and 2000 short form available at this time. The mail response rate in 2000 was 66.4 percent for short forms and 53.9 percent for long forms. No analysis that we were aware of was conducted on the incomplete long forms that left the citizenship question blank. The Census 2000 Content Reinterview Survey showed low inconsistency of the responses to the citizenship question. Only 1.8 percent of the respondents changed answers in the reinterview.
Source for 2000 mail response rates: https://www.census.gov/pred/www/rpts/A.7.a.pdf
Source for 2000 Content Reinterview Survey. Page 32 source. https://www.census.gov/pred/www/rpts/B.5FR_RI.PDF
5. For the 2000 long and short forms, what was the percentage unanswered (left blank) for each question (i.e., what percentage of the responses for each question (sex, race, ethnicity, income, citizenship, etc.) were left blank)?
For the 2000 shortform, the table in question 3a provides the percentage unanswered for each question.
For the 2000 longform, Griffin, Love and Obenski (2003) summarized the Census 2000 longform responses. Allocation rates for individual items in Census 2000 were computed, but because of the magnitude of these data, summary allocation measures were derived.
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These rates summarize completeness across all data items for occupied units (households) and are the ratio of all population and housing items that had values allocated to the total number of population and housing items required to have a response. These composite measures provide a summary picture of the completeness of all data. Fifty-four population items and 29 housing items are included in these summary measures. The analysis showed that 9.9 percent of the population question items and 12.5 percent of the housing unit question items required allocation. Allocation involves using statistical procedures, such as within-household or nearest neighbor matrices, to impute missing values.
https://ww2.amstat.org/sections/srms/Proceedings/y2003/Files/JSM2003-000596.pdf
6. What was the incorrect response rate for the citizenship question that was asked on the Long Form during the 2000 Decennial Census? Does the response rate on the 2000 Long Form differ from the incorrect response rate on the citizenship question for the ACS?
In the 2000 long form, 2.3 percent of persons have inconsistent answers, 89.4 percent have consistent answers, and 8.2 percent have missing citizenship data in the SSA Numident and/or the 2000 long form. Among persons with nonmissing citizenship data in the SSA Numident and/or the 2000 long form, 2.6 percent have inconsistent answers and 97.4 percent have consistent answers.
In the 2010 ACS, 3.1 percent of persons have inconsistent answers, 86.0 percent have consistent answers, and 10.8 percent have missing citizenship data in the SSA Numident and/or the 2010 ACS. Among persons with nonmissing citizenship data in the SSA Numident and/or the 2010 ACS, 3.6 percent have inconsistent answers and 96.4 percent have consistent answers.
In the 2016 ACS, 2.9 percent of persons have inconsistent answers, 81.2 percent have consistent answers, and 15.9 percent have missing citizenship data in the SSA Numident and/or the 2016 ACS. Among persons with nonmissing citizenship data in the SSA Numident and/or the 2016 ACS, 3.5 percent have inconsistent answers and 96.5 percent have consistent answers.
These ACS and 2000 Census long form rates are based on weighted data.
This shows that inconsistent response rates are higher in the 2010 and 2016 ACS than in the 2000 long form.
7. What is the incorrect response rate on other Decennial or ACS questions for which Census has administrative records available (for example, age, sex or income)?
Table 7a shows the agreement rates between the 2010 Census response and the SSA Numident for persons who could be linked and had nonmissing values, and Table 7b shows
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the agreement rates between the 2010 ACS and the SSA Numident. Gender has low disagreement (0.4-0.5 percent), and white alone (0.9 percent), black alone (1.7-2 percent), and age (2.1 percent) also have low disagreement rates. Disagreement rates are greater for other races (e.g., 46.4-48.6 percent for American Indian or Alaska Native alone). Hispanic origin is not well measured in the Numident, because it contains a single race response, one of which is Hispanic.

Table 7a. Demographic Variable Agreement Rates Between the 2010 Census and the SSA Numident

2010 Census Response

Percent Agreement with SSA Numident

Hispanic

54.2

Not Hispanic

99.7

White Alone

99.1

Black Alone

98.3

American Indian or Alaska Native Alone

51.4

Asian Alone

84.3

Native Hawaiian or Other Pacific Islander

74.4

Alone

Some Other Race Alone

17.7

Age

97.9

Gender

99.4

Source: Rastogi, Sonya, and Amy O’Hara, 2012, “2010 Census Match Study,” 2010

Census Planning Memoranda Series No. 247.

Table 7b. Demographic Variable Agreement Rates Between the 2010 Census and the SSA

Numident

2010 ACS Response

Percent Agreement with SSA Numident

White Alone

99.1

Black Alone

98.0

American Indian or Alaska Native Alone

53.6

Asian Alone

82.9

Native Hawaiian or Other Pacific Islander

72.9

Alone

Some Other Race Alone

17.2

Age 0-2 Date of Birth

95.2

Age 3-17 Date of Birth

95.6

Age 18-24 Date of Birth

95.2

Age 25-44 Date of Birth

95.8

Age 45-64 Date of Birth

95.9

Age 65-74 Date of Birth

96.5

Age 75 and older Date of Birth

92.7

Male

99.5

Female

99.5

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Source: Bhaskar, Renuka, Adela Luque, Sonya Rastogi, and James Noon, 2014, “Coverage and Agreement of Administrative Records and 2010 American Community Survey Demographic Data,” CARRA Working Paper #2014-14.
Abowd and Stinson (2013) find correlations of 0.75-0.89 between Survey of Income and Program Participation (SIPP) and SSA Detailed Earnings Record annual earnings between 1990-1999.1
8. How does the Census presently handle responses on the (A) Decennial Census and (B) the ACS when administrative records available to the Census confirm that the response on the Decennial Census or ACS is incorrect? Is the present Census approach to incorrect responses based on practice/policy or law (statute or regulation)?
We have always based the short form Decennial Census and the ACS on self-response, and while we have procedures in place to address duplicate or fraudulent responses, we do not check the accuracy of the answers provided to the specific questions on the Census questionnaire. This is a long established practice at the Census Bureau that has been thoroughly tested and in place since 1970, when the Census Bureau moved to a mailout/respond approach to the Decennial Census. Title 13 of the U.S. Code allows the Census Bureau to use alternative data sources, like administrative records, for a variety of purposes, and we are using data in new ways in the 2020 Census. While this includes the use of administrative records data to fill in areas where a respondent does not provide an answer, we have not explored the possibility of checking or changing responses that a responding household has provided in response to the questionnaire.
9. Please explain the differences between the self-response rate analysis and the breakoff rate analysis. The range of breakoff rates between groups was far smaller than the range of self-response rates between groups.
Self-response means that a household responded to the survey by mailing back a questionnaire or by internet, and a sufficient number of core questions were answered so that an additional field interview was not required.
A breakoff occurs when an internet respondent stops answering questions prior to the end of the questionnaire. In most cases the respondent answers the core questions before breaking off, and additional fieldwork is not required. The breakoff rates are calculated separately by which question screen was the last one reached before the respondent stopped answering altogether.
The share of Hispanic respondents who broke off at some point before the end of the questionnaire (17.6 percent) is much higher than for non-Hispanic whites (9.5 percent).
1 Abowd, John M., and Martha H. Stinson, 2013, “Estimating Measurement Error in Annual Job Earnings: A Comparison of Survey and Administrative Data,” Review of Economics and Statistics, Vol. 95(55), pp. 1451-1467.
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Spreading the overall breakoff rates over 134 screens in the questionnaire works out to quite small rates per screen. It works out to an average breakoff rate of 0.131 percent per screen for Hispanics and 0.066 percent for non-Hispanic whites.
10. The NRFU numbers are comparatively small – approximately one additional household for NRFU per Census enumerator. Is this really a significant source of concern?
Yes, this is a significant concern. First, it gives rise to incremental NRFU cost of at least $27.5 million. This is a lower bound becaues it assumes the households that do not selfrespond because we added a question on citizenship have the same follow-up costs as an average U.S. household. They won't because these households overwhelmingly contain at least one noncitzen, and that is one of our acknowledged hard-to-count subpopulations.
11. Given that the breakoff rate difference was approximately 1 percent, why did Census choose to use the 5.1 percent number for assessing the cost of Alternative B?
If a household breaks off an internet response at the citizenship, place of birth, or year of entry screens, this means it would have already responded to the core questions. This would not trigger follow-up fieldwork and thus would not involve additional fieldwork costs. In contrast, if a household does not mail back a questionnaire or give an internet response, fieldwork will be necessary and additional costs will be incurred. Thus, the 5.1 percent number for differential self-response is more appropriate for estimating the additional fieldwork cost of adding a citizenship question.
12. Alternative C states that Census would use administrative data from the Social Security Administration, Internal Revenue Service, and “other federal and state sources.” What are the other sources?
In addition to continuing the acquisition of the Social Security Administration and Internal Revenue Service data, the Census Bureau is in discussion with the U.S. Citizen and Immigration Services (USCIS) staff to acquire additional citizenship data.
13. Is Census confident that administrative data will be able to be used to determine citizenship for all persons (e.g., not all citizens have social security numbers)?
We are confident that Alternative C is viable and that we have already ingested enough high-quality citizenship administrative data from SSA and IRS. The USCIS data are not required. They would, however, make the citizenship voting age tabulations better, but the administrative data we’ve got are very good and better than the data from the 2000 Census and current ACS. The type of activities required for Alternative C already occur daily and routinely at the Census Bureau. We have been doing this for business data products,
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including the Economic Censuses, for decades. We designed the 2020 Census to use this technology too.
14. For Alternative C, the memo says, “we assume the availability of these record linkage systems and associated administrative data” – does Census already have in place access to this data or would this need to be negotiated? If negotiated, for which data sets specifically?
The Census Bureau has longstanding contractual relationships with the Social Security Administration and the Internal Revenue Service that authorize the use of data for this project. For new data acquired for this project (i.e., USCIS) we would estimate a six-month development period to put a data acquisition agreement in place. That agreement would also include terms specifying the authorized use of data for this project.
15. Are there any privacy issues / sensitive information prohibitions that might prevent other agencies from providing such data?
There are no new privacy or sensitivity issues associated with other agencies providing citizenship data. We have received such information in the past from USCIS. We are currently authorized to receive and use the data from SSA and IRS that are discussed in Alternative C.
16. How long would Census expect any negotiation for access to data take? How likely is it that negotiations would be successful? Are MOA’s needed/required?
Current data available to the Census Bureau provide the quality and authority to use that are required to support this project. Additional information potentially available from USCIS would serve to supplement/validate those existing data. We are in early discussions with USCIS to develop a data acquisition agreement and at this time have no indications that this acquisition would not be successful.
17. What limitations would exist in working with other agencies like IRS, Homeland Security, etc. to share data?
The context for sharing of data for this project is for a one-way sharing of data from these agencies to the Census Bureau. Secure file transfer protocols are in-place to ingest these data into our Title 13 protected systems. For those data already in-place at the Census Bureau to support this project, provisions for sharing included in the interagency agreement restrict the Census Bureau from sharing person-level microdata outside the Census Bureau’s Title 13 protections. Aggregates that have been processed through the Bureau’s disclosure avoidance procedures can be released for public use.
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18. If Alternative C is selected, what is Census’s backup plan if the administrative data cannot be completely collected and utilized as proposed?
The backup plan is to use all of the administrative data that we currently have, which is the same set that the analyses of Alternative C used. We have verified that this use is consistent with the existing MOUs. We would then use estimation and modeling techniques similar to those used for the Small Area Income and Poverty Estimates (SAIPE) to impute missing citizenship status for those persons for whom we do not have administrative records. These models would also include estimates of naturalizations that occurred since the administrative data were ingested.
19. Does Census have any reason to believe that access to existing data sets would be curtailed if Alternative C is pursued?
No we do not believe that any access to existing data sets would be curtailed if we pursue Alternative C.
20. Has the proposed Alternative C approach ever been tried before on other data collection projects, or is this an experimental approach? If this has been done before, what was the result and what were lessons learned?
The approach in Alternative C has been routinely used in processing the economic censuses for several decades. The Bureau's Business Register was specifically redesigned for the 2002 Economic Census in order to enhance the ingestion and use of administrative records from the IRS and other sources. The data in these administrative records are used to substitute for direct responses in the economic censuses for the unsampled entities. They are also used as part of the review, edit, and imputation systems for economic censuses and surveys. On the household side, the approach in Alternative C was used extensively to build the residential characteristics for OnTheMap and OnTheMap for Emergency Management.
21. Is using sample data and administrative records sufficient for DOJ’s request?
The 2020 Census data combined with Alternative C are sufficient to meet DoJ's request. We do not anticipate using any ACS data under Alternative C.
22. Under Alternative C, If Census is able to secure interagency agreements to provide needed data sets, do we know how long it would take to receive the data transmission from other agencies and the length of time to integrate all that data, or is that unknown?
With the exception of the USCIS data, the data used for this project are already integrated into the 2020 Census production schema. In mid-to late 2018, we plan to acquire the USCIS data and with those data and our existing data begin to develop models and business rules to select citizenship status from the composite of sources and attach that characteristic to
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each U.S. person. We expect the development and refinement of this process to continue into 2019 and to be completed by third quarter calendar year 2019.
23. Cross referencing Census decennial responses with numerous governmental data sets stored in various databases with differing formats and storage qualities sounds like it could be complicated. Does Census have an algorithm in place to efficiently combine and cross reference such large quantities of data coming from many different sources? What cost is associated with Alternative C, and what technology/plan does Census have in place to execute?
Yes, the 2018 Census End-to-End test will be implementing processing steps to be able to match Census responses to administrative record information from numerous governmental data sets. The Census Bureau has in place the Person Identification Validation System to assign Protected Identification Keys to 2020 Census responses. The required technology for linking in the administrative records is therefore part of the 2020 Census technology. This incremental cost factored into the estimate for Alternative C is for integrating the citizenship variable specifically, since that variable is not currently part of the 2020 Census design. No changes are required to the production Person Identification Validation system to integrate the administrative citizenship data.
24. For section C-1 of the memo, when did Census do the analyses of the incorrect response rates for non-citizen answers to the long form and ACS citizenship question? Were any of the analyses published?
The comparisons of ACS, 2000 Decennial Census longform and SSA Numident citizenship were conducted in January 2018. This analysis has not been published.
25. Has Census corrected the incorrect responses it found when examining non-citizen responses? If not, why not?
In the American Community Survey (ACS), and the short form Decennial Census, we do not change self-reported answers. The Decennial Census and the ACS are based on selfresponse and we accept the responses provided by households as they are given. While we have procedures in place to address duplicate or fraudulent responses, we do not check the accuracy of the answers provided to the specific questions on the Census questionnaires. This is a long established process at the Census Bureau that has been thoroughly tested and in place since 1970, when the Census Bureau moved to a mail-out/respond approach to the Decennial Census.
26. Has the Department of Justice ever been made aware of inaccurate reporting of ACS data on citizenship, so that they may take this into consideration when using the data?
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Not exactly. The Census Bureau is in close, regular contact with the Department of Justice (DOJ) regarding their data requirements. Our counterparts at DOJ have a solid understanding of survey methodology and the quality of survey data, and they are aware of the public documentation on sampling and accuracy surrounding the ACS. However, the specific rate of accuracy regarding responses to the ACS question on citizenship has never been discussed.
27. Why has the number of persons who cannot be linked increased from 2010 to 2016?
The linkage between the ACS and administrative data from the SSA Numident and IRS ITIN tax filings depends on two factors: (a) the quality of the personally identifiable information (PII) on the ACS response and (b) whether the ACS respondent is in the SSN/ITIN universe.
With respect to the quality of the PII on the ACS, there may be insufficient information on the ACS due to item nonresponse or proxy response for the person to allow a successful match using the production record linkage system. There may also be more than one record in the Numident or ITIN IRS tax filings that matches the person’s PII. Finally, there may be a discrepancy between the PII provided to the ACS and the PII in the administrative records.
Alternatively, the person may not be in the Numident or ITIN IRS tax filing databases because they are out of the universe for those administrative systems. This happens when the person is a citizen without an SSN, or when the person is a noncitizen who has not obtained an SSN or ITIN.
Very few of the unlinked cases are due to insufficient PII in the ACS or multiple matches with administrative records. The vast majority of unlinked ACS persons have sufficient PII, but fail to match any administrative records sufficiently closely. This means that most of the nonmatches are because the ACS respondent is not in the administrative record universe.
The incidence of ACS persons with sufficient PII but no match with administrative records increased between 2010 and 2016. One contributing factor is that the number of persons linked to ITIN IRS tax filings in 2016 was only 39 percent as large as in 2010, suggesting that either fewer of the noncitizens in the 2016 ACS had ITINs, or more of them provided PII in the ACS that was inconsistent with their PII in IRS records.
28. Independent of this memo, what action does Census plan to take in response to the analyses showing that non-citizens have been incorrectly responding to the citizenship question?
The Census Bureau does not have plans to make any changes to procedures in the ACS. However, we will continue to conduct thorough evaluations and review of census and survey data. The ACS is focusing our research on the potential use of administrative records
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in the survey. For instance, we are exploring whether we can use IRS data on income to reduce the burden of asking questions on income on the ACS. We are concentrating initially on questions that are high burden, e.g., questions that are difficult to answer or questions that are seen as intrusive.
29. Did Census make recommendations the last time a question was added?
Since the short form Decennial Census was established in 2010, the only requests for new questions we have received have been for the ACS. And, in fact, requests for questions prior to 2010 were usually related to the Decennial Census Long Form. We always work collaboratively with Federal agencies that request a new question or a change to a question. The first step is to review the data needs and the legal justification for the new question or requested changes. If, through this process, we determine that the request is justified, we work with the other agencies to test the question (cognitive testing and field testing). We also work collaboratively on the analysis of the results from the test which inform the final recommendation about whether or not to make changes or add the question.
30. Does not answering truthfully have a separate data standard than not participating at all?
We’re not sure what you’re asking here. Please clarify the question.
31. What was the process that was used in the past to get questions added to the decennial Census or do we have something similar where a precedent was established?
Because no new questions have been added to the Decennial Census (for nearly 20 years), the Census Bureau did not feed bound by past precedent when considering the Department of Justices’ request. Rather, the Census Bureau is working with all relevant stakeholders to ensure that legal and regulatory requirements are filled and that questions will produce quality, useful information for the nation. As you are aware, that process is ongoing at your direction.
32. Has another agency ever requested that a question be asked of the entire population in order to get block or individual level data?
Not to our knowledge. However, it is worth pointing out that prior to 1980 the short form of the Decennial Census included more than just the 10 questions that have been on the short form since 1990.
33. Would Census linking of its internal data sets, with other data sets from places like IRS and Homeland Security, have an impact on participation as well (i.e., privacy concerns)?
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The potential that concerns about the use of administrative records could have an impact on participation has always been a concern of ours, and it’s a risk that we’re managing on our risk register. We’ve worked closely with the privacy community throughout the decade, and we established a working group on our National Advisory Committee to explore this issue. We’ve also regularly briefed the Congress about our plans. At this stage in the decade there does not appear to be extensive concerns among the general public about our approach to using administrative records in the Nonresponse Operation or otherwise. We will continue to monitor this issue. 34. Would Alternative C require any legislation? If so, what is the estimated time frame for approval of such legislation?
No. 35. Census publications and old decennial surveys available on the Census website show that
citizenship questions were frequently asked of the entire population in the past. Citizenship is also a question on the ACS. What was the justification provided for citizenship questions on the (A) short form, (B) long form, and (C) ACS? In 1940, the Census Bureau introduced the use of a short form to collect basic characteristics from all respondents, and a long form to collect more detailed questions from only a sample of respondents. Prior to 1940, census questions were asked of everyone, though in some cases only for those with certain characteristics. For example, in 1870, a citizenship question was asked, but only for respondents who were male and over the age of 21. Beginning in 2005, all the long-form questions – including a question on citizenship -- were moved to the ACS. 2010 was the first time we conducted a short-form only census. The citizenship question is included in the ACS to fulfill the data requirements of the Department of Justice, as well as many other agencies including the Equal Employment Opportunities Commission, the Department of Health and Human Services, and the Social Security Administration.
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ACS Item Allocation Rates for United States: 2016, 2013, 2010

Title Overall housing allocation rate

2016

2013

2010

occupied and vacant housing units

4.9

5.6

5.2

Overall person allocation rate

total population

9.5

8.4

5.8

Vacancy status

vacant housing units Tenure
occupied housing units

3.9

3.5

2.9

1.2

1.3

1.2

Units in structure

occupied and vacant housing units Year moved in

1.5

1.5

1.5

occupied housing units Month moved in

3

3

3.4

occupied housing units into which households move in the last two years

0.7

0.7

0.7

Year built

occupied and vacant housing units

18.2

17.1

16.2

Lot size

occupied and vacant single family and mobile homes

3.9

3.9

4.2

Agricultural sales

occupied and vacant single family and mobile homes with lot size greater

than or equal to 1 acre

4

4.2

4.4

Business on property

occupied and vacant single family and mobile homes

**

2.4

3

Number of rooms

occupied and vacant housing units

5

5.5

5.2

Number of bedrooms

occupied and vacant housing units

5.5

4.6

4.3

Running water

occupied and vacant housing units

2.4

2.1

2

Flush toilet

occupied and vacant housing units

**

2.2

2

Bathtub or shower

occupied and vacant housing units

2.6

2.2

2

Sink with a faucet

occupied and vacant housing units

2.6

2.2

2

Stove or range

occupied and vacant housing units

3.1

2.8

2.5

Refrigerator

occupied and vacant housing units

3.2

2.9

2.7

Telephone

occupied housing units

1.5

1.2

1.1

Number of vehicles

occupied housing units

1.2

1.4

1.3

Heating fuel

occupied housing units

3.4

3.4

3.3

Monthly electricity cost

occupied housing units

8.1

8.2

7.3

Monthly gas cost

occupied housing units

9.6

9.9

9.8

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Yearly water and sewer cost occupied housing units
Yearly other fuel cost occupied housing units
Yearly food stamp recipiency - household occupied housing units
Yearly real estate taxes owner-occupied housing units
Yearly property insurance owner-occupied housing units
Mortgage status owner-occupied housing units
Monthly mortgage payment owner-occupied housing units with a mortgage
Mortgage payment incl. real estate taxes owner-occupied housing units with a mortgage
Mortgage payment incl. insurance owner-occupied housing units with a mortgage
Second mortgage owner-occupied housing units
Home equity loan owner-occupied housing units
Other monthly mortgage payment(s)

8.5

8.8

8.1

7.3

8.3

10.6

1.7

1.7

1.3

16.7

18.5

16.3

23.9

25.6

23.2

2.2

2.5

2.1

10.5

12.4

10.7

6.2

6.9

(X)

6.8

7.4

(X)

3.2

3.7

3.4

3.7

4.3

4.2

owner-occupied housing units with second mortgage or home equity loan

23.3

21.7

17.9

Property value

owner-occupied housing units and vacant housing units for sale

11.6

12.9

12.3

Yearly mobile home costs

occupied mobile homes and other units

21.7

21.5

19.9

Monthly condominium fee

owner-occupied housing units

0.8

0.8

0.7

Monthly rent

occupied housing units rented for cash rent and vacant housing units for

rent

10.5

9.8

9.3

Meals included in rent

occupied housing units rented for cash rent and vacant housing units for

rent

2.1

2.1

2

Desktop/laptop/notebook computer

occupied housing units

1.3

3.2

**

Handheld computer/smart mobile phone

occupied housing units

**

3.3

**

Tablet or other portable wireless computer

occupied housing units

1.6

**

**

Smartphone

occupied housing units

1.6

**

**

Other computer

occupied housing units

1.7

3.7

**

Household has internet access

occupied housing units

3.3

4.4

**

Dial-up internet service

occupied housing units with internet access

3.8

5.7

**

DSL internet service

occupied housing units with internet access

**

5.7

**

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Cable modem internet service occupied housing units with internet access
Fiber-optic internet service occupied housing units with internet access
Cellular data plan (formerly mobile broadband) occupied housing units with internet access
Satellite internet service occupied housing units with internet access
High speed internet service occupied housing units with internet accesss
Some other internet service occupied housing units with internet access
Race total population
Hispanic origin total population
Sex total population
Age total population
Relationship total household population
Marital status total population 15 years and over
Married past 12 months total population 15 years and over, except those never married
Widowed past 12 months total population 15 years and over, except those never married
Divorced past 12 months total population 15 years and over, except those never married
Times married total population 15 years and over, except those never married
Year last married total population 15 years and over, except those never married
Place of birth total population
Citizenship total population
Year of naturalization total population naturalized citizens
Year of entry total population not born in US
Speaks another language at home total population 5 years and over
Language spoken

**

5.7

**

**

5.7

**

7.6

26.7

**

3.8

5.7

**

3.8

**

**

3.8

5.7

**

1.5

1.6

1.5

1.8

2.1

1.8

0.1

0.1

0.1

1.7

1.6

1.3

1.2

1.1

1.2

5.3

4.8

3

6.9

6.6

4.7

7.4

7

4.5

7.4

7

4.5

8.1

7.8

5.1

13.5

13.3

11.4

9.1

8.6

6.5

6

5.2

2.7

22.5

22.5

16.6

14.8

13.2

10.3

6.8

5.9

3.4

total population 5 years and over who speak another language at home

8.3

7

5.7

English ability

total population 5 years and over who speak another language at home

7.1

5.9

4

School enrollment

total population 3 years and over

6.7

6

3.7

Grade level attending

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total population 3 years and over enrolled Educational attainment
total population 3 years and over Field of degree

10.2

8.9

6

8.5

8

5.6

total population 25 years and over with a bachelor's degree or higher

13.5

12.4

9.8

Mobility status

total population 1 years and over

7.2

6.5

4

Migration state/foreign county

total population 1 years and over movers

13.2

11.3

7.1

Migration county

total population 1 years and over movers within US

14.6

12.5

8.3

Migration minor civil division

total population 1 years and over movers within US

14.2

12.1

8.4

Migration place

total population 1 years and over movers within US

15

12.9

8.8

Health insurance thru employer/union

total population

10.7

9

6.2

Health insurance purchased directly

total population

11.3

9.7

6.9

Health insurance through Medicare

total population

9.5

8.1

5.2

Health insurance through Medicaid

total population

12.2

10.5

7.9

Health insurance through TRICARE

total population

12.5

10.8

8.1

Health insurance through VA

total population

12.3

10.7

8.1

Health ins. thru Indian Health Service

total population

12.8

11.1

8.5

Visual difficulty

total population

7.1

6.1

3.4

Hearing difficulty

total population

6.8

5.9

3.2

Physical difficulty

total population 5 years and over

7.5

6.7

3.5

Difficulty remembering

total population 5 years and over

7.5

6.7

3.5

Difficulty dressing

total population 5 years and over

7.5

6.7

3.5

Difficulty going out

total population 16 years and over

7.3

6.5

3.4

Grandchildren living in home

noninstitutionalized population 30 years and over

1.1

1

0.9

Responsibility for grandchildren

noninstitutionalized population 30 years and over who are grandparents

with grandchildren in the home

17.7

15.7

12

Months responsible for grandchildren

noninstitutionalized population 30 years and over who are grandparents

with grandchildren in the home that have responsibility

17.2

16.1

14.9

Fertility status

female total population 15-50

7.8

6.7

3.7

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Veteran status

total population 17 years and over

7.3

6.8

3.8

Periods of military service

total population 17 years and over on active duty now or previously

9.7

9.3

6.3

Service-connected disability rating

total population 17 years and over, except those who never served in the

Armed Forces

6.8

6.6

3.9

Service-connected disability rating value

total population 17 years and over with a service-connected disability

0.2

0.2

0.7

Employment status recode

noninstitutionalized population 16 years and over

8.7

8.1

5.1

When last worked

noninstitutionalized population 16 years and over

9.6

9.1

5.7

Weeks worked in the past 12 months

noninstitutionalized population 16 years and over who worked in the past 12

months

10.6

9.7

6.9

Hours worked per week

noninstitutionalized population 16 years and over who worked in the past 12

months

11.9

10.8

7.7

Place of work state/foreign county

noninstitutionalized population 16 years and over at work last week Place of work county

11.8

10.4

6.3

noninstitutionalized population 16 years and over at work last week

12.5

11

7

Place of work minor civil division

noninstitutionalized population 16 years and over at work last week Place of work place

3.6

3.3

2.1

noninstitutionalized population 16 years and over at work last week Transportation to work

13.1

11.6

7.6

noninstitutionalized population 16 years and over at work last week

9.6

8.8

5.7

Carpool size

noninstitutionalized population 16 years and over at work last week who

drive to work

10.9

9.9

6.8

Time of departure

noninstitutionalized population 16 years and over at work last week who

don't work at home

20.2

18.5

12.8

Commuting time

noninstitutionalized population 16 years and over at work last week who

don't work at home

14.5

13.3

9.7

Class of worker

total population 16 years and over who worked in the last 5 years

11.7

10.7

7.2

Industry

total population 16 years and over who worked in the last 5 years

12.7

11.4

7.8

Occupation

total population 16 years and over who worked in the last 5 years

13.4

11.8

8.1

Wages/salary income

total population 15 years and over

19.1

19

16

Self-employment income

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total population 15 years and over Interest, dividends, etc. income
total population 15 years and over Social security or railroad retirement
total population 15 years and over Supplemental security income
total population 15 years and over Public assistance
total population 15 years and over Retirement income
total population 15 years and over Other income
total population 15 years and over Some or all income allocated
total population 15 years and over

10.5

9.3

5.9

15.2

12.6

8.8

14.5

12.3

8.9

12.7

10.3

6.7

13.2

10.5

6.8

13.6

11.1

7.5

13.2

10.8

7.4

28.4

25.3

22.4

Source: ACS 1-year data. See following links for more information: https://www.census.gov/acs/www/methodology/sample-size-and-data-quality/item-allocation-rates/

https://www.census.gov/programs-surveys/acs/methodology/sample-size-and-data-quality/item-allocation-rates-definitions.html Note: **X0AT This item was not asked in this year.

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Summary Analysis of the Key Differences Between Alternative C and Alternative D
This short note describes the Census Bureau’s current assumptions about two alternatives to address the need for block level data on citizen voting age populations. The goal is to measure the citizenship status of all people enumerated in the 2020 Decennial Census. Both alternatives utilize administrative data on the citizenship status of individuals, however one option, Alternative D, proposes to also include the current American Community Survey (ACS) question on citizenship status on the 2020 Decennial Census short form.
In both alternatives described here, the methodology requires linking 2020 census response data and administrative records. However, as illustrated both alternatives would also need to assign/impute citizenship for a portion of the population. The Census Bureau will have to assign citizenship in cases of questionnaire non-response and item non-response. Additionally, it is important to note, that even when a self-response is available it is not always possible to link response data with administrative records data. Poor data quality (e.g., name and age) and nonresponse or incomplete 2020 Census responses mean that we will not have a direct measure of citizenship status for all residents enumerated in 2020. The Census Bureau will to need employ an imputation model for these cases.
One of the key differences between to the two alternatives described below is the number of cases requiring imputation. The other key difference is the impact of errors in the citizenship status reported on the 2020 Census.
In the most recent version of the 2020 Decennial Life Cycle Cost Estimate, the Census Bureau projects counting 330 million residents in 2020. Figure 1 summarizes how citizenship status will be measured under Alternative C that does not employ a citizenship question on the 2020 Census. Figure 2 summarizes how this will be done using both administrative records and a 2020 citizenship question under Alternative D.
Alternative C is a simplified process for assigning citizenship through direct linkage and modelling, without including the question on the 2020 Census. The Census Bureau will link the responses for the 330 million census records to administrative records that contain information on the citizenship status of individuals. The Census Bureau expects to successfully link and observe this status for approximately 295 million people. The Census Bureau would need to impute this status for approximately 35 million people under Alternative C whose 2020 responses cannot be linked to administrative data. Although the Census Bureau has fully developed and tested the imputation model, it has high confidence that an accurate model can be developed and deployed for this purpose. Further, we will most likely never possess a fully adequate truth deck to benchmark it to.
Measuring citizenship status is slightly more complex under Alternative D where all U.S. households will be given the opportunity to provide the citizenship status of each household member. Based on response data for the ACS citizenship and other response data research, we know that not all households that respond to the 2020 Census will answer this question, leaving the question blank or with otherwise invalid responses. Additionally, Alternative D, must also account for those households that do not respond at all or will have proxy responses. Due to these reasons, we estimate that we will get 2020 citizenship status responses for approximately 294.6 million people, a slightly higher estimate
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than Alternative C. For the 35.4 million people without a 2020 citizenship response, the Census Bureau will employ the same methodology as in Alternative C, linking the 2020 Census responses to the administrative records. The Census Bureau estimates that it will be able to link these cases to administrative records where we observe citizenship status for approximately 21.5 million people. For the remaining 13.8 million will be imputed through a model as described above. Thus, there will be a need for imputing many cases across either alternative. The Census Bureau will link the 294.6 million records from the 2020 Census with the administrative records. This will be done both for potential quality assurance purposes and to improve the quality of future modeling uses. Based on the current research from the ACS, the Census Bureau expects to successfully link approximately 272.5 million of these cases. Of these, 263 million will have citizenship statuses that agree across the 2020 response and administrative record. The Census Bureau estimates there will be 9.5 million cases where there is disagreement across the two sources. Historic Census Bureau practice is to use self-reported data in these situations. However, the Census Bureau now knows from linking ACS responses on citizenship to administrative data that nearly one third of noncitizens in the administrative data respond to the questionnaire indicating they are citizens, indicating that this practice should be revisited in the case of measuring citizenship. Finally, for those 22.2 million cases that do not link to administrative records (non-linkage occurs for the same data quality reasons discussed above), the Census Bureau will use the observed 2020 responses. Again, Census Bureau expect some quality issues with these responses. Namely, the Census Bureau estimates that just under 500 thousand noncitizens will respond as citizens. The relative quality of Alternative C versus Alternative D will depend on the relative importance of the errors in administrative data, response data, and imputations. To be slightly more but not fully precise consider the following description of errors under both alternatives. First note that all possible measurement methods will have errors. Under Alternative C, there will be error in the administrative records, but we believe these to be relatively limited dues to the procedure following by SSA, USCIS and State. In both Alternative, the modeled cases will be subject to prediction error. Prediction error occur when the model returns the incorrect status of a case. As there are more models cases in Alternative C, prediction error will be a bigger issue there. Alternative D has an additional source or error, response error. This is where 2020 respondent give the incorrect status. Statisticians often hope these error are random and cancel out. However, we know from prior research that citizenship status responses are systematically biased for a subset of noncitizens. Response error is only an issue in alternative D. Unfortunately, the Census Bureau cannot quantify the relative magnitude of the errors across the alternatives at this time.
001305

Case 1:18-cv-02711-DLF Document 8-4 Filed 01/18/19 Page 172 of 178

Figure 1

Alternative C

j

CUn.11.&d~~
ensus
2020
330,000,000

7

Linked

Not linked

Adrec 295,000,000

Model 35 ,000,000

001306

Case 1:18-cv-02711-DLF Document 8-4 Filed 01/18/19 Page 173 of 178

Figure 2

l
r- 2020 C 1t1z e nsh 1p O bserv ed
294,600 ,000

111~
330,000 ,000
7
Not li nked

Alternative D
1

35,400,000

Not l inked

Ag ree

Disagree

2020 =Adrec

263 ,000 ,000

-- - ~- =-- I,._,..,.,... Census UIU!ltdst&tts

of~

9 ,500,000

l
2020 C 1t1zensh 1p
22 ,200 ,000

Adrec 21,500 ,000

Model 13,800 ,000

001307

Case 1:18-cv-02711-DLF Document 8-4 Filed 01/18/19 Page 174 of 178
UNITED STATES DEPARTMENT OF COMMERCE Economics and Statistics Administration U.S. Census Bureau Was hington, DC 20233-000 1

March 1, 2018

MEMORANDUM FOR:

Wilbur L. Ross, Jr. Secretary of Commerce

Through:

Karen Dunn Kelley Performing the Non-Exclusive Functions and Duties of the Deputy Secretary

Ron S. Jarmin Performing the Non-Exclusive Functions and Duties of the Director

Enrique Lamas Performing the Non-Exclusive Functions and Duties of the Deputy Director

From:

John M. Abowd Chief Scientist and Associate Director for Research and Methodology

Subject:

Preliminary analysis of Alternative D (Combined Alternatives B and C)

See attached.

Approved: _______________________________ Date: __________
John M. Abowd, Chief Scientist and Associate Director for Research and Methodology

001308census.gov

Case 1:18-cv-02711-DLF Document 8-4 Filed 01/18/19 Page 175 of 178
Preliminary Analysis of Alternative D
At the Secretary’s request we performed a preliminary analysis of combining Alternative B (asking the citizenship question of every household on the 2020 Census) and Alternative C (do not ask the question, link reliable administrative data on citizenship status instead) in the January 19, 2018 draft memo to the Department of Commerce into a new Alternative D. Here we discuss Alternative D, the weaknesses in Alternative C on its own, whether and how survey data could address these weaknesses, implications of including a citizenship question for using administrative data, and methodological challenges.
Description of Alternative D: Administrative data from the Social Security Administration (SSA), Internal Revenue Service (IRS), U.S. Citizenship and Immigration Services (USCIS), and the State Department would be used to create a comprehensive statistical reference list of current U.S. citizens. Nevertheless, there will be some persons for whom no administrative data are available. To obtain citizenship information for this sub-population, a citizenship question would be added to the 2020 Census questionnaire. The combined administrative record and 2020 Census data would be used to produce baseline citizenship statistics by 2021. Any U.S. citizens appearing in administrative data after the version created for the 2020 Census would be added to the comprehensive statistical reference list. There would be no plan to include a citizenship question on future Decennial Censuses or American Community Surveys. The comprehensive statistical reference list, built from administrative records and augmented by the 2020 Census answers would be used instead. The comprehensive statistical reference list would be kept current, gradually replacing almost all respondent-provided data with verified citizenship status data.
What are the weaknesses in Alternative C?
In the 2017 Numident (the latest available), 6.6 million persons born outside the U.S. have blank citizenship among those born in 1920 or later with no year of death. The evidence suggests that citizenship is not missing at random. Of those with missing citizenship in the Numident, a much higher share appears to be U.S. citizens than compared to those for whom citizenship data are not missing. Nevertheless, some of the blanks may be noncitizens, and it would thus be useful to have other sources for them.
A second question about the Numident citizenship variable is how complete and timely its updates are for naturalizations. Naturalized citizens are instructed to immediately apply for a new SSN card. Those who wish to work have an incentive to do so quickly, since having an SSN card with U.S. citizenship will make it easier to pass the E-Verify process when applying for a job, and it will make them eligible for government programs. But we do not know what fraction of naturalized citizens actually notify the SSA, and how soon after being naturalized they do so.
A third potential weakness of Numident citizenship is that some people are not required to have a Social Security Number (SSN), whether they are a U.S. citizen or not. It would also be useful to have a data source on citizenship that did not depend on the SSN application and tracking process inside SSA. This is why we proposed the MOU with the USCIS for naturalizations, and why we have now begun pursuing an MOU with the State Department for data on all citizens with passports.
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IRS Individual Taxpayer Identification Numbers (ITIN) partially fill the gap in Numident coverage of noncitizen U.S. residents. However, not all noncitizen residents without SSNs apply for ITINs. Only those making IRS tax filings apply for ITINs. Once again, it would be useful to have a data source that did not depend on the ITIN process. The USCIS and State Department MOUs would provide an alternative source in this context as well.
U.S. Citizenship and Immigration Services (USCIS) data on naturalizations, lawful permanent residents, and I-539 non-immigrant visa extensions can partially address the weaknesses of the Numident. The USCIS data provide up-to-date information since 2001 (and possibly back to 1988, but with incomplete records prior to 2001). This will fill gaps for naturalized citizens, lawful permanent residents, and persons with extended visa applications without SSNs, as well as naturalized citizens who did not inform SSA about their naturalization. The data do not cover naturalizations occurring before 1988, as well as not covering and some between 1988-2000. USCIS data do not always cover children under 18 at the time a parent became a naturalized U.S. citizen. Such children automatically become U.S. citizens under the Child Citizenship Act of 2000. The USCIS receives notification of some, but not all, of these child naturalizations. Others inform the U.S. government of their U.S. citizenship status by applying for U.S. passports, which are less expensive than the application to notify the USCIS. USCIS visa applications list people’s children, but those data may not be in electronic form.
U.S. passport data, available from the State Department, can help plug the gaps for child naturalizations, blanks on the Numident, and out-of-date citizenship information on the Numident for persons naturalized prior to 2001. Since U.S. citizens are not required to have a passport, however, these data will also have gaps in coverage.
Remaining citizenship data gaps in Alternative C include the following categories:
1. U.S. citizens from birth with no SSN or U.S. passport. They will not be processed by the production record linkage system used for the 2020 Census because their personally identifiable information won’t find a matching Protected Identification Key (PIK) in the Person Validation System (PVS).
2. U.S. citizens from birth born outside the U.S., who do not have a U.S. passport, and either applied for an SSN prior to 1974 and were 18 or older, or applied before the age of 18 prior to 1978. These people will be found in PVS, but none of the administrative sources discussed above will reliably generate a U.S. citizenship variable.
3. U.S. citizens who were naturalized prior to 2001 and did not inform SSA of their naturalization because they originally applied for an SSN after they were naturalized, and it was prior to when citizenship verification was required for those born outside the U.S. (1974). These people already had an SSN when they were naturalized and they didn’t inform SSA about the naturalization, or they didn’t apply for an SSN. The former group have inaccurate data on the Numident. The latter group will not be found in PVS.
4. U.S. citizens who were automatically naturalized if they were under the age of 18 when their parents became naturalized in 2000 or later, and did not inform USCIS or receive a U.S. passport. Note that such persons would not be able to get an SSN with U.S. citizenship on the card without either a U.S. passport or a certificate from USCIS. These people will also not be found in the PVS.
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5. Lawful permanent residents (LPR) who received that status prior to 2001 and either do not have an SSN or applied for an SSN prior to when citizenship verification was required for those born outside the U.S. (1974). The former group will not be found in PVS. The latter group has inaccurate data in Numident.
6. Noncitizen, non-LPR, residents who do not have an SSN or ITIN and who did not apply for a visa extension. These persons will not be found in PVS.
7. Persons with citizenship information in administrative data, but the administrative and decennial census data cannot be linked due to missing or discrepant PII.
Can survey data address the gaps in Alternative C?
One might think that survey data could help fill the above gaps, either when their person record is not linked in the PVS, and thus they have no PIK, or when they have a PIK but the administrative data lack up-to-date citizenship information. Persons in Category 6, however, have a strong incentive to provide an incorrect answer, if they answer at all. A significant, but unknown, fraction of persons without PIKs are in Category 6. Distinguishing these people from the other categories of persons without PIKs is an inexact science because there is no feasible method of independently verifying their non-citizen status. Our comparison of ACS and Numident citizenship data suggests that a large fraction of LPRs provide incorrect survey responses. This suggests that survey-collected citizenship data may not be reliable for many of the people falling in the gaps in administrative data. This calls into question their ability to improve upon Alternative C.
With Alternative C, and no direct survey response, the Census Bureau’s edit and imputation procedures would make an allocation based primarily on the high-quality administrative data. In the presence of a survey response, but without any linked administrative data for that person, the edit would only be triggered by blank citizenship. A survey response of “citizen” would be accepted as valid. There is no scientifically defensible method for rejecting a survey response in the absence of alternative data for that respondent.
How might inclusion of a citizenship question on the questionnaire affect the measurement of citizenship with administrative data? Absent an in-house administrative data census, measuring citizenship with administrative data requires that persons in the Decennial Census be linked to the administrative data at the person level. The PVS system engineered into the 2020 Census does this using a very reliable technology. However, inclusion of a citizenship question on the 2020 Census questionnaire is very likely to reduce the self-response rate, pushing more households into Nonresponse Followup (NRFU). Not only will this likely lead to more incorrect enumerations, but it is also expected to increase the number of persons who cannot be linked to the administrative data because the NRFU PII is lower quality than the self-response data. In the 2010 Decennial Census, the percentage of NRFU persons who could be linked to administrative data rate was 81.6 percent, compared to 96.7 percent for mail responses. Those refusing to self-respond due to the citizenship question are particularly likely to refuse to respond in NRFU as well, resulting in a proxy response. The NRFU linkage rates were far lower for proxy responses than selfresponses (33.8 percent vs. 93.0 percent, respectively).
Although persons in Category 6 will not be linked regardless of response mode, it is common for households to include persons with a variety of citizenship statuses. If the whole household does not self-
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Case 1:18-cv-02711-DLF Document 8-4 Filed 01/18/19 Page 178 of 178
respond to protect the members in Category 6, the record linkage problem will be further aggravated. Thus, not only are citizenship survey data of suspect quality for persons in the gaps for Alternative C, collecting these survey data would reduce the quality of the administrative records when used in Alternative D by lowering the record linkage rate for persons with administrative citizenship data. What methodological challenges are involved when combining these sources? Using the 2020 Census data only to fill in gaps for persons without administrative data on citizenship would raise questions about why 100 percent of respondents are being burdened by a citizenship question to obtain information for the two percent of respondents where it is missing. Including a citizenship question in the 2020 Census does not solve the problem of incomplete person linkages when producing citizenship statistics after 2020. Both the 2020 decennial record and the record with the person’s future location would need to be found in PVS to be used for future statistics. In sum, Alternative D would result in poorer quality citizenship data than Alternative C. It would still have all the negative cost and quality implications of Alternative B outlined in the draft January 19, 2018 memo to the Department of Commerce.
001312

 
 Case 1:18-cv-02711-DLF Document 8-5 Filed 01/18/19 Page 1 of 75
Exhibit 5

Case 1:18-cv-02711-DLF Document 8-5 Filed 01/18/19 Page 2 of 75
Version Number: 01-2017
U.S. Department of Commerce U.S. Census Bureau

Privacy Impact Assessment for the
CEN05 Field Systems Major Application System March 2018

Reviewed by:

~ Concurre nce of Senior Agency Official for Privacy/DOC Chief Privacy Officer

D Non-concurrence of Senior Agency Official for Privacy/DO C Chief Privacy Officer

CATRINA PURVIS

Digitally signed by CATRINA PURVIS DN: c=US, o=U.S. Government, ou=Department of Commerce, ou=Office of the Secretary, cn=CATRINA PURVIS, 0.9.2342.19200300.100.1.1=13001002875743

Date: 2018.06.22 13:49:29 -04'00'

Signature of Senior Agency Official for Privacy/DO C Chief Privacy Officer

Date

Case 1:18-cv-02711-DLF Document 8-5 Filed 01/18/19 Page 3 of 75
Version Number: 01-2017
U.S. Department of Commerce Privacy Impact Assessment U.S. Census Bureau/CEN05 Field Systems Major Application System
Unique Project Identifier: 006-000401400
Introduction: System Description
Provide a description of the system that addresses the following elements:
(a) The CEN0S Field Systems Major Application System is a major information system managed by the Application Development Services Division (ADSD) in support of the Census Bureau Field Directorate.
(b) The IT system is housed at the Census Bureau's Bowie, MD computer center. (c) CEN0S interconnects with other CENs. Desktop and laptop client services are provided
by CEN 17, server support is provided by CEN 16, and Oracle 12c database support is provided by CEN I 8. (d) How the system operates to achieve the purpose(s) identified in section 4: The Field Directorate plans , organizes, coordinates, and carries out the Census Bureau 's field data collection program for sample surveys, special censuses, the Economic Census, and the Decennial census. The CEN0S IT system maintains Personally Identifiable Information (Pll) collected from respondents for these surveys and censuses such as name, address, contact information, race, gender, education, financial information, etc. ln addition, Field Representative characteristics are also collected while surveys and census interviews are conducted .
Laptops are used to collect survey data in the field. An application assigns cases and monitors interviewing progress. Information systems covered by other CEN plans are used as routing mechanisms to transfer survey data from various survey sources, that includes but are not limited to, computer interviewing, telephone interviewing utilizing Census computer programs, internet self surveys, and paper surveys to the survey sponsors.
ln addition to laptops, the Field Directorate has begun utilizing both tablet and other mobile computing devices to perform Census Tests that lead up to the 2020 Decennial Census to collect respondent information using Census Bureau issued mobile devices.
The Customer Experience Management (CEM) System is a centralized data store from five data sources currently being utilized by the Census Bureau and will deploy an enterprise dashboard for Census Bureau leadership.
This dashboard will provide insights into custom er engagement for Census Bureau products & services, and will allow analysts to leverage data across data sources on a
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.Version Number: 01-201 7
holistic Business Intelligence (Bl) platform. The system will not only eliminate manual processes but will:
1) Create an opportunity for a better understanding of patterns and trends of customer experiences that can lead to actionable improvement plans, and;
2) Establish a framework and foundation for other data integration, Bl, and analytics efforts.
CEM will interface/collect information for various sources inside and outside of the Census Bureau and will contain PII data.
The Census Enterprise Data Collection and Processing initiative (CEDCaP) is a suite of systems and supporting infrastructure to handle data collection and processing for the nearly l 00 surveys and three censuses conducted by the Census Bureau. CEN0S is part of this infrastructure and includes the Enterprise Censuses and Surveys Enabling platform (ECaSE) which will provide about half the data collection capabilities for CEDCaP
The ECaSE - ISR (Internet Self-Response) secure Internet data exchange system is a web-based framework for the design, delivery, and execution of surveys, censuses, and other data collection and data exchange efforts over the Internet. The enterprise-level application offers data collection areas the ability to reach a large number of potential respondents online, in a customizable manner to suit their business needs. ECaSE - ISR is developed to support increased demand for online data collections, including the extreme ly high loads associated with the 2020 Decennial Census.
ECaSE - OCS (Operational Control System) will serve as the standard tool to assign, control, track, and manage listing, survey and census workloads for the field workforce. ECaSE - OCS provides an enterprise application framework for this need, regardless of the interviewer-assisted mode used (phone or in person).
To establish a cohesive system boundary for the purposes of security assessmen t, the CEN0S IT system is comprised of three major areas: Collections, Business Support Processes, and Backend Processes. Each of these major components employs security control mechanism s that must be individually documented to ensure that the system as a whole is appropriately protected. As such, the system security plan is organized to reflect the implementation of technical controls for each subsystem component.
ADSD incorporated a Survey Field Identificati on Tool (sFIT) to aid in investigating situations where it is suspected that a Field Representative may be falsifying respondent information. The tool will be used by Contact Center and Regional Office (RO) representatives to indicate FR who are suspected of falsification and to facilitate and document the results of the investigations. The newly developed tool replaced the previou s automated system and the paper 11-163 forms. sFIT collects and disseminates PII regarding a survey respondent and the Field Representative who is suspected of falsifying survey data. sFIT received its Authority to Operate (ATO) on 7/13/2017.
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(e) How information in the system is retrieved by the user
There are many external sponsors but CEN0S does not have direct connections to any of them . Demographics Survey Division (DSD), Econ, etc., will give CEN0S the surveys that they have crafted for the external sponsors and the data collected for those surveys is placed into the CEN0S Master Control System (MCS) for the internal system to pick up. It will be the other internal sponsors' responsibility to vet the information, transfonn it into a format that the external sponsors can ingest and send it off. The sharing of the data should be on those systems with the external connection to the external sponsors. This is the same with the National Center for Health Statistics (NCHS) survey.
(0 How information is transmitted to and from the system
The CEN0S IT system includes a data warehouse that extracts and provides a view of survey data over time, data collection modes, and data collection operations. It aggregates data and creates canned reports. These reports are mad e available to stakeholders, approved individuals, and organizations to support optimization and coordination of decennial, current, and special surveys. The reports are developed by a special staff that was established through the Office of the Director to serve as an analytic team with specific, ongoing, responsibilities to develop analytic tools (charts and tables). These tools will be used by decennial and current survey field managers toward the goal of continuous improvement in . survey operational efficiency. This group will both initiate and respond to issues related to survey performance indicators including cost, data quality, and data collection progress . This databas e interfaces with systems throughout the Census Bureau that contain PII, Business Identifiable Information (BIi), and data collected and/or protected under Title 13 and Title 26.
(g) Any information sharing conducted by the system
The CEN0S IT system only shares PII and BIi data within other CEN05 systems/components and with other Census Bureau TTsystems. The data warehouse provides the ability for survey sponsors to view statistical data. It does not allow access to the information at the individual case level where the "raw" data resides. The data warehouse interacts with multiple systems within the Census Bureau netwo rk such as the system that contains information about businesses , which provides the mailing list for the Economic Census, and the primary sampling frame for virtually all other business surveys. The survey information about businesses is collected to track the movement of commodities from businesses throughout the United States. The data will be stored in its "raw" form and then transformed and stored in the data warehouse. The data warehouse will tabulate the data and display it in various reports. The data in its "raw" forn1 will not be displayed. The data warehouse maintains PII, BIi, Title 13 and Title 26 information.
(h) The specific programmatic authoriti es (statutes or Executive Orders) for collecting, maintaining, using, and disseminating the information
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15 U.S.C. 301. 13 U.S.C. Chapter 5, 6(c), 8(b), 131, 132, 141, 161, 182, 193, 196 18 U.S.C. 2510-2521 15 CFR, Part 50. 26 U.S.C.

(i) The Federal Information Processing Standards (FIPS) 199 security impact category for the system The Federal Information Processing Standard (FIPS) 199 security impact category for this system is Moderate.

Section 1: Status of the Information System 1.1 Indicate whether the information system is a new or existing system.

_____ This is a new information system. _____ This is an existing information system with changes that create new privacy risks.
(Check all that apply.)

Changes That Create New Privacy Risks (CTCNPR)

a. Conversions

d. Significant Merging

b. Anonymous to Non-

e. New Public Access

Anonymous

c. Significant System

f. Commercial Sources

Management Changes

j. Other changes that create new privacy risks (specify):

g. New Interagency Uses h. Internal Flow or
Collection i. Alteration in Character
of Data

__X_ This is an existing information system in which changes do not create new privacy risks, and there is a SAOP approved Privacy Impact Assessment.

Section 2: Information in the System

2.1 Indicate what personally identifiable information (PII)/business identifiable information (BII) is collected, maintained, or disseminated. (Check all that apply.)

Identifying Numbers (IN)

a. Social Security*

X e. File/Case ID

b. Taxpayer ID

f. Driver’s License

c. Employer ID

g. Passport

d. Employee ID

X h. Alien Registration

m. Other identifying numbers (specify):

X i. Credit Card j. Financial Account k. Financial Transaction l. Vehicle Identifier

*Explanation for the need to collect, maintain, or disseminate the Social Security number, including truncated form:

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I) Employee's full SSN info needed for cost reimbursement and other financial purposes. 2) The last 4 digits of the survey respondent's SSN helps is collected on behalf of the survey sponsor, The National Center for Health Statistics (NCHS). The justification for the necessity of collecting this information, taken from the latest approved Office of Management and Budget (0MB) Information Collection Request (ICR) supporting statement is below:
Social Security Number and Health Insurance Claim Number: The last four digits of the Social Security Number (SSN) is asked on the NHIS questionnaire to allow linkage with administrative and vital records, such as the National Death Index (NDI). The N DI is a computerized central file of death record information. It is compiled from data obtained by NCHS from the State vital statistics offices. The data contain a standard set of identi-fying information on decedents from 1979 to the present. Records are matched using Social Security Number and other variables such as name, father's surname, date of birth, sex, state ofresi-dence, and marital status. Of these, Social Security Number is the most important identifier for successful matching. The last four digits has been shown to be nearly as effective for matching as the full number.
The Social Security Number is also used by the Medical Expenditure Panel Study to help track the location of respondents who have changed residence since their NHIS interview. Finding a correct address for respondents is essential to maintaining response levels at an acceptable level in linked surveys, and the Social Security Number is a key item for establishing a correct address .
Medicare beneficiaries are given a health insurance claim (HIC) number that is their (or their spouse's) SSN with an alphabetic prefix . The NHJ S also asks for the last four digits of that number so that the NHIS data can be linked to Medicare claims informat ion for purpo ses of stati stic al research.

General Personal Data (GPD)

a. Name

X g. Date of Birth

b. Maiden Name

X h. Place of Birth

C. Alia s

X i. Hom e Addr ess

d. Ge nder

X i. Telephone Num ber

e. Age

X k . Emai l Address

f. Race/Et hni city

X I. Education

s. Other general personal data (spec ify):

X m. Re ligion

X n. Financial Information

X

X 0. Medical Information

X

X P. Military Ser vice

X

X Q. Physical Characteristi cs
xx X r. Moth er's Maiden Name

Work-Related Data (WRD)

a. Occupation

X d. Telephone Number

b. Job Tit le

X e. Email Address

C. Work Address

X f. Business Associate s

i. Other work-related data (specify):

X g. Salary

X

X X

h.

Work History
~

--

xx

Distini?uishinl! Features/Biometrics (DFB)

a . Finge rprint s

d. Photographs

b. Palm Prints

e . Scars , Mark s, Tattoos

C. Voice

f. Vasc ular Scan

Recor din g/Sig natures

J. Other distinguishing features/ biometric s (spec ify):

g. DNA Profiles h. Retina/Iris Scans i. Dental Profile

System Administration/ Audit Data SAAD)

a. User ID

Ix C. Date/Ti me of Access

Ix Ie. ID Files Accessed

Ix

b. IP Address

Ix d. Que ries Run

Ix Ir. Co ntent s of Files

Ix

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VersionNumber: 01-2017 g. Other system administration/audit data (specify):
I Othe, lnfo,mation (spodfy)

2.2 Indicate sources of the PII/BII in the system. (Check all that apply.)

Directlv from Individual about Whom the Information Pertains

In Person

IX I Hard Coov: Mail/Fax

I I Online

Ix

Telephone

I X I Email

Ix I

I

Other (specify):

Government Sources Within the Bureau State, Local, Tribal Other (specify):

IX I Other DOC Bureaus IX I Foreign

I I Other Federal Agencies

Ix

I I

I

Non-government Sources

Public Organizations

I

Third Party Website or Application

Other (specify):

I Private Sector

Ix I Commercial Data Brokers Ix

I I

I

2.3 Describe how the accuracy of the information in the system is ensured.
It will be the internal sponsors ' responsibility to vet the information, transform it into a fonnat that the external sponsors can ingest and send it off. The sharing of the data should be on those systems with the external connection to the external sponsors.

2.4 ls the information covered by the Paperwork Reduction Act?
Yes, the information is covered by the Paperwork Reduction Act. Provide the 0MB control number and the agency number for the collection.
X No, the information is not covered by the Paperwork Reduction Act.

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2.5 Indicate the technologies used that contain PII/B11in ways that have not been previously deployed. (Check all that apply.)

Technolo ies Used Containin Smart Cards Caller-ID Other (specify):

PII/B11 Not Previous!

De lo ed TUCPBNPD Biometrics Personal ldenti Verification (PIV Cards

X There are not an technolo ies used that contain PII/BJI in wa s that have not been reviousl de lo ed.

Section 3: System Supported Activities

3.1 Indicate IT system supported activities which raise privacy risks/concerns. (Check all that apply.)

Activities Audio recordings Video surveillance Other (specify):

Ix I Building entrv readers

I

I I Electronic purchase transactions

I

I There are not any IT system supported activ ities which raise privacy risks/concerns.

Section 4: Purpose of the System

4.1 Indicate why the PII/B11in the IT system is being collected, maintained, or disseminated. (Check all that apply.)

Purpose For a Computer Matching Program For administrative matter s For litigation For civil enforcement activitie s To improve Federal services online For web measurement and customization technologies (single-session ) Other (specify):

For adminis tering human resources programs

X To promote information sharing initiatives

For criminal law enfo rcement activities

For intelligence activities

For emolovee or customer satisfaction

X

For web measurement and customization

technologies (multi-ses sion)

Section 5: Use of the Information 5.1 In the context of functional areas (business processes , missions, operations, etc .) supported
by the IT system, describe how the PII/B11that is collected , maintained , or disseminated will be used. Indicate if the PII/BII identified in Section 2.1 of this document is in
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reference to a federal employee/contractor, member of the public , foreign national, visitor or other (specify).
Census Bureau information shapes important policy and operational decisions that help improve the nation's social and economic conditions. We conduct the constitutionally mandated Census of Population and Housing every 10 years, which is used to apportion seats in the House of Representatives and informs congressional redistricting. We also conduct a census of all business establishments and of all governmental units, known respectively as the Economic Census and the Census of Governments, every five years. The Economic Census is the benchmark used for measuring Gross Domestic Product (GDP) and other key indicators that guide public policy and business investment decisions. In addition, we conduct several ongoing business and household surveys that provide the information in several of the Nation's key economic indicators and which is used to allocate over $400 billion in Federal funding annualJy. The Pll/BII collected for statistical purposes: The PII/BJI maintained is from voluntary and mandatory surveys, census interviews , pilot tests and cognitive interviews collected from members of the public. The PII collected for administrative purposes: We collect information about Census Bureau employees during the collection of respondent information. Field representative and interviewer characteristics obtained during census and survey interviews, pilot tests, and cognitive interviews are used for research and analytical studies to evaluate Census Bureau surve s and ro rams.
5.2 Describe any potential threats to privacy as a result of the bureau's/operating unit's use of the information, and controls that the bureau/operating unit has put into place to ensure that the information is handled, retained, and disposed appropriately. (For example: mandatory training for system users regarding approp riate handlin g of information, automatic purging of information in accordance with the retention schedule, etc.)
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The Census Bureau Information technology systems employ a multitude of layered security controls to protect BII/PII at rest, during processing, as well as in transit. These NIST 800-53 controls, at a minimum, are deployed and managed at the enterprise level including , but not limited to the following:
• Intrusion Detection IPrevention Systems (IDS IIPS)
• Firewalls • Mandatory use of HTTP(S) for Census Bureau Public facing websites • Use of trusted internet connection (TIC) • Anti-Virus software to protect host/end user systems • Encryption of databases (Data at rest) • HSPD-12 Compliant PIV cards • Access Controls The Census bureau Information technology systems also follow the National Institute of Standards and Technology (NIST) standards including special publications 800-53, 800-63, 800-37 etc. Any system within the Census Bureau that contains, transmits, or processes BII/PII has a current authority to operate (ATO) and goes through continuous monitoring on a yearly basis to ensure controls are implemented and operating as intended. The Census Bureau also deploys a Data Loss Prevention solution as well.
All Bureau employee s and contractors undergo mandatory annual data stewardship training to includ e proper handling, dissemination, and disposal of BII/PII/Title 13/Title 26 data.
Section 6: Information Sharing and Access
6.1 Indicate with whom the bureau intends to share the PII/BII in the IT system and how the PII/BII will be shared. (Check all that apply.)

Recipient
Within the bureau DOC bureaus Federa l agencies State, local, tribal gov't agencies Public Private sector Foreign government s Foreign ent ities Other (specify):

How Information will be Shared

Case-by-Case

Bulk Transfer

Direct Access

X

X

X

I The PII/811 in the system will not be shared.

6.2 Indicate whether the IT system connects with or receives information from any other IT systems authorized to process PII and/or BIi.

X Yes, this IT system connects with or receives information from another IT system(s) authorized to process PII and/or BIL Provide the name of the IT system and describe the technical contro ls which prevent PH/BU leakage.:

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CEN03, CEN04 CBS, CEN06 NPC, CEN 11, CEN 13, CEN22, CEN35, CEN36
CEN05 uses a multitude of security controls mandated by the Federal Information Security Management Act of2002 (FISMA) and various other regulatory control frameworks including the National Institute of Standards and Technology (NIST) special publication 800 series. These security controls include, but are not limited to the use of mandatory HTTPS for public facing websites, access controls, anti-virus solutions , enterprise auditing/monitoring, encryption of data at rest, and various physical controls at the Census Bureau facilities that house Information Technology systems. The Census Bureau also deploys an enterprise Data Loss Protection (OLP) solution as well. No, this IT system does not connect with or receive information from another IT system(s) authorized to process PI! and/or BIL

6.3 Identify the class of users who will have access to the IT system and the PII/B11. (Check all that apply.)

Class of Users General Public Contractors Other (specify):

I I Government Employees

Ix

Ix I

I

Section 7: Notice and Consent

7.1 Indicate whether individuals will be notified if their PIVBJI is collected, maintained, or disseminated by the system. (Check all that apply.)

X Yes , notice is provided pursuant to a system of reco rds notice published in the Federal Register and

discussed in Section 9.

X Yes, notice is provided by a Privacy Act statement and/or privacy policy. The Privacy Act stateme nt

and/or privacy policy can be found at:

X Yes, notice is provided by other means. Specify how: as specified in some survey instrument(s),

respondent letters, etc.

No, notice is not provided .

Specify why not:

7.2 Indic ate whether and how individuals have an opportunity to decline to provide PII/B11.

X Yes, individuals have an opportunity to Specify how: For voluntary surveys or censuses, the

decline to provid e PU/BIi.

respondent has an oonortunity to decline to provide PII/Bll.

X No , individuals do not have an

Specify why not: For mandatory surveys or censuses , the

opportunity to decline to provide

respondent does not have an opportunity to decline to provide

PII/BII .

Pll/BII

7.3 Indicate whether and how individuals have an opportunity to consent to particular uses of their PII/BII.

X Yes , individua ls have an opportunity to Specify how: For Employee Productivity Measurement

consent to particular uses of their

Records the consent is requir ed for employmen t

PII/BII.

X No, individuals do not have an

Specify why not: As identified in the applicable SORNs

opportunity to consent to particular

Census -3, -4, -5, and -7 the records are exempted from

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uses of their Pll/BU.

notification, access, and contest requirements of the agency procedures (under via 5 U.S.C 552a(c)(3),(d) , (e),(1), (e),(4) ,(G), (H) and (I), and (t). The data are maintained by the U.S. Census Bureau solely as statistical records as required under Title 13 U.S.C., and are not used in whole or in part in making any determination about an identifiable individual. This exemption is also made in accordance with the Department's rules which aooear in 15 CFR part 4 subpart B.

7.4 Indicate whether and how individuals have an opportunity to review/update PII/BII pertaining to them.

X Yes, individuals have an opportunity to Specify how: : As identified in the applicable SORN for

review /update PII/Bll pertaining to them.

Employee Productivit y Measurement Records, these individual may contact the Associate Director for Field Operations for

access to these records.

X No, individuals do not have .an

Specify why not: As identified in the applicable SORNs

opportunity to review/update PII/Bll

Census-3, -4, -5, and -7 the records are exempted from

pertaining to them.

notification , access, and contest requirements of the agency

procedures (under via 5 U.S.C 552a(c) (3),(d) , (e),(1),

(e),(4) ,(G), (H) and (I), and (f). The data are maintained by the

U.S. Census Bureau solely as statistical records as required

under Title 13 U.S.C., and are not used in whole or in part in

making any determ ination about an identifiabl e individual.

This exemption is also made in accordance with the

Department's rules which aooear in 15 CFR part 4 subpart B.

Section 8: Administrative and Technological Controls
8.1 Indicate the administrative and technological controls for the system. (Check all that apply.)
X All users signed a confidentiality agreement or non -disc losure agreement. X All users are subject to a Code of Conduct that includes the requirement for confidentiality. X Staff (employees and contractors) received training on privacy and confidentiality policies and practices. X Acc ess to the Pll/Bll is restricted to authorized personnel only. X Access to the PII/811 is being monitored, tracked, or recorded .
Explanation:
X The information is secured in accordance with FISMA requirements. Provide date of most recent Assessment and Authorization (A&A): 7/20/2017
□ This is a new system. The A&A date will be provided when the A&A package is approved .
X The Federa l Information Processing Standard (FIPS) 199 security impact category for this system is a moderate or higher.
X NIST Special Publication (SP) 800-122 and NIST SP 800-53 Revision 4 Appendix J recommended security controls for protecting PII/BII are in place and functioning as intended; or have an approved Plan of Action and Milestones (POA&M) .
X A sec urity assessment report has been reviewed for the supporting information system and it has been determined that there are no add itional privacy risks.
X Contractor s that have access to the system are subject to information security provisions in their contracts required by DOC policy. Contracts with customers establi sh ownership rights over data including PII/Bll.
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Acceptance of liability for exposure of PII/BII is clearly defined in agreements with customers. X Other (specify): Publications are approved by the Disclosure Review Board
8.2 Provide a general description of the technologies used to protect Pll/BII on the IT system. (Include data encryption in transit and/or at rest, if applicable).
The Census Bureau Information technology systems employ a multitude of layered security controls to protect BIi/PU at rest, during processing, as well as in transit. These NIST 800-53 controls, at a minimum, are deployed and managed at the enterprise level including, but not limited to the following:
• Intrusion Detection IPrevention Systems (IDS IIPS)
• Firewalls • Mandatory use of HTTP(S) for Census Bureau Public facing websites • Use of trusted internet connection (TIC) • Anti-Virus software to protect host/end user systems • Encryptio n of databases (Data at rest) • HSPD-12 Compliant PIV cards • Access Controls The Census bureau Information technology systems also follow the National Institute of Standards and Technology (NIST) standards including special publications 800-53, 800-63, 800-37 etc. Any system within the Census Bureau that contains, transmits, or processes BII/PII has a current authority to operate (ATO) and goes through continuous monitoring on a yearly basis to ensure controls are implem ented and operating as intended. The Census Bureau also deploys a Data Loss Prevention solution as well.
Section 9: Privacy Act
9.1 Indicate whether a system of records is being created under the Privacy Act, 5 U.S.C.
§ 552a. (A new system of records notice (SORN) is required if the system is not covered
by an existing SORN).
As per the Privacy Act of 1974, " the tenn 'sys tem of records ' means a group of any records under the control of any agency from which information is retrieved by the name of the individual or by some identifying number, symbol, or other identifying particular assigned to the individual."
X Yes, this system is covered by an existing system of record s notice (SORN). Provide the SORN name, number, and link. (list all that apply): COMMERCE/CENSUS-2, Employee Productivity Measurement Records : http://www.osec.doc.gov/opog/PrivacyAct/SORNs/census-2 .html
COMMERCE/CENSUS-3, Special Censuses, Surveys, and Other Studies: http://www.osec.doc.gov/opog/PrivacyAct/SORNs/census-3. html
COMMERCE/CENSUS -4, Econom ic Survey Collection: http ://www.osec.doc.gov/opog/Privac yAct/SORN s/census -4.html
COMMERCE/CENSUS-5, Decennial Census Program:
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http://www.osec.doc.gov/opog/PrivacyAct/SORNs/census-5.html COMMERCE/CENSUS-7, Special Censuses of Population Conducted for State and Local Government: http://www.osec.doc.gov/o12og/PrivacyAct/SORNs/census-.html Yes, a SORN has been submitted to the Department for aooroval on (date). No, this system is not a system of records and a SORN is not aoolicable.

Section 10: Retention of Information
10.1 Indicate whether these records are covered by an approved records control schedule and monitored for compliance. (Check all that apply.)
X There is an approved record control schedule. Provide the name of the record control schedule: GRS 3.1: General Technology Management Records; GRS 3.2: Information Systems Security Records; GRS 4. l: Records Manag ement Records; GRS 4.2: Information Access and Protection Records; GRS 4.3: Input Records, Output Records, and Electronic Copies, N 1-29-89-5 American Housing Survey, NC l -29-79-7 Demographic Fields Area, NCl-29-80-6 Demographic and Economic area Divisions - Secondary Use Samp ling Records No, there is not an approved record control schedu le. Provide the stage in which the project is in developing and submitting a recor ds control schedule:
X Yes, retention is monitored for compliance to the schedu le. No, retention is not monitored for compliance to the schedu le. Provide explanation:

10.2 Indicate the disposal method of the PII/Bll. (Check all that apply.)

Disposal

Shredd ing

I

I Overwriting

Ix

Degaussing

I

I Deleting

Ix

Other (specify):

Section 11: NIST Special Publication 800- 122 PH Confidentiality Impact Level
11.1 Indicate the potential impact that could result to the subject individuals and/or the organization if PII were inappropriate ly accessed, used, or disclosed. ([he PJJ Confidentiality Impact Level is not the same as the Federal Information Processing Standards (FJPS) 199 security impact category.)
I Low - the loss of confidentia lity, integrity, or availabi lity could be expected to have a limited advers e
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effect on organizational operations, organizational assets, or individuals. Moderate - the loss of confidentiality, integrity, or availability could be expected to have a serious adverse effect on organizational operations, organizational assets, or individuals. X High - the loss of confidentiality, integrity, or availability could be expected to have a severe or catastrophic adverse effect on organizational ooerations, organizational assets, or individuals.
11.2 Indicate which factors were used to determine the above PII confidentiality impact levels. (Check all that apply.)

X Identifiability

Provide explanation:

Individual data elements directly identifying unique individuals.

X Quantity of Pll

Provide explanation:

A severe or catastrophic number of individuals affected by loss,

theft, or compromise. Severe or catastrophic collective hatm to

individuals, hatm to the organization's reputation, or cost to the

organization in addressing a breach.

X Data Field Sensitivity

Provide explanation:

Data fields, alone or in combination, are directly usable in other

contexts and make the individual or organization vulnerable to

harms, such as identity theft, embarrassment, loss of trust, or

costs.

X Context of Use

Provide explanation: Disclosure of the PII is likely to result in

severe or catastrophic harm to the individual or organization.

X Obligation to Protect Confidentiality Provide explanation: Organization or Mission- specific privacy

laws, regulations, mandates, or organizational policy apply that

add more restrictive requirements to government- wide or

industry-specific requirements. Violations may result in severe

civil or criminal penalties. PII in this IT system is collected under

the authoritv of Title 5.

X Access to and Location of Pll

Located on computers and other devices on a network controlled

by the organization. Access limited to a multiple populations of

the organization's workforce beyond the direct program or office

that owns the information on behalf of the organization. Access

only allowed by organization- owned equipment outside of the

physical locations owned by the organization only with a secured

connection (e.g., virtual private network (VPN)).

Other:

Provide explanation :

Section 12: Analysis
12. l Identify and evaluate any potential threats to privacy that exist in light of the information collected or the sources from which the information is collected. Also, describe the choices that the bureau/operating unit made with regard to the type or quantity of information collected and the sources providing the information in order to prevent or mitigate threat s to privacy. (For example: If a decision was made to collect less data, include a discussion of this decision; if it is necessary to obtain information from sources other than the individual , explain why.)
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The biggest potential threat to privacy is the potential loss of a Field Representative's CAPI laptop. This threat is mitigated by the use of full disk encryption of the hard drive or solid state drive which renders the data inaccessible in the event that laptop is lost, damaged, or stolen. Due to the quantity, nature, and scope of the multiple surveys collected and processed through CEN05 (including the upcoming Decennial Census), there are no plans to reduce the quantity or type of data being collected, nor the sources of that data. 12.2 Indicate whether the conduct of this PIA results in any required business process changes.
Yes, the conduct of this PIA results in required business process changes. Explanation: X No, the conduct of this PIA does not result in any required business process changes .
12.3 Indicate whether the conduct of this PIA results in any required technology changes.
Yes, the conduct of this PlA results in required technology changes. Explanation: X No, the conduct of this PIA does not result in any required technology changes.
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Exhibit 6

Case 1:18-cv-02711-DLF Document 8-5 Filed 01/18/19 Page 19 of 75
Version Number: 01-2017
U.S. Department of Commerce U.S. Census Bureau

Privacy Impact Assessment for the
CEN08 Decennial Information Technology Division (DITO)

ff;a~ Reviewed by:

B ~

,Bureau Chief PrivacyOfficer

i;zJ Concurrence of Senior Agency Official for Privacy/DOC Chief Privacy Officer □ Non-concurrence of Senior Agency Official for Privacy/DOC Chief Privacy Officer

CATRINA PURVIS

Digitally signed by CATRINA PURVIS DN: c=US, o=U.S. Government, ou=Department of Commerce, ou=Office of the Secretary, cn=CATRINA PURVIS, 0.9.2342.19200300.100.1.1=13001002875743 Date: 2018.09.28 19:04:38 -04'00'



Signature of Senior Agency Official for Privacy/DOC Chief Privacy Officer

Date

Case 1:18-cv-02711-DLF Document 8-5 Filed 01/18/19 Page 20 of 75
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15

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Exhibit 7

Case 1:18-cv-02711-DLF Document 8-5 Filed 01/18/19 Page 36 of 75
Version Number: 01-2015
U.S. Department of Commerce U.S. Census Bureau

Privacy Impact Assessment for the
CENl 1 Demographic Census, Surveys, and Special Processing

Reviewed by:

~ Concurrence of Senior Agency Official for Privacy/DOC Chief Privacy Officer
D Non-concurrence of Senior Agency Official for Privacy/DOC Chief Privacy Officer

CATRINA PURVIS

Digitally signed by CATRINA PURVIS DN: c=US, o=U.S. Government, ou=Department of Commerce, ou=Office of the Secretary, cn=CATRINA PURVIS, 0.9.2342.19200300.100.1.1=13001002875743 Date: 2018.06.22 13:55:40 -04'00'

Signature of Senior Agency Official for Privacy/DOC Chief Privacy Officer

Date

Case 1:18-cv-02711-DLF Document 8-5 Filed 01/18/19 Page 37 of 75 Version Number: 01-2015
U.S. Department of Commerce Privacy Impact Assessment U.S. Census Bureau/Demographic Census, Surveys, and Special Processing
Unique Project Identifier: 006-000400500
Introduction: System Description
Provide a description of the system that addresses the following elements:
The response must be written in plain language and be as comprehensive as necessary to describe the system.
(a) a general description of the information in the system
The U.S. Census Bureau's CENl 1 Demographic Census, Surveys, and Special Processing System is a system comprised of components that support the Demographic Directorate business functions. The component within CENI I that contains PII is a Commercial off the Shelf (COTS) product used by Census Bureau demographic programs for data access, transformation, reporting, and statistical analysis. Some of the demographic data maintained in this system are Name, date of birth , telephone number, occupation, military service information (if applicable), medical information, financial information etc.
(b) a description of a typical transaction conducted on the system
The survey data for demographic programs is collected using a multi-mode approach made up of:
• Face-to-face or telephone induction interviews • Field Representatives (FR) • Web-based respondents
The information is collected by using:
Web-based respondents use a web-based application instrument that resides on the Census Bureau network via CEN15 Centurion . Respondents use their personal computers to access Centurion.
Introduction interviews are collected using electronic instruments - Computer-Assisted Personal Interviewing (CAPI) (a CEN05 component).
Once the information is collected by the instruments, the information is stored in a repository for use.
(c) any information sharin g conduct ed by the system
There is Pll bein g shared as follows :
• The Censu s Bureau provides access to staff at Department of Housing and Urban
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Development (HUD) with Special Sworn Status (SSS) for the American Housing Survey (AHS) via the Census Bureau Virtual Desktop Infrastructure (VDI). • The Census Bureau provides some Bureau of Labor Statistics (BLS) Staff access to Current Population Survey (CPS) and Consumer Expenditure Survey (CES) data on a CENl 1 Server in the DMZ. BLS Staff have Special Sworn Status (SSS) to have Census accounts to access the server. Consumer Expenditure staff at BLS access CPS data for weighting purposes. • Census Bureau sends a file containing respondent addresses to BLS for the Telephone Point of Purchase Survey (TPOPS). • The Census Bureau sends data files to the National Center for Health Statistics (NCHS) for the National Ambulatory Medical Care Survey (NAMCS), the National Hospital Ambulatory Medical Care Survey (N(H)AMCS) and National Health Interview Survey (NHIS). Data transfers are conducted through the Centers for Disease Control and Prevention (CDC) Secure Access Management Services (SAMS). • The Census Bureau sends data files to the National Center for Education Statistics (NCES) for the National Household Education Survey (NHES), the School Survey on Crime and Safety (SSOCS), the Schools and Staffing Survey (SSS), the Private School Survey (PSS), the National Teacher and Principal Survey (NTPS), the Teacher Follow-up Survey (TFS), the Principal Follow-Up Survey (PFS) and the Beginning Teacher Longitudinal Survey (BTLS). Data transfers are conducted through the Institute of Education Sciences (IES) Members Site. (d) a citation of the legal authority to collect P/1 and/or BIi 13 USC sections 8(b), 182 and 18 U.S.C. 2510-2521 (e) _the Federal Information Processing Standard (Ff PS) 199 security impact category for the system This is categorized as a moderate system.
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Section 1: Status of the Information System 1.1· Indicate whether the information system is a new or existing system.

__ This is a new information system. __ This is an existing information system with changes that create new privacy risks.
(Check all that apply)

Chanees That Create New Privacv Risks (CTCNPR)

a. Conversions

d. Significant Merging

b. Anonymous to Non-

e. New Public Access

Anonymous

C. Significant System

f. Commercial Sources

Management Changes

i. Other changes that create new privacy risks (specify):

g_ New lnteragency Uses h. Internal Flow or
Collection i. Alteration in Character
of Data

_x _ This is an existing information system without changes that create new privacy risks.

Section 2: Information in the System

2.1 Indicate what personally identifiable information (PJJ)/business identifiable information (BIi) is collected, maintained, or disseminated. (Check all that apply.)

ldentifyin2 Numbers (IN)

a. Social Security*

X e. File/Case ID

b. Taxpayer ID

X f. Driver's License

C. Employer ID

X g. Passport

d. Employee ID

h. Alien Registration

m. Other identifying numbers (specify):

L Credit Card i. Financial Account k. Financial Transaction I. Vehicle Identifier

*Explanation for the need to collect, maintain, or disseminate the Social Security number, including truncated form: The last 4-digits of the SSN is used in admin records matching to the National Health Interview Survey (NHIS).

The justification for the necessity of collecting this information , taken from the latest approved 0MB ICR supporting statement is below:

Social Security Number and Health Insurance Claim Number : The last four digits of the Social Security Number (SSN) is asked on the NHIS questionnaire to allow linkage with administrative and vital records , such as the National Death Index (NDI). The NDI is a computerized central file of death record information. It is compiled from data obtained by NCHS from the State vital statistics offices. The data contain a standard set ofidenti-fying information on decedents from I 979 to the present. Records are matched using Social Security Number and other variables such as name, father's surname, date of birth, sex, state ofresi-dence, and marital status. Ofthese, Social Security Number is the most important identifier for successful matching. The last four digits has been shown to be nearly as effective for matching as the full number.

The Social Security Number is also used by the Medical Expenditure Panel Study to help track the location of respondents who have changed residence since their NHIS interview. Finding a correct address for respondents is essential to maintainin g response level s at an acceptable level in linked surveys, and the Social Security Number

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is a key item for establishing a correct address.
Medicare beneficiaries are given a health insurance claim (HlC) number that is their (or their spouse's) SSN with an alphabetic prefix. The NHIS also asks for the last four digits of that number so that the NHlS data can be linked to Medicare claims information for purposes of statistical research.

General Personal Data (GPD)

a. Name

X g. Date of Birth

b. Maiden Name

X h. Place of Birth

C. Alias

X i. Home Address

d. Gender

X j. Telephone Number

e. Age

X

k. Email Address

f. Race / Ethnicity

X

I. Education

s. Other general personal data (specify): Citizenship

X m. Religion

X n. Financial Information

X

X

0. Medical Infonnation

X

X p. Military Service

X

X

Q. Physical Characteristics

X

X r. Mother's Maiden Name

Work-Related Data (WRD)

a. Occupation

X d. Telephone Number

X

g. Salary

X

b. Job Title

X e. Email Address

X h. Work History

X

C. Work Address

X f. Business Associates

1. Other work-related data (specify):

Distin2uishin2 Features/Biometrics (DFB)

a. Fingerpri nts

d. Photographs

b. Palm Prints

e. Scars, Marks , Tattoos

C. Voice

X f. Vascular Scan

Recording/Signatures

j. Other distinguishing features/biometrics (specify):

g . DNA Profiles h. Retina/Iris Scans i. Dental Profile

System Administration/Audit Data SAAD)

a. User ID

Ix

C. Date/Time of Access

Ix I e. ID Files Accessed

I

b. IP Address

I

d. Queries Run

I I r. Contents of Files

I

g. Other system admi nistratio n/audit data (spec ify):

I Dlhe< Information (specify)

2.2 Indicate sources of the PII/BII in the system. (Check all that apply.)

Directly from Individual about Whom the Information Pertains

In Person

Ix I Hard Coov: Mail/Fax

Ix I On line

Ix

Te lephone

Ix I Email

Ix I

I

Other (specify) :

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Government Sources Within the Bureau State, Local, Tribal Other (specify):

Ix I Other DOC Bureaus Ix I Foreign

I

I Other Federal Agencies

I

I [

I

Non-government Sources

Public Organizations

I

Third Party Website or Aoolication

Other (specify):

I Private Sector

I I Commercial Data Brokers Ix

Ix I

I

2.3 Indicate the technologies used that contain PII/B11in ways that have not been previously deployed. (Check all that apply.)

Technolo!!ies Used Containinl! PII/811 Not Previously Deployed (TUCPBNPD)

Smart Cards

I I Biometrics

I

Caller-ID

I

I Personal Identity Verification (PlV) Cards

I

Other (specify):

I x I There are not any technologies used that contain Pll/BII in ways that have not been previously deployed.

Section 3: System Supported Activities
3.1 Indicate IT system supported activities which raise privacy risks/concerns. (Check all that apply.)

Activities Audio recordings Video surveillance

Ix I Building entrv readers

I

I

I Electronic purchase transactions

I

Other (specify): For Computer Assisted Personal Interviewing (CAP!), the Demographic Programs Directorate

(DEMO) uses Computer-audio recording interviewing (CARI) for select interviews for the Survey of Income and

Program Participation (SIPP); future plans are to incorporate CARI for all demographic CAPl surveys. For

Computer Assisted Telephone Interviewing (CATl) surveys, the NICE Sentinel 2.5 system is used to record

selected interviews for Quality Assurance (QA) purposes. Both types of recordings contain PII.

I There are not any IT system supported activities which raise privacy risks/concern s.
Section 4: Purpose of the System 4.1 Indicate why the PII/B11in the IT system is being collected, maintained, or disseminated.
(Check all that apply.)
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Purvose

To detennine eligibility

For administering human resources programs

For administrative matters

To oromote information sharing initiatives

For litigation

For criminal law enforcement activities

For civil enforcement activities

For intelligence activities

To improve Federal services online

For employee or customer satisfaction

For web measurement and customization

For web measurement and customization

technologies (single-session )

technologies (multi-session )

Other (specify): For statistical purpo ses (i.e. , Censuses/S urveys)

Section 5: Use of the Information
5.1 In the context of functional areas (business processes, missions, operations, etc.) supported by the IT system, describe how the Pll/B11that is collected, maintained, or disseminated will be used. Indicate if the PII/B11identified in Section 2.1 of this document is in reference to a federal employee/contractor, member of the public, foreign national , visitor or other (specify).
PII is used to process numerous national statistical surveys and other demographic data programs.
The data is used to calculate, process, and manipulate the statistical data input for the purpose of creating statistical information and reports (i.e. Annual household and group quarters population estimates by age, sex, race, and origin for counties) .
The information that is ~ollected in this system is from members of the public.

Section 6: Information Sharing and Access
6.1 Indicate with whom the bureau intends to share the PII/B11in the IT system and how the PII/B11will be shared . (Check all that apply.)

Recipient Within the bureau

How Information will be Shared

Case -by-Case I Bulk Transfer I Direct Access

X

Ix

Ix

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DOC bureaus

Federal agencies

X

State, local, tribal gov't agencies

Public

Private sector

Foreign governments

Foreign entities

Other (specify):

I The PII/BII in the system will not be shared.

6.2 Indicate whether the IT system connects with or receives information from any other IT systems authorized to process PU and/or BIi.

Yes, this IT system connects with or receives information from another IT system(s) authorized to process PII and/or BIi. X Provide the name of the IT system and describe the technical controls which prevent PII/BII leakage: CENI I shares information with CEN03, CEN07, CEN08, CENl3, CEN 14, CENl 8, CENl9 , and CEN30. CEN 11 receives information from CEN 13, CEN30, and CEN35.
The CENl 1 IT system uses a multitude of security controls mandated by the Federal Information Security Management Act of 2002 (FISMA) and various other regulatory control frameworks including the National Institute of Standards and Technology (NIST) special publication 800 series. These security controls include, but are not limited to the use of mandatory HTTPS for public facing websites, access controls, anti-virus solutions , enterprise auditing/monitoring , encryption of data at rest, and various physical controls at Census Bureau facilities that house Information Technology systems. The Census Bureau also deploys an enterprise Data Loss Protection (DLP) solution as well.
No, this IT system does not connect with or receive information from another IT system(s) authorized to process PII and/or Bil.
6.3 Identify the class of users who will have access to the IT system and the PII/Bll. (Check all that apply.)

Class of Users General Public Contractors Other (specify):

I I Governme nt Employees

Ix

Ix I

I

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Section 7: Notice and Consent
7.1 Indicate whether individuals will be notified if their Pll/BII is collected, maintained, or disseminated by the system. (Check all that apply.)
X Yes, notice is provided pursuant to a system of records notice published in the Federal Register and discussed in Section 9.
X Yes, notice is provided by a Privacy Act statement and/or privacy policy. The Privacy Act statement and/or privacy policy can be found at: httos://www.census.e.ov /about/oolicies /orivacv /orivacv-oolicv .html
X Yes, notice is provided by other means. Specify how: Official correspondence letter or email from the Census Bureau to respondents.

No, notice is not provid ed .

Specify why not:

7.2 Indicate whether and how individuals have an opportunity to decline to provide PII/B11.

X Yes, individuals have an opportunity to Specify how: CENl 1 surveys are voluntary. Individuals may

decline to provide Pll/BII.

refuse to participate in the survey or, if they do participate, they

may refuse to answer specific questions.

No, individuals do not have an

Specify why not:

opportunity to decline to provid e

PII/811.

7.3 Indicate whether and how individuals have an opportun ity to consent to particular uses of their Pll/B11.

Yes, individuals have an opportunity to Specify how :

cons ent to particular uses of their

PII/BII.

X No, individuals do not have an

Specify why not: For records covered under SORNs Census-3

opportunity to consent to particular

and SORN Census -7 the data is collected for statistica l

use s of their PII/BII.

purposes and there is no opportu nity to consent to uses of the

data .

7.4 Indicate whether and how individuals have an opportunity to review/updat e Pll/BII pertaining to them .

Ye s, individuals have an opportunity to Specify how:

review/updat e PII/811 pertainin g to

them .

X No , individuals do not have an

Specify why not: For records covered under SORNs Census -]

opportunity to review/update PII/B11 and SORN Ce nsus-7 there is no access to the records since the

pertainin g to them.

data is collected for statistical purposes.

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Section 8: Administrative and Technological Controls
8.1 Indicate the administrative and technological controls for the system. (Check all that apply.)
X All users signed a confidentiality a!!reement or non-disclosure agreement. X All users are subject to a Code of Conduct that includes the requirement for confidentialitv. X Staff(emoloyees and contractors) received training on privacy and confidentiality policies and practices. X Access to the Pll/Bll is restricted to authorized personnel only. X Access to the PII/Bll is being monitored , tracked, or recorded.
Explanation:
X The information is secured in accordance with FISMA requirements. Provide date of most recent Assessment and Authorization (A&A): 7/ 14/2017
□ This is a new system. The A&A date will be provided when the A&A package is approved.
X The Federal Information Processing Standard (FIPS) 199 security impact category for this system is a moderate or higher.
X NIST Special Publication (SP) 800-122 and NIST SP 800-53 Revision 4 Appendix J recommended security controls for protecting PII/B11are in plac e and functioning as intended ; or have an approved Plan of Action and Milestones (POA&M).
X Contractors that have access to the system are subject to information security provisions in their contracts required by DOC policy. Contracts with customers establish ownership right s over data includin!! PII/Bll. Acceptance of liabilitv for exposure of Pll/B[l is clearly defined in agreements with customers.
X Other (specify): Publications are approved by the Disclosure Review Board
8.2 Provide a general description of the technologies used to protect PU/BITon the IT system.
(Include data encryption in transit and/or at rest, if applicable).
Census Bureau Information technology system s employ a multitude of layered security controls to protect Pll/BII at rest during processing, as well as in transit. These NIST 800-53 control s, at a minimum, are deployed and managed at the enterprise level including, but limited to the following:
• Intrusion Detection/ Prevention System s (IDA/IPS) • Firewalls • Mandatory use of HTTP(S) for Census Public facing websites • Use of trusted internet connection (TIC) • Anti-Viru s software to protect host/end user systems • Encryption of databases (Data at rest) • HSPD-12 Compliant PIV card s • Access Control s Census Bureau Information technology systems also follow the National Institute of Standards and Technology (NIST) standards , including special publications 800-53, 800-63, 800-37 etc. Any system within the Census that contains, transmits , or processes BII/PII has a current authority to operate (ATO) and goes throu gh continuous monitorin g on a yearly basis to·ensure controls are implanted and operating as intended. Census also deploy s a DLP solution as well.
9

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Section 9: Privacy Act

9.1 Indicate whether a system ofrecords is being created under the Privacy Act, 5 U.S.C.
§ 552a. (A new system of records notice (SORN) is required if the system is not covered

by an existing SORN).

As per the Privacy Act of 1974, "the tenn 'sys tem of records ' means a group of any records under the control of any agency from which

information is retrieved by the name of th e individual or by some identifying number, symbol, or other identifying panicular assigned

to the individual. "

·

Yes, this system is covered by an existing system of records notice (SORN). Provide the SORN name and number (list all that apply):
X Yes , a SORN has been submitted to the Department for approval on (date).
I. Census -3, Demogr,aphic Survey Collection (Census Bureau Sampling Frame) submitted on 7/22/ 16. 2. Census-7, Demographic Survey Collection (non-Census Bureau Sampling Frame) submitted on
7/22/16.
No, a SORN is not being created.

Section 10: Retention of Information
10.1 Indicate whether these records are covered by an approved records control schedule and monitored for compliance. (Check all that apply.)
X There is an approved record control schedule. Provide the name of the record control schedule: N 1-29-99-5, N 1-29-89-3, N 1-29-87-3, N 1-29-86-3, NC 1-29-85- 1, NC 1-29-79-7, and GRS 3.1 GRS 3.2 GRS 4.1, GRS 4.3
No, there is not an approved record control schedule. Provide the stage in which the project is in developing and submitting a reco rds control schedule:
X Yes, retention is monitor ed for compliance to the schedul e. No, retention is not monitored for compliance to the schedule. Provide explanation:

10.2 Indicate the disposal method of the PU/Bil. (Check all that apply.)

Disposal

Shredding

Ix

I Overwriting

Ix

Degaussing

I

I Deleting

Ix

Other (specify):

10

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Section 11: NIST Special Publication 800-122 PII Confidentiality Impact Levels

11.1 Indicate the potential impact that could result to the subject individuals and/or the organization if PII were inappropriately accessed , used, or disclosed.
Low - the loss of confidentiality, integrity, or availability could be expected to have a limited adverse effect on organizational operations, organizational assets, or individuals. Moderate - the loss of confidentiality, integrity, or availability could be expected to have a serious adverse effect on organizational operations, organizational assets, or individuals. X High - the loss of confidentiality , integrity, or availability could be expected to have a severe or catastrophic adverse effect on organizational operations, organizational assets, or individuals.

11.2 Indicate which factors were used to determine the above PU confidentiality impact levels. (Check all that apply.)

X Identifiability X Quantity of PII

Provide explanation: Pll/Bll collected can be directly used to identifv individuals
Provide explanation: The collection is for Census Bureau Censuses and surveys, therefore, a severe or catastrophic number of individuals would be affected if there was loss, theft or compromise of the data.

X Data Field Sensitivity

Provide explanation: The PII/BII, alone or in combination , are directly usable in other contexts and make the individual or organization vulnerable to harms, such as identity theft, embarrassment , loss of trust, or costs.

X Context of Use

Provide explanation: Disclosure of the act of collecting and using the PII/Bll in this IT system or the PII/Bll itself may result in severe or catastrophic harm to the individual or organization.

X Obligation to Protect Confidentiality Provide explanation: PII/Bll collected is required to be protected in accordance with organization or mission- specific privacy laws, regulations, mandates, or organizational policy apply that add more restrictive requirement s to government- wide or industryspecific requirements. Violations may result in severe civil or criminal penalties.

X Access to and Location of PII Other :

PH/Bil is located on computers controlled by the Census Bureau or on mobile devices or storage media . Access is limited to certain popu lations of the Census Bureau ' s workfor ce and limited to Special Sworn Status individuals . Access is only allowed by organization-owned equipment outside of the physical locations, and only with a secured connection . Provide explanation :

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Section 12: Analysis 12.1 Indicate whether the conduct of this PIA results in any required business process changes.
X Yes, the conduct of this PIA result s in required business process changes. Explanation: Next PTA will be update selection in question 2 to yes to address audio recordings and consistency with section 3. I of the PIA. No, the conduct of this PIA does not result in anv required business process changes.
12.2 Indicate whether the conduct of this PTAresults in any required technology changes.
Yes, the conduct of this PIA results in required technology changes. Explanation: X No, the conduct of this PIA does not result in anv required technolo!!v changes.
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Exhibit 8

Case 1:18-cv-02711-DLF Document 8-5 Filed 01/18/19 Page 50 of 75
Version Number: 01-2015
U.S. Department of Commerce Bureau of the Census

Privacy Impact Assessment for the
CEN13 Center for Economic Studies (CES)

~61~ Reviewed by:
) l

'-ti 'o, I'I ) I BureauChief PrivacyOfficer

~ Concurrence of Senior Agency Official for Privacy/DOC Chief Privacy Officer
□ Non-concurrence of Senior Agency Official for Privacy/DOC Chief Privacy Officer

For Dr. Catrina D. Purvis

LISA MARTIN Digitally signed by LISA MARTIN DN: c=US, o=U.S. Government, ou=Department of Commerce, ou=Office of the Secretary, cn=LISA MARTIN, 0.9.2342.19200300.100.1.1=13001000105292 Date: 2018.06.26 14:07:58 -04'00'

Signature of Senior Agency Official for Privacy /DOC Chief Privacy Officer

Date

Case 1:18-cv-02711-DLF Document 8-5 Filed 01/18/19 Page 51 of 75
Version Number: 01-2015
U.S. Department of Commerce Privacy Impact Assessment Bureau of the Census, CEN13 Center for Economic Studies (CES)
Unique Project Identifier: 006-000400700
Introduction: System Description
Provide a description of the system that addresses the.following elements:
(a) a general description of the information in the system
The Center for Economic Studies IT System includes data maintained by the Federal Statistical Research Data Centers (FSRDCs), the Center for Economic Studies and the Center for Administrative Records Research and Applications (CARRA). The CEN13 CES IT system covers the personally identifiable information (PIJ) and Business identifiable information (Bil) from each of the centers maintained by the system. The CES data holdings include census and survey data which may contain name, gender, age, date of birth etc. from across the Census Bureau, administrative records from other federal agencies, and proprietary data files from commercial vendors and some non-profits .

(b) a description of a typical transaction conducted on the system

For internal Census staff users, the Data Management System (DMS) is used to perform management and tracking functions for research proposal and active projects. The OMS is used to track the status and activity of all projects from initial conception through completion and close out.

For external FSRDC users, the CES Management System (CMS) is used to perform management and tracking functions for research proposals and active projects . The CMS is used to track the status and activity of all projects from initial conception through completion and close out. Data is available only to researchers who have received prior approval.

As an example, there may be a researcher wants to conduct an external project using the

Census Bureau's 2012 Survey of Business Owners (SBO). Information about the researcher

is collected to create an account in CMS; that account is associated with a project that is

documented in CMS (e.g. datasets such as SBO), the date pertaining to the of the data (e.g.

2012), other researcher s (i.e. research assistant), and the length of the project , (in this

example three years). The CMS is used to track all required reviews for the proposal. Once

the project and Special Sworn Status (SSS) for the individual is approved, the researcher is

provided a badge to access the FSRDC facility and a user account to access the server. The

researcher can then proceed to conduct their project. The CMS tracks ongoing activity

during the life of the project: who works on the proj ect, annual trainin g for each person,

annual reports, and disclosure requests . When the project is completed, the final report from

the project and the archival of the project files.

·

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(c) any information sharing conducted by the system
CES CEN13 has ISA ICD 's with the following Census systems - data is shared with: • ADEP ITO Associate Directorate for Economic Programs (CEN36) • EAD Economic Census and Surveys and Special Processing (CEN03) • GEO Geography (CEN07) • DSD Demographic Census, Surveys and Special Processing (CENI 1)
CES CEN13 has MOU's or contracts with the following systems external to Census: • Agency for Healthcare Research and Quality • Bureau of Labor Statistics • Department of Energy • National Center for Health Statistics • Internal Revenue Service
CES also shares data within the Bureau , with designated Federal agencies , State, Local and Tribal governments and Non-Profit organizations as part of its mission.

(d) a citation of the legal authority to collect Pl/ and/or BIJ: 13 U.S.C., Chapter 5, 8(b), 131, I32, and 182and 13 U.S.C. 6

(e) the Federal Information Processing Standard (FfPS) 199 security impact category for the system is Moderate.
Section 1: Status of the Information System
1.I Indicate whether the information system is a new or existing system. Existing System, No New Security Risks.

This is a new information system. This is an existing information system with changes that create new privacy risks . (Check all that apply.)

Chan2es That Create New Privacy Risks (CTCNPR)

a. Convers ions

d. Significant Merging

b. Anonymous to Non-

e. New Public Access

Anonymous

c. Significant System

f. Comme rcial Sources

Management Changes

j. Other changes that create new privacy risks (specify):

g. New lnteragency Use s h. Internal Flow or
Co llect ion i. Alteration in Characte r
of Data

X This is an existing information system without changes that create new privacy risks.

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Section 2: Information in the System
2.1 Indicate what personally identifiable information (Pil)/business identifiable information (BIi) is collected, maintained, or disseminated. (Check all that apply.)

ldentifvine: Numbers HN)

a. Social Securitv*

X e. File/Case ID

b. Taxpayer ID C. Emplover ID

X f. Driver's License X g_ Passport

d. EmPlovee ID

X h. Alien Registration

m. Other identifying numbers (specify):

X i. Credit Card

X i. Financial Account

X

k. Financial Transaction

X

X I. Vehicle Identifier

*SSNs are often included in administrative records datasets acquired in support of the Census Bureau's Title 13 authority to collect these data. When SSN s are present in these data they serve as one of several components used in a matchine or look-UPprocess to assien an anonvmized protected identification kev (PIK) to the record.

General Personal Data (GPD1

a . Name

X g, Date of Birth

b. Maiden Name

X h. Place of Birth

C. Alias d . Gender

X i. Home Address
X i. Telephone Number

e. Age

X k. Email Address

f. Race/ Ethnicity

X I. Education

s. Other general personal data (specify) :

X m. Religion

X n. Financial Information

X

X o. Medical Information

X

X p. Militarv Service

X

X q. Physical Characte ristics

X r. Mother' s Maiden Name X

Work-Related Data (WRD)

a. Occuoation b. Job Title

X d. Telephon e Number

X g. Salarv

X

X e. Email Addre ss

X h. Work Historv

X

C. Work Address

X f. Business Associates

X

i. Oth er work-relat ed data (specify) :

Distin!!uishin!! Features/Biometrics (DFBl

a. Fingerorint s

d. Photographs

b. Palm Prints

e. Scars, Marks, Tattoo s

C. Voice

f. Vascular Scan

Recording/Sign atures

J. Other distinguishing features/biometric s (specify):

g. DNA Profiles h. Retina/Iri s Scans i. Dental Profile

Svstem Administration/Audit Data SAAD)

a. User ID

IX C. Date/Tim e of Access

I

I e. ID Files Accessed

I

b. IP Addr ess

I

d. Querie s Run

I

I f. Contents of Files

I

g_ Other system administration/audit data (specify) :

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I0th« lnlumation (•~eeffl')

2.2 Indicate sources of the PII/B11in the system. (Check all that apply.)

Directly from Individual about Whom the Information Pertains

In Person

IX I Hard Copy: Mail/Fax

I I Online

I

Telephone

IX I Email

IX I

I

Other (specify):

Government Sources Within the Bureau State, Local , Tribal Other (specify):

Ix I Other DOC Bureaus
IX I Foreign

IX I Other Federal Agencies

IX

I I

I

Non-2:overnment Sources

Public Organizations

I

I Private Sector

Ix I Commercial Data Brokers IX

Third Party Website or Application

I I

I

Other (specify): Some data is receiv ed from Non-profit organizations

2.3 Indicate the technologies used that contain PII/B11in ways that have not been previously deployed. (Check all that apply.)

Technoloi:des Used Contai nine: Pll/811 Not Previouslv Deployed (TUCPBNPD)

Smart Cards Caller-ID

I I Biometrics

I

I

I Personal Identity Verification (PJV) Cards

I

Other (specify):

I I X There are not any technologies used that contain PII/Bll in ways that have not been previously deployed.

Section 3: System Supported Activities

3.1 Indicate IT system supported activities which raise privacy risks/concerns. (Check all that apply.)

Activities Audio recordings Video surveillance Other (specify) :

I I Building entry readers

I

I

I Electronic purchase transactions

I

X I There are not any IT system supported activities which raise privacy risks/concerns.

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Section 4: Purpose of the System
4.1 Indicate why the PII/BII in the IT system is being collected, maintained, or disseminated. (Check all that apply.)

Purpose

To determine eligibility

For administering human resources nroe:rams

For administrative matters

X To promote information sharing initiatives

For litigation

For criminal law enforcement activities

For civil enforcement activities

For intelligence activities

To improve Federal services online

For employee or customer satisfaction

For web measurement and customization

For web measurement and customization

technologies (single-session)

technologies (multi-session)

Other (specify): Research, Improvement/support of Census Bureau programs through use of administrative and

other non-survey data, Quality assurance, and statistical purposes.

Section 5: Use of the Information
5.1 In the context of functional areas (business processes, missions, operations, etc.) supported by the IT system, 1) describe how the PII/BJI that is collected, maintained, or disseminated will be used. 2) Indicate if the PII/BIIidentified in Section 2.1 of this document is in reference to a federal employee/contractor, member of the public, foreign national, visitor or other (specify).
Administration and research mission of the CEN13 program for statistical purposes:
For administrative matters: The PII/BII is used for record linkage. SSNs are used to assign protected identification keys (PIKs) after which SSN anct"other PII are dropped from the file. After the PIK is assigned, ,files are linked only by PIK. This PII/BII covers members of the public, businesses, contractors and federal employees.
Research. Improvement/support of Census Bureau programs through use of administrative and other non-survey data. Quality assurance. and statistical purposes : Record linkage using BIi and PIKs facilitates research to improve and support existing Census Bureau programs and creation of beta data products. These products use innovative techniques that leverage existing data and reduce the burden on respondents. This PII/BII covers members of the public , businesses , contractors and federal employees.

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Section 6: Information Sharing and Access
6.1 Indicate with whom the bureau intends to share the PII/BII in the IT system and how the PII/BII will be shared. (Check all that apply.)

Recipient
Within the bureau DOC bureaus Federal agencies State, local, tribal gov't agencies Public Private sector Foreign governments Foreign entities Other (specify): Data is made available to approved researchers on the RDC and CES internal servers, the researchers are Sworn Census employees , Contractors or Special Sworn Status.

How Information will be Shared

Case-bv-Case

Bulk Transfer

Direct Access

X

X

X

X

X

X

I The PU/BU in the system will not be shared.

6.2 Indicate whether the IT system connects with or receives information from any other IT systems authorized to process PII and/or BIL

X Yes, this IT system connects with or receives information from another IT system(s) authorized to process PU and/or BIT. Provide the name of the IT system and describe the technical controls which prevent PII/BII leakage:
CES CEN 13 has shares data with the following Census Bureau systems: • ADEP ITO: Associate Directorate for Economic Programs (CEN36) • EAD: Economic Census and Surveys and Special Processing (CEN03) • GEO: Geography (CEN07) • DSD: Demographic Census, Surveys and Special Processing (CEN 11)
CES CEN 13 rece ives data from the following Census Bureau systems: • ACSO: American Commun ity Survey (CEN30) • ITMD: Foreign Trade Division Applications (CEN34) • DSCMO -DSSD: Decennial (CEN08) • ASCO : Ame rican Community Survey (CEN30)
CES also receives data from within the Bureau, designated Federa l agencies , State, Local and Tribal governments and Non -Profil organizations as part of its mission.
CEN 13 uses a multitude of security controls mandated hy the Federal Information Security Managem ent Act of2002 (FISMA) and various other regulatory control frameworks including the National Institute of Standards and Technology (NIST) special publication 800 series. These security contro ls include, but are not limited to the use of mandatory HTTPS for public facing websites , access controls , anti-virus solutions, enterprise auditing/monitoring , encryption of data at rest, and various physical contro ls at

6

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Census Bureau facilities that house lnfonnation Technology systems. The Census Bureau also deploys an enterprise Data Loss Protection (OLP) solution as well. No, this IT system does not connect with or receive infonnation from another 1T system(s) authorized to process PII and/or BIi.
6.3 Identify the class of users who will have access to the IT system and the PII/B11. (Check all that apply.)

Class of Users General Public

I

I Government Employees

IX

Contractors

[X I

I

Other (specify): Special Sworn Status employees of the Census Bureau

Section 7: Notice and Consent
7.1 Indicate whether individuals will be notified if their PII/Bll is collected, maintained, or disseminated by the system. (Check all that apply.)
X Yes, notice is provided pursuant to a system of records notice published in the Federal Register and discussed in Section 9.
X Yes, notice is provided by a Privacy Act statement and/or privacy policy. The Privacy Act statement and/or privacy policy can be found at: https://www.census.gov/about/policies/privacy/privacypolicy.html Yes, notice is provided by other means. Specify how:

No, notice is not provided.

Specify why not:

7.2 Indicate whether and how individuals have an opportunity to decline to provide PII/B11.

X Yes, individuals have an opportunity to Specify how: When survey is voluntary individuals may

decline to provide PII/Bll.

decline to provide PII/Bll; however in the case of aggregated

secondary data there is no interaction with an individual.

Survey data are not collected by CENl 3 CES.

X No, individuals do not have an opportunity to decline to provide

Specify why not: When survey is mandatory individuals may not decline to provide PII/B11,and in the case of aggregated

PU/Bil.

secondary data, there is no interaction with an individual.

Survey data are not collected by CEN 13 CES.

7.3 Indicate whether and how individuals have an opportunity to consent to particular uses of their PII/B11.

X Yes, individuals have an opportunity to Specify how: When survey is voluntary individuals may

consent to particular uses of their

consent to particular uses of their PII/B11;however in the case

PII/Bll.

of aggregated secondary data there is no interaction with an

individual. Survey data are not collected bv CEN 13 CES .

X No , individual s do not have an oooortunitv to consent to oarticular

Specify why not: In the case of aggregated secondary data , there is no interaction with an individual. Survey data are not

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I uses of their PII/Bll.

I collected by CEN 13 CES.

7.4 Indicate whether and how individuals have an opportunity to review/update PIJ/BII pertaining to them.

Yes, individuals have an opportunity to Specify how:

review /update Pll/811 pertaining to

them.

X No, individuals do not have an

Specify why not: In the case of aggregated secondary data

opportunity to review /update Pll /811 there is no direct contact with the individual.

oertaining to them.

Section 8: Administrative and Technological Controls
8.1 Indicate the administrative and technological controls for the system. (Check all that apply.)
X All users signed a confidentiality agreement or non-disclosure agreement X All users are subject to a Code of Conduct that includes the requirement for confidentiality. X Staff(employees and contractors) received training on privacy and confidentiality policies and practices . X Access to the Pll/B11 is restrict ed to authorized personnel only. X Access to the PIUBII is being monitored, tracked , or recorded.
Explanation: All individual activities within PIJ systems are logged, access is controlled by Access Control Lists(ACL) and all controls are reviewed in accordance with Audit and Accountability controls and Continuou s Monitoring as specified in NIST 800-53 Revision-4. Only authorized government/contractor personnel are allowed to access PH/BH within a system. Authorizations for users occur yearly , at a minimum in accordance with applicable Bureau, Agency, and Federal policies/guidelines. In additional to system processes that handle PII/BII , all manual extractions for PII/BIJ are Jogged and recorded per Department of Commerce Policy , the NIST 800-53 Appendix J Privacy Control Catalog , and specifica lly NIST control AU-03, Conten t of Audit records.
X The information is secured in accordance with FISMA requirements . Provide date of most recent Assessment and Authorization (A&A): July 13, 2017
□ This is a new system . The A&A date will be provided when the A&A package is approve d.
X The Federal Information Processing Standard (FIPS) 199 sec urity impacl category for this system is a moderate or higher.
X NIST Special Publication (SP) 800-122 and NIST SP 800-53 Revision 4 Appendix J recommended sec urity controls for protecting Pl 1/811are in place and functioning as intended ; or have an approved Plan of Action and Milestones (POAM).
X Contractors that have access to the system are subject to information security provisions in their contracts required by DOC policy.
X Contracts with customers establish ownership rights over data including PII/Bll. X Acceptance ofliability for exoosure of PII/BII is clearly defined in agreements with customers.
Other (specify):

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8.2 Provide a general description of the technologies used to protect PIJ/BJI on the IT system. (Similar to 6.2, technical controls and leakage management)
The Census Bureau Information technology systems employ a multitude of layered security controls to protect Pll/811 at rest, during processing, as well as in transit. These NIST 800-53 controls, at a minimum, are deployed and managed at the enterprise level including, but not limited to the following:
• Intrusion Detection I Prevention Systems (IDS I IPS)
• Firewalls • Mandatory use ofHTTP{S) for Census Bureau Public facing websites • Use of trusted internet connection (TIC} • Anti-Virus software to protect host/end user systems • Encryption of databases (Data at rest) • HSPD-12 Compliant PIV cards • Access Controls The Census bureau Information technology systems also follow the National Institute of Standards and Technology (NIST) standards including special publications 800-53, 800-63, 800-37 etc. Any system within the Census Bureau that contains, transmits , or processes 811/PII has a current authority to operate (ATO) and goes through continuous monitoring on a yearly basis to ensure controls are implemented and operating as intended. The Census Bureau also deploys a DLP solution as well.
Section 9: Privacy Act
9.1 Indicate whether a system of records is being created under the Privacy Act, 5 U.S.C. § 552a. (A new system of records notice (SORN) is required if the system is not covered by an existing SORN).
As per the Privac y Act of 1974, "the term ' system of records ' means a group of any records under the control of any agency from which information is retrieved by the name of the individual or by some identifying number, symbol , or other identifying particular assigned to the individual. "
X Yes, this system is covered by an existing system of records notice (SORN). Provide the SORN name and number (list all that apply):
Census-8 , Statistical Administrative Records System
X Yes, a SORN has been submitted to the Department for approval on (date).
Census - 4, Economic Survey Collection submitted on 8/24/16
No, a SORN is not being created.
Section 10: Retention of Information
10.1 Indicate whether these records are covered by an approved records control schedule and monitored for compliance. (Check all that apply.)
X There is an approved record control schedule. Provid e the name of the record control schedule:
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GRS 3.1 General Technology Management Records, GRS 3.2 Information Systems Security Records; GRS 4.3 Input Records, Output Records and Electronic Copies. DAA-0029-2014-0005: Records of the Center for Administrative Records Research and Applications.
No, there is not an approved record control schedule. Provide the stage in which the project is in developing and submitting a records control schedule:
X Yes, retention is monitored for compliance to the schedule. No, retention is not monitored for compliance to the schedule. Provide explanation:

10.2 Indicate the disposal method of the PII/BII. (Check all that apply.)

Disposal

Shredding

IX I Overwriting

IX

Degaussing

I

I Deleting

Ix

Other (specify):

Section 11: NIST Special Publication 800-122 PII Confidentiality Impact Levels

11.1 Indicate the potential impact that could result to the subject individuals and/or the organization if PII were inappropriately accessed, used, or disclosed.
Low - the loss of confidentiality , integrity, or availability could be expected to have a limited adverse effect on organizational operations, organizational assets, or individuals. Moderate - the loss of confidentiality, integrity, or availability could be expected to have a serious adverse effect on organizational operations , organizational assets, or individuals. X High - the loss of confidentiality , integrity, or availability could be expected to have a severe or catastrophic adverse effect on organizational operations, organizational assets, or individuals.
11.2 Indicate which factors were used to determine the above Pll confidentiality impact levels. (Check all that apply.)

X Identifiability X Quantity of PII
X Data Field Sensitivity

Provide explanation: Individual data elements directly identifying unique individuals. Provide explanation: A severe or catastrophic number of individuals affected by loss, theft, or compromi se. Severe or catastrophic collective harm to individuals , harm to the organization 's reputation , or cost to the organization in addressing a breach. Provide explanation : Data fields, alone or in combination, are directly usable in other contexts and make the individual or organization vulnerabl e to .harms, such as identity theft, embarrassm ent, loss of trust, or costs.

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X Context of Use

Provide explanation: Disclosure of the act of collecting, and using the PII, or the PH itself is likely to result in severe or catastrophic harm to the individual or organization

X Obligation to Protect Confidentiality Provide explanation: Organization or Mission- specific privacy laws, regulations, mandates, or organizational policy apply that add more restrictive requirements to government- wide or industry-specific requirements. Violations may result in severe civil or criminal penalties.

X Access to and Location of Pll

Provide explanation: Located on computers and other devices on a network controlled by the organization. Access limited to a multiple populations of the organization's workforce beyond the direct program or office that owns the information on behalf of the organization . Access only allowed by organization- owned equipment outside of the physical locations owned by the organization only with a secured connection

Other:

Provide explanation

Section 12: Analysis 12.1 Indicate whether the conduct ofthis PIA results in any required business process changes.
Yes, the conduct of this PIA results in required business proce ss changes. Explanation:
X No, the conduct of this PIA does not result in any required business proce ss changes .
12.2 Indicate whether the conduct of this PIA results in any required technology changes.
Yes, the conduct of this PIA results in required technology changes. Explanation :
X No, the conduct of this PIA does not result in any required technolo !>v chan ges.

11

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Exhibit 9

Case 1:18-cv-02711-DLF Document 8-5 Filed 01/18/19 Page 63 of 75
Version Number: 01-2015
U.S. Department of Commerce U.S. Census Bureau

Privacy Impact Assessment for the
CEN18 Enterprise Applications

Reviewed by:

-"fLConcurrence of Senior Agency Official for Privacy/DOC Chief Privacy Otlicer
D Non-concunence of Senior Agency Official for Privacy/DOC Chief Privacy Officer

LISA MARTIN Digitally signed by LISA MARTIN DN: c=US, o=U.S. Government, ou=Department of Commerce, ou=Office of the Secretary, cn=LISA MARTIN, 0.9.2342.19200300.100.1.1=13001000105292

Dr. Catrina D. Purvis

- ------

Date: 2018.06.26 14:19:48 -04'00'
- ------

- - ----

Signature of Senior Agency Official for Privacy/DOC Chief Privacy Orficcr

Date

Case 1:18-cv-02711-DLF Document 8-5 Filed 01/18/19 Page 64 of 75
Version Number: 01-2015
U.S. Department of Commerce Privacy Impact Assessment U.S. Census Bureau CEN18 Enterprise Applications
Unique Project Identifier: 006-000401700
Introduction: System Description
(a) a general description of the information in the .system;
The CEN18 Enterprise Applications system is the functional management frame\vork used to deliver applications to end users of the U.S. Census Bureau network. The CEN18 Enterprise Applications system includes several applications that maintain or collect personally identifiable infonnation (Pll) . These applications arc:
• an enterprise-level data tracking system; • a general support system for internal data management, • a transaction-based system • a relational database management system , and • a concurrent analysis and estimation system (CAES),
Some examples of survey and census information maintained by this system arc personal names , personal addresses, personal contact infomiation (telephone numbers, email address), business infonnation. occupation. medical infonnation. tax information, etc. The systems reside in Census Bureau's Bowie Computing center. The components that collect Pll/BII do not reside in the cloud.
(b) a description of a fJ,JJicaltransaction conducted on the system:
The purpose of the enterprise-level data tracking system is to ensure data consistency, data integrity, and generate meaningful data information through data management, tracking, and reporting for Census Bureau collections .
The general support system for CEN 18 provides internal data management within the Census Bureau collections. This system alld\.vs·users to request access to datasets, and when approved, users are granted access to the datasets within a secure environment provisioned by the system . Census Bureau datasets are for internal use by employees , and arc capable of containing protected or administrative inforn1ation.
The transaction-based system within CEN 18 serves as the primary mechanism for operational control across surveys for data colkction. The system can be considered an operational brain that detennincs operational \Vorkflo\VbaseJ on pre-existing protocols .
The relational database management system stores and retrieves data as requested by other software applications. This system provide s both a testing, development and production environment for optimum functionality.
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The CAES serves as the enterprise-wide analytics platfonn for surveys and censuses. This system allows statisticians within census and survey projects to perform statistical models using census and survey response data, paradata, administrative records, and many other types of data. The system will receive PII including Identifying Numbers, General Personal Data. and WorkRelated Data. The PH is received from other information systems that collect, maintain and disseminate Census and Survey data.
(c) any il?f<Jnnationsharing conducted hy lhe .~yslem
The enterprise-level data tracking system does not share information.
The general support system shares infi.Jm1ation within the Census Bureau by querying indexed metadata and by sending email to data owners, administrators, and other application users.
The relational database management system does not share infonnation.
The transaction-based system shares demographic survey. Decennial, and Economic Census infonnation within the Census Rureau and with the Department of Commerce, that is used to determine new survey content, support electronic collections, for statistical purposes. and to create datasets for the Census Rurcau.
The ConCLment Analysis and Estimation System (CAES) is an environment for use hy researchers to make decisions during the data collection phase of a survey or a Census. The CAES system \Villprovide the researcher \IYithany data that they request as input and will output and send decision based data only to other systems. This could include things such as case level intervention codes, a stop work decision, or best time of day to contact respondents. CAES docs not provide a mechanism for sharing PII/BU with other systems.
(d} a citation ,~(lhe legul alllhorit.1· lo collect Pl/ and /or Bil:
The legal authorities to collect Pl! and/or BIi for CEN l 8 are:
5 U.S.C. 301 13 U.S.C. Chapter 9, and Sections: 6, 8(b), 9, 131, 132, 141, 161, 182, 193, 196 15 C.F.R. Part 30 and 19 C.F.R. Section 24.53 18 U.S.C. 2510-2521 26 U.S.C. 6103(.i) and Foreign Trade Statistical Regulations or its successor document, the Foreign Trade Regulations
(e) the Federal h?fhrmation Processing Siandard (Ff PS) 199 security impucl categmy.fiw lhe ,\ysre,n
The Federal Jnfom1ation Processing Standard (FIPS) l 99 category for this system is Moderate.
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Section 1: Status of the Information System 1.1 Indicate whether the infonnation system is a nevvor existing system.

This is a new information system. This is an existing information system with changes that create new privacy risks . (Check all that app~y)

S!!?nges That Create New Priva<;vRisks, CTCNPR) ___

a. Conversion s

d. Significant ~ e_!:~,n~_o;;:___

h. /\nonyrnou $ to Non-

C. New Public Acces s

- 1\non ,tmous C. Significant Syste m

f Co mm.::rcial Soun :·cs

ManaQem ent Chan!!.cS

j. Other changes that create new privac y risks (specif y):

- ----

- ----

--

g. New lntc rage ncy _U_s~_,s_-1h. Internal Flow or
Co lkction i. Alteration in Character of
Data

x risks.

This is an existing information system without changes that create new privacy

Section 2: Information in the System

2. I Indicate what personally identifiable information (PH)/business identifiable infonnation (BIJ) is collected, maintained , or disseminated. (Check all that apply.)

,-- ---

-- ----- --·- ---

!d!_n_!lfying N~mbers IN

~- ------

---- -

·- ------

- - ------___ __ _

a. Social ~_:__ _b~_Taxpayer ID_ __

c. File/Case ID

-~-

i . Credit Card

X f. Driver 's License

__ -~ L Financial Account

~ mp!2;-'er ID

X

0 • Pas sport __ __

k. Financi_alTr~nsac!ion

d~ 1:mplo ec ID

X !!:__6.!~l 10.e g istra!i_si-1-~ _ _ ..!.__ Vehicl ~ Identifier __

m . Other identif y ing numbers (specify):

- --
X X _ X X

-- -- - -- --- -- --- ----

-

'kExplanation for the need to collect, maintain , or disseminat e the Social Security number , includin g truncated

form :

- -- -- -- - -- --

----

- ---- -- - -- --- --- -

--- - - - --

- - - -- --- ------

G~~ral _P~~~onalData (GPD)

- ---·---

-- . ·-

- -----

--

a Name

X

g, Date of Birt-h---

-- X n1 Re!ig_i~ _ __ _

b-.- -Ma- i-d--e-n Name-- ---+-

X h. Place of Birth

X n. Financial Information

X

-- -

- - - ---+--

-

-c--. Alias - -----

- ---+-- X

i. llome Addre ss - --

0 . Medical lnfonnation---+-

X

cl. Gender

X .:..__!_elephoncN':!_!bTcI r

. Milit~.2,~vice

_ X

e. Age·-- ---- - ----+

X

k. F.mail Ad-dres-s -----+--

f. R--a-ce /E-t-hnicitv~--

X !. Education

s. Other general per sonal dat a (spec ify) :

X

~ hys ical Characteri~!i~s _ X

X r. Mother 's Maid en Nam e X

-- _·--_- -- - ---- ------------

"]

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a. Occupation

X d. Telephone Number

b. Job Title

X e. Emai l Address

C. Work Address

X f. Business Associates

1. Other work-related data (specify):

X g. Salary X h. Work History X

X X--· ----~ ----
-

Distin2uishi112 Features/Biometrics (DFB)

a. Fingerprints

d. Photographs

...b..._ Palm Prints

e. Scars, Marks, Tattoos

C. Voice

f. Vascular Scan

Recording/Signatures

J. Other distinguishing features /biometrics (s pecify):

~

--

g. DNA Profiles

h. Retina/Iris Scans

- --

i. Dental Profile

S ·stem Administration/Audit Data SAAD)

a. User ID

X

I I I -=:~-=-:-- ---:- -----.--,-----

-,-----

---.,.---j

c. Date/Time of Access

X e. ID Files Accessed

X

b. 1PAddress

X d. ___9~eries Run

I X I f. Contents of Files

I X

g. Other system admini stration/audit data (specify):

Other Information (specify) _ _____ __ _

- ----------

1------

-----

-- --- - - --- -- --

-- ----

-- --- -- -

---

·- ----

- - ---

2.2 Indicate sources of the Pll / 811 in the system. (Check all that apply.)

- --------

- -- - -- ----

-L y,-_on.. Directh· from Individual about Whom the Information Pertains

In Pe:5011 -----

-- -

J_l:l_~d Copy: MailiFa:,: _ __,__

l~c -

Telephone

____

E~1~il---

-

_L

Other (specify):

L-

---

--

---

-

----

Government Sources

--

-

-- -

- - -- - - ----

--- ---

-

-- -- -

J

-t~~-~-~:-~B--~~c~-u-~:-_~¥-_r·_,-;_p_~~-·F--~=~:J-~~-~.~~, --? - ;_ta_i:1_~:_·1-~--~hc_:_:_3,_~-:--~~u~a___l_____ ____J-G+-~"_ 0

Other (specify):

-----------------

·

- - ---------

- -----

-- - ---- --- ----

----

----- -- -- - - - --

~------

----

-- - ---- - --- - -- ------

-- ------

- -- - --~

4

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Indicate the technologies used that contain PII/Bll in ways that have not been previously deployed. (Check all that apply.)

~-- - -- ---- -- ---

---

----

-- --- - -- - ------

Teclrnolo<TiesUsed Containing PII/BII Not Previously De toyed TUCPBNP_Ql__ - -----

-- --
-~ ----l

S_rn_~r_Cta_rc_ls __ __ _____ __ ____

+--- -t-B_i_on1_et_r_ic_s____ _ ____

__ __ _

Ca ller-ID

Personal Identity Verification (PIVLC~rd__s__ _.___ ---1

Other (specify):

[_L[j~ 1ere arc not anv technolo ~ies used that contain Pll/BII in ,~ays that have not been prev iously deplo yed.

Section 3: System Supported Activities

3. 1 Indicate IT system supported activities, \Vhichraise privacy risks/concerns . (Check all thal apply.)

--- -·-- --

- -- ------

--- ---·--

-- ----

-- -------

- - ----- - ---
[x ~ 1"-1ic-re-a~~no~nv -,T-svst~~-s upported activities, which raise 2!:iv-a-cv riiks /~o- n-ce·-rn-s. -~~ -- - --

Section 4: Purpose of the System

4.1 Indicate why the Pll/BII in the IT system is being collected, maintained , or disseminated . (Check all that apply.)

------

---

------

-- ----

-- ------

Pur~ --- -- ---- -- --

_ _______

- ------

--- ---~

To determine ~ligibility

--- -----+--

-+-_For adrnin~t~~~l!_~eso1~

-~J-~_r_Qg_r1_as_n_,__

For administr_at_i_v1e_n_att_crs__

X To _po_mr (2!cint~ r~ ~ i~1~haring i_f!itiatives _ _ X

For litigation

____ ___

For criminal ]a\_V_en_!:roc__e·_mc.!!_t_c_taiYiti~_s__ _ _

For ci"'._il _e1_1forc__me_en_t _ac_t,_iv_iteis_______

_

For inte~encc activitie s _ ______ _

To improv~ Federal services on line _ ___

. For empl(?~ _2_1:_~~1~tosmateirs_Qiction__ _

For web meas urement and customization

For web meas urement and custom ization

techno~gi_eJ _(_s~~le-ses~~O)_f! ______

.. ~- -~ technologies (multi-session )_ _ ______ _

Other (specify) : For research and statistical purpo ses

-- -- -----

--- -------

5

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Section 5: Use of the Information
5.1 In the context of functional areas (business processes, missions, operations, etc.) supported by the IT system, describe how the PII/BII that is collected, maintained, or disseminat~d will be used. Indicate if the PII/BJI identified in Section 2.1 of this document is in reference to a federal employee/contractor, member of the public, foreign national, visitor or other (specify).
The Pll/BJI maintained for administrative pun)oses: This IT system maintains first name, last name, address, email address, etc. to ensure that mandatory survey or statistical, information is ready for internal Census use. The infonnation pertains and is in reference to federal employees/contractors conducting the surveys and the public,
The PII/BIImaintained for statistical and research purposes: The data maintained by this fT system is collected from other IT systems that collect censuses and surveys (e.g., responses and statuses) and is used to direct data collection efforts. ft is also used to inform program areas within the Census Bureau (responsible for survey and census questionnaire mail out) whom to send survey and census fom1s to. The IT system gathers response data fi:om the data collection modes to send it to th~ survey and census processing IT systems in a standardized way. This infommtion enables the Census Bureau to fulfill its legal obligation to provide mandated statistics. The information pertains to members of the public.
The PIJ/Rll maintained for information sharingjnitiatives: This information is collected and shared within the Census Bureau and the Department of Commerce to create datasets for various types of censuses and surveys. This information enables the Census Bureau to fulfill its legal obligation to enhance its infonnation sharing initiatives. The infonnation pertains lll members of the public.

Section 6: Information Sharing and Access

6.1 Indicate with ,vhom the bureau intends to share the Pll/811 in the IT system and how the PII/Bll ,vill be shared. (Check all 1ha1appZr.)

Recipient

- --

_____

I J___!_Q,_v_ln_f_o_rn_bia__et__Sio~_hn__a\__rvei_l_cl_ ..

\Vithin the bureau

--------+-X_C_'a.:-~:QY-Casc

·-l)O_C_b_u_r~-aus-------=---_-----

x" ·- -----

F~~~l-~enc\e? . _______

__ ___

_State, local, tribal ~ov·t~encies__ _

___

----t-----·--

_ __ . -~-

===_----__--__--~7 X Bulk lransfor

X Direct Acccss

_______

_

________

_, ______

_

6

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j _--__-~~---_-_-- :~i~~~e ------i----+- - For~1 sgeoctvoerrnments ---_-

_

__

-i

Foreignenti~e_s _ _ _

Other (s ecify) _: __

[_---] The PII/Bll inthe ~ystem will not be sh_a_re_d_.__ __ _

_ _ ___ ]

6.2 Indicate whether the IT system connects with or receives information from any other IT systems authorized to process Pll and/or BIL

X Yes, this IT system connects with or receives information from another 1Tsystem(s) authorized to process Pll and /or Bil. Provide the name of the IT system and describe the technical controls which prevent Pll/B11 leakage: CEN0 I. CEN03, CEN04 , CEN05, CEN07, CEN08 , CEN I0. CEN 11, CEN 13, CEN 16, CEN 17, CEN24, CEN26, CEN33
The CEN 18 IT system uses a multitude of security controls mandated by the Federal Information Security Management Act of2002 (FISMA) and various other regulatory control frameworks including the National Institute of Standards and Technology (NlST) special publication 800 series. These security controls include. but are not limited to the use of mandatory I ITTPS for public facing websites. access controls, anti-virus solutions, enterprise auditing/monitoring, encryption of data at rest, and various physical controls at Census facilities that house Information Technology systems. The Census Bureau also de lovs an enterprise Data Loss Protection (OLP) so lution as well. No, this IT system does not connect ,vith or receive information from another IT systcm(s) authorized to -~~ r_ocess PII and/or BIL__ _____ _ _

6.3 Identify the class of users who \Vill have access to the IT system and the PU/BU. (Check all that apply.)

e3 -

:_s-_:=r1f-:=i-~~~~-,-s-_-__-:-__---_~

-

11

o-n---tracto-r-s ----
her (specif)'):

- - - --- -- ----- ---~

------

---

Section 7: Notice and Consent

X _f-~_q_ov_me ment Emefoyces

_
-

-. -----=

7 .1 Indicate whether individuals will be notified if their PJJ/Bll is collected, maintained. or disseminated by the system. (Check al! that apply.)

---
'(
X
, ----+

--- - -- -- ------ ------

-- -------

- - -- ------ -- --

Yes. noti ce is provided pursuant to a system of records notic e published in the Federal Regi ste r and

discussed in Section 9.

----

------

--

Yes. notice is provided by a Privacy Act statement and/or privacy policy. The Privacy Act statement

and/or privacy policy can be found at: hlli\~://w\_!'.\!'..,_census.gov/al,m!!LpQ)i~cLi~_pri_yacvlp1j_y<J91-

120ilcy.html ____ _ _ _----

-- ~--

_ _____ ·_ ___ ___________

_

Yes, notic e is provid ed by other means . Specify how :

--- -------
N~i,_n_Q_ticics not provid ed. ___ ___~, p~'::.!f_wr hynot:

--
-----

- --- - -- - -- - - -- - -
--- - ---

7

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7.2 lndicate whether and how individuals have an opportunity to decline to provide Pll/B11.

Y cs, individuals have an opportunity to Specif:,·how:

--

decline to provide Pll/811.

-

X No, individuals do not have a11

Specify why not: PIL-'811is pulled from other Census Bureau

opportunity to decline to provide

Information Systems, therefore there is not an opportunity to

PII/B11.

decline to r,rovide Pll / 1311at the CEN l 8 system level.

7-3 lndicate whether and hov,1individuals have an opportunity to consent to pru1icular uses of their Pll/Bll.

,---~------------------,-----
Yes. individuals have an opportunity to

consent to particular uses of their

Pit/Bl I.

t-----t--

------------

X No, individuals do not have an

opportunity to consent to particular

uses of their PlliBII.

Specify how:
Specify why not:PII/B11 is pulled from other Census Bureau Informalion Systi:ms. therefore there is not an oppm1unity to consi;:ntto particular uses of Pll/B11at the CEN 18system level.

7.4 Indicate whether and how individuals have an opportunity to review/update PII/Bll pe1taining to them.

-

----------

Yes. individuals have an opportunity to

review/update Pll/BII pertaining lo

t-h-e--m--.----------No, individuals do not have an

opportunity to review/update Pll/Hll

P~Etainin~l them.

___

_

-- ·---
Specify how:

-----

·- ---- - --------------

Specify why not: PII/Bll is pulled from other Census Bureau

Information Systems. therefore then~ is not an opportunity to

rcvicwiup_datePll !l:311at_the CEN I 8~stcm level.

Section 8: Administrati"·e and Technological Controls

8.1 Indicate the administrative and technological controls for the system. {Check all that upp~v.j

-~- - ---------

-----

---

-----

--------

--

x All users signed a confidentiality agreement or non-disclosure ag:recmcnt.

x --All usi;;r~ar;-;,ubject to a Cml~~uct

that includes !he t'Ct)l~iremcnftor confid~

.

--

x __ Staff(~lovec s and contr.\ct~ received traini~ on priva..:yand confidentiality policies and practict:s.

x ~ccss lo_the Pll /Rl.!Js restricted to ~uthorized pcrsL~~,-~ only.

·- __ _ ____ . ___ _

x Access to the Pll/HI I is being monitored. tracked. or recorded.

Explanation : Only authorized government /contractor personnel are allov.1cclto access Pl I/Bil within a

system. Authorizations for users occur y.~arly, at a minimum in accordance with applicable Bureau,

Ag.ency,and Federal policies/guidelines. In addition, audit logs are in place and assessed per NIST

control Al./..-03, Co11/l!nt oj',-l11di1 records. ____ _

The information is secured in accordance with FISf'vlArequircm..:nts.

Provide date of most recent Assessment and Authorization (A&A) : July 20 . 2017

____ D This is a ncw_system._ The A&A elate will he provided when the A&A packagt~. is approv-e--d .
x The Federal Information Prm;cssing Standard (FIPS) 199 security impact category for this system is a

-~------m- oderate or hi•g·h--e-r--.--------------------------------

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~-~-

-- - - --- -

-

---- - ----

X N 1ST Special Publication (SP) 800-122 and NIST SP 800-5 3 Revision 4 Appendix J recommended

sec urity controls for protecting PII/B11are in place and functioning as intended: or have an approved Plan

of Action and Mile sto nes (POAM).

__ _ _____

__ ___

_ __ __ _

X Contractors that have access to the system are subject to infonnation security provision s in their contracts

re uirecl bv DOC."..£oJi9:.__ ___ _____

___ _ _

Contracts with customers establish ownership right s over data including Pll/B1 I. _ ______

_

Acceptance of liabilitv for e~xposureof PII/B11 is clearlv definej in a~ements with ·cu s!_on_e_11__·s.__ _

-Oth-~e~r (spec~if~y): ---

- ------

----

---

----

---

--- ----

8.2 Provide a general description of the technologies used to protect PII/Bll on the IT system.

-- ----

- - ----

Census Bureau Information technology systems employ a multitude oflayercd security

controls to protect BIi/PH at rest , during processing, as well as in transit. These NIST 800-53

controls, at a minimum, are deployed and managed at the enterprise level including, but not

limited to the following:
• Intrusion Detection I Prevention Systems (IDS I IPS)

• Firewalls

• Mandatory use of 1ITTP(S) for Census Public facing \vebsitcs

• Use of trusted internet connection (TIC)

• Anti-Virus so1hvare to protect host/end user systems

• Encryption of databases (Data at rest)

• l lSPD-12 Compliant PIV cards

• Access Controls

Census Bureau Information technology systems also follow the National Institute of

Standards an<lTechnology (NIST) standards including special publications 800-53 , 800-63 ,

800-37 etc. Any system within the Census that contains, transmits , or processes Bil/PI! has a

cmTent authority to operate (ATO) and goes through continuous monitoring on a yearly basis

to ensure controls arc implemented and operating as intended. The Census Bureau also

deploys a OLP solution as well. ___ ___ _____

___ ____

_ __ _____ _

Section 9: Privacy Act

9.1 Indicate \Yhether a system of records is being created under the Privacy Act, 5 U.S.C.

§ 552a. (A neH' system o_(records notice (SORN) is required i.(the system is not covered

by an existing SORN).

As per the Privacy /\ct of 1974, --11ict.:rm 's yslcm ,,fn:cord s' m..a: ns a group of any records und..:rthe c,,ntrol of any agency from whid1

informution is retrieved by the name of Lhc individual or by som.o identifying number , symbo l, or other idcntilyin g particular ,,ss igncd

to the individual."

·

-- - --- --- ---

- -- --

'(

Yes, this sys tem is covered by an existing system of record s notice (SORN) .

Provide the SORN name and number (list all that appzv):

COMMERCE /CENSUS-2 , Employee Productivity Measurement Records :
sf )1!.tg:// wwv. '.O_iC~.do.c.gov/ opo_g!PrivacyA_c:!L_QSE~ CCllSIJS-1. .\:!!1nl

COMMbRCE /CENSUS-3 , Special Censuses, Surveys, and Other Studies:
h.!tp;j/ www .ose~.dnc~w ijlQ_o_gLpvraicy/1 cli'.SO RN s/c_£n~us.:,,J:n.111.l

_ CENSUS-4, Economic Su~Collection:

_ _______

__ _____

____ _______

_

9

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h!!n://www.osec.doc.gov/opog/PrivacvAct/SORNs/census-4.html

COMMERCE/CENSUS-5, Decennial Census Program: http://www.osec.doc._gs_lv/opog/rPivarrActJSORN s/census-5. htmI

COMMERCE/CENSUS- 7, Special Censuses of Population Conducted for State and Local Government:
http://www.oseL:d. oc .gov/opog/ PrivacyAc:1/SORNsfcensus- 7.ljilll

COMMERCE/CENSUS-8, Statistical Administration Records Systems: /1Jtlli£www.osec.doc_,_g_y_[opog/ Priy_acvA ct/SORN s/censu s-8.htrnl

COMMERCE/CENSUS-(), Longitudinal Employer Household Dynamics System http://www.oscc.do.£gov/o.J2_0!.?./vParcivAct/SO RNs/census-9. htm I

COMMERCE/CENSUS-12. Foreign Trade Statistics:

http:![\"-'.}V~' .o;;e£. <l<£.1m.)/9&,g/ J_>riv_a_syf,.~Bt/S!__si(L)c~nsuf'- 12ll!mI_ __ _ __ ____

__ _ __

_Yes.J!_~ORN has been submitted to the Department ~~~pproval on (<:l~t~e--)--

No. a SORN is not being created.

_______

____ _ __ __ -- --- -~

Section 10: Retention of Information

10. I Indicate whether these records ·are covered by an approved records control schedule and monitored for compliance. (Check all that app~v.)

.\. There is an approv ed record control schedule .

- --

---· ------

Provide the mime of the record control schedule:

GRS 3.1 GRS 3.2 GRS 4 . 1. GRS 4.2, GRS 4.3

Demographic Directorate Nl -29-99-5, Nl -29-8()-3. Nl-29-87-3. Nl- 29-86-3. NC!- 2()-85-1. NCJ-2()-7()-7

Economics Directorate N 1-029-10-2, N 1-029-10-3. N 1-029- 12-004 . N 1-029-10--1

C'ompany Statistics Division NJ-:2()-10-1

Econo111icSurveys Division Nl-29-0 3-JN C l-29-80-1 5. NCl-29-79-4, NCl -29-78- 15 NCl -29-78-8

Manufacturing and Construction Division NCl-2()-81-10

Decennial Directorate Nl-29-05-01. Nl-29-10 -5

American Comm unity Survey

DAA-0029-201--5--000 l ------

-

---

No, there is not an approved record control schedule.

-- ·------

--- -----

-- --

Provide the sta/!e in which thc__1~_1:eocit is in develo~1_g c111sdubrnitti!_1a'. records control schedule:____ __

Yes, retention is monitored for co mpliance to the schedule . ______

___ _ __

No, retention is not monitored fc1rcompliance to the sched ule. Provide explanation :

------------

10

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I 0.2 Indicate the disposal method of the PH/BIi. (Check all that apply.)

Section 11: NIST Special Publication 800-122 PH Confidentiality Impact Levels

11.1 Indicate the potential impact that could result to the subject individuals and/or the organization if PU were inappropriately accessed, used, or disclosed.

-----------Low - the loss of confidentiality, integrity, or availability could be expected to have a limited adverse

effect on or~izational operations, or_g_anizatiorrnal ssets. or individualsc:.·-----------

Moderate the loss of confidentiality, integrity, or availability could be expected to have a serious

adverse effoct on £!"ganl!-~t_ional_9~1ions 1_~rganizational assets, or individu~t_!~----

_____ _

X High - the loss of confidentiality, integrity, or availability could be expected to have a severe or

catastro_ebjc adverse effect on organi7.,ational o~rations, organizational assets, or individmils. ____ _

11.2 fndicate which factors ,vere used to determine the above Pll confidentiality impact levels. (Check all that apply.)

----

--- ----

X ldenlifiability

X Quantity of Pl I

X Data Field Sensitivity

X Context of Use

X Obligation to Protect Confidentiality

>--- -t------

- ------

--

X Access to anJ Location of Pl1

X Identifiability
Section 12: Analysis

--- -- -------

-----

--------

Provide explanation: PlliBII collected can be directly used to

id~individuals

____________

_

Provide explanation: The collection is for demographic,

Economic Surveys, and other surveys, and therefore , a severe or

catastrophic number of individuals would be affected if there was

lo~. ~et1 or compromise of the data. ____________

_

Provide explanation: The PII/Rll, alone or in combination, are

directly usable in other contexts and make the individual or

organization vulnerable to harms, such as identity theft.

-e--m- barrassm--ent,-·- lo-s-s--o--f--tr-ust, or costs. -------------Provide explanation: Disclosure of the act of col lect ing and using

the PII/B11 in this IT system or the PlliBII itself may result in

severe or_catastrophic harm to the individual or ~anization.

__

Provide explanation: Pll/Rll collected is required to be protected

in accordance Title 13 co1lections. Violations may result in severe

~i_v~~!:_crimina[penaltics. ____________

_

Pll!BII is located on computers controlled by the Census Bureau

or on mobile devices or storage media. Access is Iimited to cc1iain

populations of the Census Bureau's worlforce and limited to

Special Sworn Status individuals. Access is only allowed by

organization-owned equipment outside of the physical locations.

and only with a secured connection. _______

_

Provide explanation: PII/B II collected can be directly used to

ide_!lt_iJ\_.l!)c!i_vidu_~__l!_>__________

----··

11

Case 1:18-cv-02711-DLF Document 8-5 Filed 01/18/19 Page 75 of 75
Version Number: 01-2015

12.1 Indicate whether the conduct of this PIA result~ in any required business process changes.

------Yes, the conduct of this PIA results in required business process changes. Explanation:

-------

x No, the conduct of this PIA does not result in an , re< uired business )roccss chan~es.

12.2 Indicate \Vhcthcr the conduct of this PIA results in any required technology changes .

.----r-----

-------------------------

Yes. the conduct of this PIA results in required technology changl.!s.

Explanation :

------------

-------

12

Case 1:18-cv-02711-DLF Document 8-6 Filed 01/18/19 Page 1 of 24
Exhibit 10

Case 1:18-cv-02711-DLF Document 8-6 Filed 01/18/19 Page 2 of 24

IN THE UNITEDSTATES DISTRICTCOURT FOR THE DISTRICTOF COLUMBIA

ELECTRONICPRIYACY INFORMATION CENTER,
Plaintiff,
V.
UNITED STATES DEPARTMENT OF COMMERCE, et al.,
Defendants.

Civ. Action No. 18-2711

DECLARATIONOF CHRISTOPHERWOLF I, Christopher Wolf, declare as follows:
I. My name is Christopher Wolf. I am over 18 years old. The information in this declaration is based on my personal knowledge.
2. I reside in Washington, DC, United States of America. 3. I am Senior Counsel in a Washington, DC law firm, focusing on privacy law. 4. The Electronic Privacy Information Center ("EPIC") is a non-profit, public interest
research center established in 1994 to focus public attention on emerging privacy and civil liberties issues. Central to EPIC's mission is oversight of government activities that impact individual privacy, free expression, and democratic values . EPIC has a particular interest in preserving legal privacy protections for personal data, including the obligation of federal agencies to conduct privacy impact assessments. 5. I am a member of EPIC. EPIC's members are distinguished experts in law, technology, and public policy. As a member of EPIC, I serve on the EPIC Advisory Board, participate

Scanned with CamScanner

Case 1:18-cv-02711-DLF Document 8-6 Filed 01/18/19 Page 3 of 24
in the activities of EPIC. help finance the activities of EPIC. and provide leadership for EPIC. I also pay annual membershipdues. as required by the amended EPIC bylaws. 6. I becamean EPIC Member because I am concerned about protecting privacy. freedom of expression,and democratic values in the infonnntion age. As privacy lawyer. EPIC's workon these issues is of special importanceto me. 7. EPIC works on my behalf to protect my privacy rights. and l rely on EPIC to obtain and disseminateinfonnation about governmentactivities that threaten my privacy. 8. As a resident of the United States, I understandthnt the Census Bureau intends to nsk for my citizenship status on the 2020 Census. By law, l nm required to provide n truthful response to such a question. 9. The Census Bureau has indicated that it may disclose my citizenship status to other federal agencies, including for criminallaw enforcementpurposes. I0. The imminentcollection and possibledisclosureof my citizenship status by means of the 2020 Census is an unwarrantedinvasionof my privacyand would cause me irrepnrnble harm by exposing my personal information.I do not consent to the collection or disclosure of my citizenship status. I J. The Census Bureau is required to produceand publish n comprehensive Privacy Impact Assessment("PIA") when it beginsto develop n new collection of personnldntn,such ns the citizenship status of every person in the United States. 12.I understandthat the Census Bureau intends to collect, process. and store personal data concerningcitizenship status using five separate Bureausystems: CEN0S. CEN08, CEN11,CEN13,and CEN18.
2
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Case 1:18-cv-02711-DLF Document 8-6 Filed 01/18/19 Page 4 of 24
13. On my behalf, EPIC sought the five required Privacy Impact Assessments analyzing the collection, processing, and storage of personal data concerning citizenship status. I also sought the five required Privacy Impact Assessments myself by visiting the webpage where Census Bureau PIAs are published .1
14. For each of the five CEN systems, the Census Bureau failed to publish a Privacy Impact Assessment that adequately analyzed the collection , processing, and storage of personal data concerning citizenship status. I have therefore been denied information to which I am legally entitled concerning the privacy implications of the Census Bureau's citizenship question.
15. Moreover, I have been irreparably harmed by the Census Bureau's unlawful failure to publish the required Privacy Impact Asse ssments. I am unable to determine whether the Census Bureau has fully considered or addressed the risks to my privacy, even as the Bureau begins to develop a new collection of personal data that will contain my citizenship status .
I declare under penalty of perjury that, to the best of my knowledge, the foregoing is true and correct.
Executed on November 29, 2018
1 http ://www.osec .doc.gov/opog/pri vacy/Census-pias .html . 3
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Case 1:18-cv-02711-DLF Document 8-6 Filed 01/18/19 Page 5 of 24
Exhibit 11

Case 1:18-cv-02711-DLF Document 8-6 Filed 01/18/19 Page 6 of 24

IN THE UNITED STATES DISTRICT COURT FOR THE DISTRICT OF COLUMBIA

ELECTRONIC PRIVACY INFORMATION CENTER, Plaintiff, v.
UNITED STATES DEPARTMENT OF COMMERCE, et al.,
Defendants.

Civ. Action No. 18-2711

DECLARATION OF BRUCE SCHNEIER I, Bruce Schneier, declare as follows:
1. My name is Bruce Schneier. I am over 18 years old. The information in this declaration is based on my personal knowledge.
2. I reside in Minneapolis, Minnesota, United States of America. 3. I am a Special Advisor to IBM Security. I am a fellow and lecturer at the Harvard
Kennedy School. I am also an author and speaker on security and privacy topics. 4. The Electronic Privacy Information Center (“EPIC”) is a non-profit, public interest
research center established in 1994 to focus public attention on emerging privacy and civil liberties issues. Central to EPIC’s mission is oversight of government activities that impact individual privacy, free expression, and democratic values. EPIC has a particular interest in preserving legal privacy protections for personal data, including the obligation of federal agencies to conduct privacy impact assessments. 5. I am a member of EPIC. EPIC’s members are distinguished experts in law, technology, and public policy. As a member of EPIC, I serve on the EPIC Advisory Board, participate
1

Case 1:18-cv-02711-DLF Document 8-6 Filed 01/18/19 Page 7 of 24
in the activities of EPIC, help finance the activities of EPIC, and provide leadership for EPIC. I also pay annual membership dues, as required by the amended EPIC bylaws. 6. I became an EPIC member because I am concerned about protecting privacy, freedom of expression, and democratic values in the information age. As someone who thinks, works, and writes about digital privacy, EPIC’s work on these issues is of special importance to me. 7. EPIC works on my behalf to protect my privacy rights, and I rely on EPIC to obtain and disseminate information about government activities that threaten my privacy. 8. As a resident of the United States, I understand that the Census Bureau intends to ask for my citizenship status on the 2020 Census. By law, I am required to provide a truthful response to such a question. 9. The Census Bureau has indicated that it may disclose my citizenship status to other federal agencies, including for criminal law enforcement purposes. 10. The imminent collection and possible disclosure of my citizenship status by means of the 2020 Census is an unwarranted invasion of my privacy and would cause me irreparable harm by exposing my personal information. I do not consent to the collection or disclosure of my citizenship status. 11. The Census Bureau is required to produce and publish a comprehensive Privacy Impact Assessment (“PIA”) when it begins to develop a new collection of personal data, such as the citizenship status of every person in the United States. 12. I understand that the Census Bureau intends to collect, process, and store personal data concerning citizenship status using five separate Bureau systems: CEN05, CEN08, CEN11, CEN13, and CEN18.
2

Case 1:18-cv-02711-DLF Document 8-6 Filed 01/18/19 Page 8 of 24
13. On my behalf, EPIC sought the five required Privacy Impact Assessments analyzing the collection, processing, and storage of personal data concerning citizenship status. I also sought the five required Privacy Impact Assessments myself by visiting the webpage where Census Bureau PIAs are published.1
14. For each of the five CEN systems, the Census Bureau failed to publish a Privacy Impact Assessment that adequately analyzed the collection, processing, and storage of personal data concerning citizenship status. I have therefore been denied information to which I am legally entitled concerning the privacy implications of the Census Bureau’s citizenship question.
15. Moreover, I have been irreparably harmed by the Census Bureau’s unlawful failure to publish the required Privacy Impact Assessments. I am unable to determine whether the Census Bureau has fully considered or addressed the risks to my privacy, even as the Bureau begins to develop a new collection of personal data that will contain my citizenship status.
I declare under penalty of perjury that, to the best of my knowledge, the foregoing is true and correct.
Executed on November 30, 2018
Bruce Schneier
1 http://www.osec.doc.gov/opog/privacy/Census-pias.html. 3

Case 1:18-cv-02711-DLF Document 8-6 Filed 01/18/19 Page 9 of 24
Exhibit 12

Case 1:18-cv-02711-DLF Document 8-6 Filed 01/18/19 Page 10 of 24

IN THE UNITED STATES DISTRICT COURT FOR THE DISTRICT OF COLUMBIA

ELECTRONIC PRIVACY INFORMATION CENTER, Plaintiff,
V.
UNITED STATES DEPARTMENT OF COMMERCE, et al.,
Defendants.

Civ. Action No. 18-2711

DECLARATION OF HARRY R. LEWIS I, Harry R. Lewis, declare as follows:
1. My name is Harry R. Lewis. I am over 18 years old. The information in this declaration is based on my personal knowledge.
2. I reside in Brookline, Massachusetts United States of America. 3. I am Gordon McKay Professor of Computer Science at Harvard University. 4. The Electronic Privacy Information Center ("EPIC") is a non-profit, public interest
research center established in 1994 to focus public attention on emerging privacy and civil liberties issues. Central to EPIC's mission is oversight of government activities that impact individual privacy, free expression, and democratic values. EPIC has a particular interest in preserving legal privacy protections for personal data, including the obligation of federal agencies to conduct privacy impact assessments. 5. I am a member of EPIC. EPIC's members are distinguished experts in law, technology, and public policy. As a member of EPIC, I serve on the EPIC Advisory Board, participate

1

Case 1:18-cv-02711-DLF Document 8-6 Filed 01/18/19 Page 11 of 24
in the activities of EPIC, help finance the activities of EPIC, and provide leadership for EPIC. I also pay annual membership dues, as required by the amended EPIC bylaws. 6. I became an EPIC member because I am concerned about protecting privacy, freedom of expression, and democratic values in the information age. As a professor of computer science, EPIC's work on these issues is of special importance to me. 7. EPIC works on my behalf to protect my privacy rights, and I rely on EPIC to obtain and disseminate information about government activities that threaten my privacy. 8. As a resident of the United States, I understand that the Census Bureau intends to ask for my citizenship status on the 2020 Census. By law, I am required to provide a truthful response to such a question. 9. The Census Bureau has indicated that it may disclose my citizenship status to other federal agencies, including for criminal law enforcement purposes. 10. The imminent collection and possible disclosure of my citizenship status by means of the 2020 Census is an unwarranted invasion of my privacy and would cause me irreparable harm by exposing my personal information. I do not consent to the collection or disclosure of my citizenship status. 11. The Census Bureau is required to produce and publish a comprehensive Privacy Impact Assessment ("PIA") when it begins to develop a new collection of personal data, such as the citizenship status of every person in the United States. 12. I understand that the Census Bureau intends to collect, process, and store personal data concerning citizenship status using five separate Bureau systems: CEN05, CEN08, CENl 1, CEN13, and CEN18.
2

Case 1:18-cv-02711-DLF Document 8-6 Filed 01/18/19 Page 12 of 24
13. On my behalf, EPIC sought the five required Privacy Impact Assessments analyzing the collection, processing, and storage of personal data concerning citizenship status. I also sought the five required Privacy Impact Assessments myself by visiting the webpage where Census Bureau PIAs are published. 1
14. For each of the five CEN systems, the Census Bureau failed to publish a Privacy Impact Assessment that adequately analyzed the collection, processing, and storage of personal data concerning citizenship status. I have therefore been denied information to which I am legally entitled concerning the privacy implications of the Census Bureau's citizenship question.
15. Moreover, I have been irreparably harmed by the Census Bureau's unlawful failure to publish the required Privacy Impact Assessments. I am unable to determine whether the Census Bureau has fully considered or addressed the risks to my privacy , even as the Bureau begins to develop a new collection of personal data that will contain my citizenship status.
I declare under penalty of perjury that, to the best of my knowledge, the foregoing is true and correct.
Executed on December 3, 2018
1 http://www.osec.doc.gov/opog/privacy/Census-pias.html. 3

Case 1:18-cv-02711-DLF Document 8-6 Filed 01/18/19 Page 13 of 24
Exhibit 13

Case 1:18-cv-02711-DLF Document 8-6 Filed 01/18/19 Page 14 of 24

epic.org

Electronic Privacy Information Center 1718 Connecticut Avenue NW, Suite 200 Washington, DC 20009, USA

\. +1 202 483 1140 ~ +1 202 483 1248
I# @EPICPrivacy $ https://epic.org

COMMENTS OF THE ELECTRONIC PRIVACY INFORMATION CENTER to the U.S. CENSUS BUREAU 2020 Census 83 FR 26643 August 7, 2018

The Electronic Privacy Information Center (“EPIC”) submits these comments in response to the Census Bureau’s notice1 on the 2020 decennial census.
EPIC is a public interest research center established in 1994 to focus public attention on emerging privacy and civil liberties issues. The Census implicates numerous privacy issues.2 We ask you to consider the risks of personal data being used for purposes that may undermine the integrity, reliability, and purpose of the U.S. census. EPIC specifically asks the Census Bureau to suspend the citizenship question from the 2020 census form until a thorough and updated Privacy Impact Assessment is conducted. So far, the Bureau has failed to demonstrate the data gathered from that particular question will not undermine the privacy rights of those who respond to the census.
EPIC has particular expertise with the misuse of census data after 9-11. And documents EPIC obtained under the Freedom of Information Act led to important reforms at the agency. We urge you not to take our comments lightly.
EPIC supports the work of the Census Bureau and the use of statistical analysis in policymaking and other government initiatives.3 The Census is an essential part of understanding the changing demographics in America. The census helps ensure evidence-based policy decisions and census data is the source of much political and economic planning in the United States. However, it is of the utmost importance the individual privacy is respected. Every effort must be taken to ensure that the personal information of individuals and that census data is not used improperly.

1 U.S. Census Bureau, Proposed Information Collection; Comment Request; 2020 Census, Notice, 83 FR 26643 (June 8, 2018), https://www.federalregister.gov/documents/2018/06/08/201812365/proposed-information-collection-comment-request-2020-census. 2 The Census and Privacy, EPIC, https://epic.org/privacy/census/. 3 EPIC testified before the Commission on Evidence-Based Policymaking and called for the Commission to adopt innovative privacy safeguards to protect personal data and make informed public policy decisions. Marc Rotenberg, Commission on Evidence-Based Policymaking: Privacy Perspectives, before the National Academies of Science, Sep. 9, 2016, https://epic.org/privacy/wiretap/RotenbergCEBP-9-16.pdf.

Privacy is a Fundamental

Right.

Case 1:18-cv-02711-DLF Document 8-6 Filed 01/18/19 Page 15 of 24

EPIC knows that the Census Bureau takes its confidentiality requirements seriously4 and that some of the strictest privacy laws in the U.S. apply to census data.5 But the addition of the citizenship question to the 2020 census raises new privacy issues. The Privacy Impact Assessment for the census indicates that the Bureau has not given proper consideration to these issues.
There has been greater concern about the confidentiality of 2020 census data than in previous decennial censuses. The Census Bureau conducted a study in 2017 that found respondents expressing new concerns including the “Muslim ban,” the dissolution of DACA, and Immigration and Customs Enforcement.6 The study found that these concerns were most pronounced among immigrant respondents.7
Part I discusses prior abuses of census data, to remind the Bureau that fears of 2020 census data being misused are not abstract. Part II explains why census data should never be used for enforcement purposes. Part III addresses the data integrity issues caused by the addition of the untested question. Part IV describes the Bureau’s Privacy Impact Assessment and why it does not address the privacy risks raised by the addition of the citizenship question.

I. Past Misuses of Census Data
Despite strong census privacy laws, the U.S. has a sordid history of misusing census data to target minority groups. The most egregious misuse of census data was the role it played in the internment of Japanese-Americans during World War II.8 In 1943 the Census Bureau complied with a request by the Treasury Secretary for the names and locations of all people of Japanese ancestry in the Washington, D.C., area.9 The Bureau should remember this human rights abuse every time another agency requests census data.
After 9-11, EPIC pursued a Freedom of Information Act request about the potential misuse of census data. Documents obtained by EPIC revealed that the Census Bureau had provided the

4 Ron Jarmin, The U.S. Census Bureau’s Commitment to Confidentiality, Census Blog (May 7, 2018) https://census.gov/newsroom/blogs/director/2018/05/the_u_s_census_bure.html. 5 92 Stat. 915; Public Law 95-416. The Census Bureau cannot disclose “personally identifiable information about an individual to any other individual or agency until 72 years after it was collected for the decennial census.” 6 Center for Survey Measurement, MEMORANDUM FOR Associate Directorate for Research and Methodology (ADRM) Respondent Confidentiality Concerns (Sept. 20, 2017), https://www2.census.gov/cac/nac/meetings/2017-11/Memo-Regarding-Respondent-ConfidentialityConcerns.pdf. 7 Id. at 1. 8 JR Minkel, Confirmed: The U.S. Census Bureau Gave Up Names of Japanese-Americans in WW II, Scientific American (March 30, 2007), https://www.scientificamerican.com/article/confirmed-theus-census-b/. 9 W. Seltzer and M. Anderson, “Census Confidentiality under the Second War Powers Act (19421947).” Paper prepared for presentation at the annual meeting of the Population Association of America, New York, March 29-31, 2007, available at http://studylib.net/doc/7742798/censusconfidentiality-under-the-second-war-powers.

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2

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Case 1:18-cv-02711-DLF Document 8-6 Filed 01/18/19 Page 16 of 24

Department of Homeland Security (“DHS”) with census data on individuals of Arab ancestry.10 In 2004 EPIC obtained documents revealing that the Census Bureau provided the DHS statistical data on people who identified themselves on the 2000 census as being of Arab ancestry. The special tabulations were prepared specifically for the law enforcement agency. There is no indication that the Department of Homeland Security requested similar information about any other ethnic groups.
One document,11obtained by EPIC, shows cities with populations of 10,000 or more and with 1,000 or more people who indicated they are of Arab ancestry. For each city, the tabulation provides total population, population of Arab ancestry, and percent of the total population which is of Arab ancestry. The tabulations were produced using data from the 2000 census long-form questionnaire, which goes to only a sample of the population. A second document12 shows the number of census responses indicating Arab ancestry in certain zip codes throughout the country. The responses indicating Arab ancestry are subdivided into Egyptian, Iraqi, Jordanian, Lebanese, Moroccan, Palestinian, Syrian, Arab/Arabic, and Other Arab. Although this data was not personally identifiable, its disclosure to a law enforcement agency was unethical.
The reason DHS gave for requesting these tabulations was to determine which languages signs should be in at international airports.13 Heavily redacted emails14 between a Census Bureau analyst and a DHS official show that the Bureau gave the documents before the intended purpose for the data was known and that this explanation was given after the tabulations had already been disclosed. The ex-post-facto reason given by DHS seems pretextual.
As a result of these revelations, resulting from EPIC’s FOIA litigation, the Census Bureau revised its policy on sharing statistical information about "sensitive populations" with law enforcement or intelligence agencies. Customs and Border Protection also changed its policy on requesting "information of a sensitive nature from the Census Bureau."15
EPIC’s FOIA efforts led the Census Bureau to implement new procedures regarding the release of “potentially sensitive data to requesting law enforcement agencies and organizations or individuals.”16 EPIC supported those efforts but recognizes also the ongoing concerns about the
10 Department of Homeland Security Obtained Data on Arab Americans From Census Bureau, EPIC, https://epic.org/privacy/census/foia/; Lynette Clemetson, Homeland Security Given Data on Arab-Americans, New York Times, Jul. 30, 2004, http://www.nytimes.com/2004/07/30/us/homeland-security-given-data-on-arab-americans.html. 11 EPIC FOIA, Tabulation 1: "Places with 10,000 or More Population and with 1,000 or More Persons of Arab Ancestry: 2000" https://epic.org/privacy/census/foia/tab_1.pdf. 12 EPIC FOIA, Tabulation 2: “People of Arab Ancestry by ZIP Code Tabulation Area: 2000” https://epic.org/privacy/census/foia/tab_2.pdf. 13 EPIC FOIA, https://epic.org/privacy/census/foia/census_emails.pdf. 14 Id. 15 U.S. Customs and Border Protection, Policy for Requesting Information of a Sensitive Nature from the Census Bureau, Memorandum (Aug. 9, 2004), https://epic.org/privacy/census/foia/policy.pdf. 16 Census Bureau News, ‘‘U.S. Census Bureau Announces Policy Regarding Sensitive Data,’’ press release CB04-145, August 30, 2004; Lynette Clemetson, Census Policy On Providing Sensitive Data Is Revised, New York Times, Aug. 31, 2004, http://www.nytimes.com/2004/08/31/us/census-policyon-providing-sensitive-data-is-revised.html.

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Case 1:18-cv-02711-DLF Document 8-6 Filed 01/18/19 Page 17 of 24
potential misuse of data collected by government agencies. Amid rising fears that some minority groups may be targeted by law enforcement agencies, your committee should ensure that the data collected by the federal government is not misused.
II. Census Data Should Never Be Used for Enforcement Purposes
Using census data to help enforce laws is a corruption of the decennial census’s constitutional purpose. The Department of Justice (“DOJ”) requested the citizenship question on the census would allow the agency to better enforce Section 2 of the Voting Rights Act, which bars the dilution of voting power of a minority group through redistricting. DOJ wants census-block-level data for locations where they suspect Section 2 violations have occurred.
The decennial census’s statistical purpose is frustrated when other agencies ask it to collect data for other purposes. The DOJ’s responsibility to enforce the Voting Rights Act is vital to ensuring fair elections. In its request to the Bureau, the DOJ called the decennial census the “most appropriate vehicle” for collecting data on the citizen voting-age population.17 EPIC disagrees with this assertion. The decennial census was never intended to be a catch-all data collection to assist other federal agencies. In fact, the statutes concerning the privacy of census data are meant to expressly prohibit this.
If the Census Bureau gets into the business of collecting data because it will assist other federal agencies enforce laws, it will be difficult to stay true to its constitutional purpose of conducting impartial statistical analysis. And it will undermine the integrity, accuracy, and reliability of the census. As a former director of the Bureau succinctly put it thirteen years ago: “The Census Bureau cannot become a quasi-investigatory agency and still perform its basic responsibilities as a statistical agency.”18 The Bureau does not serve an investigatory function and the DOJ (or any other agency) should not expect it to.
III. Data Integrity
When a new question is added this late in preparations for the 2020 census, the burden of proof is on those proposing the new question to establish that it will not impact the integrity of the data collected. The fact that the 2020 census will have an additional question—regardless of what the question asks—is likely to yield lower response rates. As Secretary Ross told Congress: “One of the problems with adding questions is reduced response rates. It may seem counterintuitive, but the

17 Re: Request to Reinstate Citizenship Question on 2020 Census Questionnaire (Dec. 12, 2017), https://www.documentcloud.org/documents/4340651-Text-of-Dec-2017-DOJ-letter-to-Census.html. 18 Counting the Vote: Should Only U.S. Citizens be Included in Apportioning Our Elected Representatives?, Hearing Before Subcomm. on Federalism and the Census of the H. Comm. on Gov’t Reform, 109th Cong. 77 (2005) (statement of former director of U.S. Census Bureau Kenneth Prewitt).

EPIC Comments Census Bureau

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Case 1:18-cv-02711-DLF Document 8-6 Filed 01/18/19 Page 18 of 24
more things you ask in those forms, the less likely you are to get them in.”19 And the fact that the new question has not been tested will create further problems with the integrity of the 2020 census data.
Six former directors of the Census Bureau—who served under both Republican and Democrat administrations—wrote to Secretary Ross to warn him that adding a new question to the 2020 census without adequate testing “at this late point in the decennial planning process would put the accuracy of the enumeration and success of the census in all communities at grave risk.”20 The typical process for adding new questions takes multiple years and requires extensive testing. Not only did the citizenship question not go through this process, but it was added after the 2018 End— to—End Census Test was already underway, so it was not even tested in what is meant to be the “dress rehearsal” for the 2020 census.
The former directors said: “even small changes in survey question order, wording, and instructions can have significant, and often unexpected, consequences for the rate, quality, and truthfulness of response.”21 But this is a significant change: a new question on a sensitive topic. In addition to a lower response rate, the question would cause an increase in inaccurate responses because “[t]here would be little incentive for non-citizens to offer to the government their actual status.”22
IV. Insufficiency of Privacy Impact Assessment
The Privacy Impact Assessment (“PIA”) for the 2020 decennial census23 indicates that the Census Bureau has not undertaken an appropriate analysis of the privacy risks of the citizenship question. “Citizenship” is listed as “other general personal data” that will be collected by the census.24 But, where the Bureau is required to indicate the status of the information system, it selects: “This is an existing information system without changes that create new privacy risks.”25 There is no analysis of the new question.

19 Rep. Jimmy Gomez Questions Secretary Ross at Oversight Hearing (Oct. 12, 2017), https://www.cspan.org/video/?c4685802/rep-jimmy-gomez-questions-secretary-ross-oversight-hearing?c4685802/repjimmy-gomez-questions-secretary-ross-oversight-hearing/video/. 20 Letter of Former Directors of U.S. Census Bureau to The Honorable Wilbur L. Ross (Jan. 26, 2018), https://www.washingtonpost.com/r/2010-2019/WashingtonPost/2018/03/27/EditorialOpinion/Graphics/DOJ_census_ques_request_Former_Directors_ltr_to_Ross.pdf. 21 Id. 22 Brief of Amici Curiae, Evenwel v. Abbot, at 25, http://www.scotusblog.com/wp-
content/uploads/2015/10/Evenwel-FormerCensusBureauDirectorsBrief092515.pdf (Amici are former directors of the Census Bureau). 23 U.S. Department of Commerce, U.S. Census Bureau, Privacy Impact Assessment for the CEN08 Decennial Information Technology Division (July 28, 2018) http://www.osec.doc.gov/opog/privacy/Census%20PIAs/CEN08_PIA_SAOP_Approved.pdf. 24 Id. at 3. 25 Id. at 2.

EPIC Comments Census Bureau

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Case 1:18-cv-02711-DLF Document 8-6 Filed 01/18/19 Page 19 of 24

The PIA does not satisfy the Department of Commerce’s own standards.26 A PIA must be updated “where a system change creates new privacy risks.” The Department of Commerce lists nine examples of new privacy risks, and the addition of the citizenship question and the stated purposes for doing so would create at least four of those risks.
The new question would alter the character of the data: “when new information in identifiable form added to a collection raises the risks to personal privacy (for example, the addition of health or financial information).”27 Citizenship data is new information and it is identifiable because it is collected alongside the other information of the person filling out the census form. Immigration status added to the collection of the other demographic data collected by the census undeniably raises the risk to personal privacy. If that privacy were to be violated, that information could be used against the respondent for deportation or other purposes.
The PIA does not acknowledge the privacy risks raised by the new question and the Bureau should conduct a new PIA dealing specifically with the issues raised by the citizenship question.
Conclusion
EPIC recommends that the Census Bureau either remove the citizenship question or conducted a revised Privacy Impact Assessment, taking account of the recently added question, as is required by law. The question raises far-reaching privacy concerns and will also undermine the integrity, reliability and accuracy of the U.S. census.
EPIC has recently pursued related matters concerning the privacy of census data with the Census Bureau that were favorably resolved. We anticipate that will be the outcome here

Sincerely,

/s/ Marc Rotenberg Marc Rotenberg EPIC President

/s/ Christine Bannan Christine Bannan EPIC Administrative Law and Policy Fellow

26 U.S. Department of Commerce, Office of Privacy and Open Government, Privacy Compliance
http://www.osec.doc.gov/opog/privacy/compliance.html. 27 Id. “Alteration in Character of Data” is the ninth example in the list of privacy risks.

EPIC Comments Census Bureau

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Case 1:18-cv-02711-DLF Document 8-6 Filed 01/18/19 Page 20 of 24
Exhibit 14

Case 1:18-cv-02711-DLF Document 8-6 Filed 01/18/19 Page 21 of 24

epic.org

Electronic Privacy Information Center 1718 Connecticut Avenue NW, Suite 200 Washington, DC 20009, USA

\. +1202483 1140 ljiiiji+1 202 483 1248 ~ @EPICPrivacy
(@ https:/ /epic.org

October 2, 2018
The Honorable Ron Johnson, Chairman The Honorable Claire McCaskill, Ranking Member U.S. Senate Committee on Homeland Security & Government Affairs 340 Dirksen Senate Office Building Washington, DC 20510
Dear Chairman Johnson and Ranking Member McCaskill:
We write to you regarding the nomination hearing of Steven D. Dillingham to be Director of the Census”1 EPIC is a public interest research center established in 1994 to focus public attention on emerging privacy and civil liberties issues. EPIC takes no position for or against the nominee. However, the Census implicates numerous privacy issues.2 EPIC specifically asks the Census Bureau to suspend the citizenship question from the 2020 census form until a thorough and updated Privacy Impact Assessment is conducted. The Bureau has failed to demonstrate the data gathered from that particular question will not undermine the privacy rights of those who respond to the census.
EPIC supports the work of the Census Bureau and the use of statistical analysis in policymaking and other government initiatives.3 The Census is an essential part of understanding the changing demographics in America. The census helps ensure evidence-based policy decisions and census data is the source of much political and economic planning in the United States. However, it is of the utmost importance the individual privacy is respected. Every effort must be taken to ensure that the personal information of individuals and that census data is not used improperly.
Through a Freedom of Information Act request EPIC has obtained documents regarding Secretary Ross’s decision to add the citizenship question to the 2020 Census.4 The documents obtained by EPIC reflect the varying opinions from lawmakers, scientists, and immigration groups

1 Nomination of Steven D. Dillingham to be Director of the Census, 115th Cong. (2018), S. Comm. on Homeland Security & Governmental Affairs, https://www.hsgac.senate.gov/hearings/09/25/2018/nominations (October 3, 2018). 2 The Census and Privacy, EPIC, https://epic.org/privacy/census/. 3 EPIC testified before the Commission on Evidence-Based Policymaking and called for the Commission to adopt innovative privacy safeguards to protect personal data and make informed public policy decisions. Marc Rotenberg, Commission on Evidence-Based Policymaking: Privacy Perspectives, before the National Academies of Science, Sep. 9, 2016, https://epic.org/privacy/wiretap/RotenbergCEBP-9-16.pdf. 4 FOIA Production 1, https://epic.org/foia/censusbureau/EPIC-18-03-22-Census-Bureau-FOIA-20180611Production-1.pdf; FOIA Production 2, https://epic.org/foia/censusbureau/EPIC-18-03-22-Census-BureauFOIA-20180611-Production-2.pdf; FOIA Production 3, https://epic.org/foia/censusbureau/EPIC-18-03-22Census-Bureau-FOIA-20180611-Production-3.pdf; FOIA Production 4, https://epic.org/foia/censusbureau/EPIC-18-03-22-Census-Bureau-FOIA-20180611-Production-4.pdf.

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about the proposal. The documents also reveal that Kris Kobach, former Vice Chair of the nowdefunct Presidential Advisory Commission on Election Integrity, urged Secretary Ross "on the direction of Steve Bannon" to add the citizenship question. According to an analysis conducted by the Census Bureau, the impact of asking about citizenship would be "very costly, harms the quality of the census count, and would use substantially less accurate citizenship data than are available" from other government resources.
I. Past Misuses of Census Data
There is substantial concern about the confidentiality of census data as a result of Secretary Ross’s decision to add a citizenship question to the 2020 census. Despite strong census privacy laws, the U.S. has a sordid history of misusing census data to target minority groups. The most egregious misuse of census data was the role it played in the internment of Japanese-Americans during World War II.5 In 1943 the Census Bureau complied with a request by the Treasury Secretary for the names and locations of all people of Japanese ancestry in the Washington, D.C., area.6 The Bureau should remember this human rights abuse every time another agency requests census data.
EPIC has a strong interest in the government’s use of Census data. After 9-11, EPIC pursued a Freedom of Information Act request about the transfer of Census data to the Department of Homeland Security. Documents obtained by EPIC revealed that the Census Bureau had provided the Department of Homeland Security (“DHS”) with census data on individuals of Arab ancestry.7 In 2004 EPIC obtained documents revealing that the Census Bureau provided the DHS statistical data on people who identified themselves on the 2000 census as being of Arab ancestry. The special tabulations were prepared specifically for the law enforcement agency. There is no indication that the Department of Homeland Security requested similar information about any other ethnic groups.
One document,8 obtained by EPIC, shows cities with populations of 10,000 or more and with 1,000 or more people who indicated they are of Arab ancestry. For each city, the tabulation provides total population, population of Arab ancestry, and percent of the total population which is of Arab ancestry. The tabulations were produced using data from the 2000 census long-form questionnaire, which goes to only a sample of the population. A second document9 shows the number of census responses indicating Arab ancestry in certain zip codes throughout the country. The responses

5 JR Minkel, Confirmed: The U.S. Census Bureau Gave Up Names of Japanese-Americans in WW II, Scientific American (March 30, 2007), https://www.scientificamerican.com/article/confirmed-the-us-census-
b/. 6 W. Seltzer and M. Anderson, “Census Confidentiality under the Second War Powers Act (1942-1947).” Paper prepared for presentation at the annual meeting of the Population Association of America, New York, March 29-31, 2007, available at http://studylib.net/doc/7742798/census-confidentiality-under-the-second-
war-powers. 7 Department of Homeland Security Obtained Data on Arab Americans From Census Bureau, EPIC, https://epic.org/privacy/census/foia/; Lynette Clemetson, Homeland Security Given Data on Arab-Americans,
New York Times, Jul. 30, 2004, http://www.nytimes.com/2004/07/30/us/homeland-security-given-data-on-
arab-americans.html. 8 EPIC FOIA, Tabulation 1: "Places with 10,000 or More Population and with 1,000 or More Persons of Arab
Ancestry: 2000" https://epic.org/privacy/census/foia/tab_1.pdf. 9 EPIC FOIA, Tabulation 2: “People of Arab Ancestry by ZIP Code Tabulation Area: 2000”
https://epic.org/privacy/census/foia/tab_2.pdf.

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indicating Arab ancestry are subdivided into Egyptian, Iraqi, Jordanian, Lebanese, Moroccan, Palestinian, Syrian, Arab/Arabic, and Other Arab. Although this data was not personally identifiable, its disclosure to a law enforcement agency was unethical.
The reason DHS gave for requesting these tabulations was to determine which languages signs should be in at international airports.10 Heavily redacted emails11 between a Census Bureau analyst and a DHS official show that the Bureau gave the documents before the intended purpose for the data was known and that this explanation was given after the tabulations had already been disclosed. The ex-post-facto reason given by DHS seems pretextual.
As a result of these revelations, resulting from EPIC’s FOIA litigation, the Census Bureau revised its policy on sharing statistical information about "sensitive populations" with law enforcement or intelligence agencies. Customs and Border Protection also changed its policy on requesting "information of a sensitive nature from the Census Bureau."12
II. Census Data Should Never Be Used for Enforcement Purposes
Using census data to help enforce laws is a corruption of the decennial census’s constitutional purpose. The Department of Justice (“DOJ”) requested the citizenship question on the census would allow the agency to better enforce Section 2 of the Voting Rights Act, which bars the dilution of voting power of a minority group through redistricting. DOJ wants census-block-level data for locations where they suspect Section 2 violations have occurred.
The decennial census’s statistical purpose is frustrated when other agencies ask it to collect data for other purposes. The DOJ’s responsibility to enforce the Voting Rights Act is vital to ensuring fair elections. In its request to the Bureau, the DOJ called the decennial census the “most appropriate vehicle” for collecting data on the citizen voting-age population.13 EPIC disagrees with this assertion. The decennial census was never intended to be a catch-all data collection to assist other federal agencies. In fact, the statutes concerning the privacy of census data are meant to expressly prohibit this.
If the Census Bureau gets into the business of collecting data because it will assist other federal agencies enforce laws, it will be difficult to stay true to its constitutional purpose of conducting impartial statistical analysis. And it will undermine the integrity, accuracy, and reliability of the census. As a former director of the Bureau succinctly put it thirteen years ago: “The Census Bureau cannot become a quasi-investigatory agency and still perform its basic responsibilities as a statistical agency.”14 The Bureau does not serve an investigatory function and the DOJ (or any other agency) should not expect it to.
10 EPIC FOIA, https://epic.org/privacy/census/foia/census_emails.pdf. 11 Id. 12 U.S. Customs and Border Protection, Policy for Requesting Information of a Sensitive Nature from the Census Bureau, Memorandum (Aug. 9, 2004), https://epic.org/privacy/census/foia/policy.pdf. 13 Re: Request to Reinstate Citizenship Question on 2020 Census Questionnaire (Dec. 12, 2017), https://www.documentcloud.org/documents/4340651-Text-of-Dec-2017-DOJ-letter-to-Census.html. 14 Counting the Vote: Should Only U.S. Citizens be Included in Apportioning Our Elected Representatives?, Hearing Before Subcomm. on Federalism and the Census of the H. Comm. on Gov’t Reform, 109th Cong. 77 (2005) (statement of former director of U.S. Census Bureau Kenneth Prewitt).

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IV. Insufficiency of Privacy Impact Assessment

The Privacy Impact Assessment (“PIA”) for the 2020 decennial census15 indicates that the Census Bureau has not undertaken an appropriate analysis of the privacy risks of the citizenship question. “Citizenship” is listed as “other general personal data” that will be collected by the census.16 But, where the Bureau is required to indicate the status of the information system, it selects: “This is an existing information system without changes that create new privacy risks.”17 There is no analysis of the new question.

The PIA does not satisfy the Department of Commerce’s own standards.18 A PIA must be updated “where a system change creates new privacy risks.” The Department of Commerce lists nine examples of new privacy risks, and the addition of the citizenship question and the stated purposes for doing so would create at least four of those risks.

The new question would alter the character of the data: “when new information in identifiable form added to a collection raises the risks to personal privacy (for example, the addition of health or financial information).”19 Citizenship data is new information and it is identifiable because it is collected alongside the other information of the person filling out the census form. Immigration status added to the collection of the other demographic data collected by the census undeniably raises the risk to personal privacy. If that privacy were to be violated, that information could be used against the respondent for deportation or other purposes. The PIA does not acknowledge the privacy risks raised by the new question and the Bureau should conduct a new PIA dealing specifically with the issues raised by the citizenship question.

EPIC looks forward to working with the Committee to ensure that the census data provides the maximum benefit to the American public while minimizing the privacy risks. We ask that this letter from EPIC be entered in the hearing record.

Sincerely,

/s/ Marc Rotenberg Marc Rotenberg EPIC President

/s/ Caitriona Fitzgerald Caitriona Fitzgerald EPIC Policy Director

/s/ Christine Bannan Christine Bannan EPIC Consumer Protection Counsel

15 U.S. Department of Commerce, U.S. Census Bureau, Privacy Impact Assessment for the CEN08 Decennial
Information Technology Division (July 28, 2018)
http://www.osec.doc.gov/opog/privacy/Census%20PIAs/CEN08_PIA_SAOP_Approved.pdf. 16 Id. at 3. 17 Id. at 2. 18 U.S. Department of Commerce, Office of Privacy and Open Government, Privacy Compliance
http://www.osec.doc.gov/opog/privacy/compliance.html. 19 Id. “Alteration in Character of Data” is the ninth example in the list of privacy risks.

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Exhibit 15

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September 26, 2003 M­03­22 MEMORANDUM FOR HEADS OF EXECUTIVE DEPARTMENTS AND AGENCIES

FROM: SUBJECT:

Joshua B. Bolten DirectoR
OMB Guidance for Implementing the Privacy Provisions of the E­ Government Act of 2002

The attached guidance provides information to agencies on implementing the privacy provisions of the E­ Government Act of 2002, which was signed by the President on December 17, 2002 and became effective on April 17, 2003.
The Administration is committed to protecting the privacy of the American people. This guidance document addresses privacy protections when Americans interact with their government. The guidance directs agencies to conduct reviews of how information about individuals is handled within their agency when they use information technology (IT) to collect new information, or when agencies develop or buy new IT systems to handle collections of personally identifiable information. Agencies are also directed to describe how the government handles information that individuals provide electronically, so that the American public has assurances that personal information is protected.
The privacy objective of the E­Government Act complements the National Strategy to Secure Cyberspace. As the National Strategy indicates, cyberspace security programs that strengthen protections for privacy and other civil liberties, together with strong privacy policies and practices in the federal agencies, will ensure that information is handled in a manner that maximizes both privacy and security.
Background
Section 208 of the E­Government Act of 2002 (Public Law 107­347, 44 U.S.C. Ch 36) requires that OMB issue guidance to agencies on implementing the privacy provisions of the E­Government Act (see Attachment A). The text of section 208 is provided as Attachment B to this Memorandum. Attachment C provides a general outline of regulatory requirements pursuant to the Children’s Online Privacy Protection Act (“COPPA”). Attachment D summarizes the modifications to existing guidance resulting from this Memorandum. A complete list of OMB privacy guidance currently in effect is available at OMB’s website.
As OMB has previously communicated to agencies, for purposes of their FY2005 IT budget requests, agencies should submit all required Privacy Impact Assessments no later than October 3, 2003.
For any questions about this guidance, contact Eva Kleederman, Policy Analyst, Information Policy and Technology Branch, Office of Management and Budget, phone (202) 395­3647, fax (202) 395­5167, e­mail Eva_Kleederman@omb.eop.gov.
Attachments
Attachment A Attachment B
_____ _ Attachment C Attachment D _..,_..,

Attachment A
E­Government Act Section 208 Implementation Guidance
I. General
A. Requirements. Agencies are required to: 1. conduct privacy impact assessments for electronic information systems and collections and, in general, make them publicly available (see Section II of this Guidance), 2. post privacy policies on agency websites used by the public (see Section III),

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3. translate privacy policies into a standardized machine­readable format (see Section IV), and 4. report annually to OMB on compliance with section 208 of the E­Government Act of 2002 (see
Section VII).
B. Application. This guidance applies to:
1. all executive branch departments and agencies (“agencies”) and their contractors that use information technology or that operate websites for purposes of interacting with the public;
2. relevant cross­agency initiatives, including those that further electronic government.
C. Modifications to Current Guidance. Where indicated, this Memorandum modifies the following three memoranda, which are replaced by this guidance (see summary of modifications at Attachment D):
1. Memorandum 99­05 (January 7, 1999), directing agencies to examine their procedures for ensuring the privacy of personal information in federal records and to designate a senior official to assume primary responsibility for privacy policy;
2. Memorandum 99­18 (June 2, 1999), concerning posting privacy policies on major entry points to government web sites as well as on any web page collecting substantial personal information from the public; and
3. Memorandum 00­13 (June 22, 2000), concerning (i) the use of tracking technologies such as persistent cookies and (ii) parental consent consistent with the Children’s Online Privacy Protection Act (“COPPA”).
II. Privacy Impact Assessment
A. Definitions.
1. Individual ­ means a citizen of the United States or an alien lawfully admitted for permanent residence.1
2. Information in identifiable form­ is information in an IT system or online collection: (i) that directly identifies an individual (e.g., name, address, social security number or other identifying number or code, telephone number, email address, etc.) or (ii) by which an agency intends to identify specific individuals in conjunction with other data elements, i.e., indirect identification. (These data elements may include a combination of gender, race, birth date, geographic indicator, and other descriptors).2
3. Information technology (IT) ­ means, as defined in the Clinger­Cohen Act3, any equipment, software or interconnected system or subsystem that is used in the automatic acquisition, storage, manipulation, management, movement, control, display, switching, interchange, transmission, or reception of data or information.
4. Major information system ­ embraces “large” and “sensitive” information systems and means, as defined in OMB Circular A­130 (Section 6.u.) and annually in OMB Circular A­11 (section 300­4 (2003)), a system or project that requires special management attention because of its: (i) importance to the agency mission, (ii) high development, operating and maintenance costs, (iii) high risk, (iv) high return, (v) significant role in the administration of an agency’s programs, finances, property or other resources.
5. National Security Systems ­ means, as defined in the Clinger­Cohen Act4, an information system operated by the federal government, the function, operation or use of which involves: (a) intelligence activities, (b) cryptologic activities related to national security, (c) command and control of military forces, (d) equipment that is an integral part of a weapon or weapons systems, or (e) systems critical to the direct fulfillment of military or intelligence missions, but does not include systems used for routine administrative and business applications, such as payroll, finance, logistics and personnel management.
6. Privacy Impact Assessment (PIA)­ is an analysis of how information is handled: (i) to ensure handling conforms to applicable legal, regulatory, and policy requirements regarding privacy, (ii) to determine the risks and effects of collecting, maintaining and disseminating information in identifiable form in an electronic information system, and (iii) to examine and evaluate protections and alternative processes for handling information to mitigate potential privacy risks.
7. Privacy policy in standardized machine­readable format­ means a statement about site privacy practices written in a standard computer language (not English text) that can be read automatically by a web browser.
B. When to conduct a PIA:5 1. The E­Government Act requires agencies to conduct a PIA before: a. developing or procuring IT systems or projects that collect, maintain or disseminate information in identifiable form from or about members of the public, or b. initiating, consistent with the Paperwork Reduction Act, a new electronic collection of information in identifiable form for 10 or more persons (excluding agencies, instrumentalities or employees of the federal government). 2. In general, PIAs are required to be performed and updated as necessary where a system change creates new privacy risks. For example:

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a. Conversions ­ when converting paper­based records to electronic systems; b. Anonymous to Non­Anonymous ­ when functions applied to an existing information collection
change anonymous information into information in identifiable form; c. Significant System Management Changes ­ when new uses of an existing IT system, including
application of new technologies, significantly change how information in identifiable form is managed in the system:
■ For example, when an agency employs new relational database technologies or web­ based processing to access multiple data stores; such additions could create a more open environment and avenues for exposure of data that previously did not exist.
d. Significant Merging ­ when agencies adopt or alter business processes so that government databases holding information in identifiable form are merged, centralized, matched with other databases or otherwise significantly manipulated: ■ For example, when databases are merged to create one central source of information; such a link may aggregate data in ways that create privacy concerns not previously at issue.
e. New Public Access ­ when user­authenticating technology (e.g., password, digital certificate, biometric) is newly applied to an electronic information system accessed by members of the public;
f. Commercial Sources ­ when agencies systematically incorporate into existing information systems databases of information in identifiable form purchased or obtained from commercial or public sources. (Merely querying such a source on an ad hoc basis using existing technology does not trigger the PIA requirement);
g. New Interagency Uses ­ when agencies work together on shared functions involving significant new uses or exchanges of information in identifiable form, such as the cross­cutting E­Government initiatives; in such cases, the lead agency should prepare the PIA; ■ For example the Department of Health and Human Services, the lead agency for the Administration’s Public Health Line of Business (LOB) Initiative, is spearheading work with several agencies to define requirements for integration of processes and accompanying information exchanges. HHS would thus prepare the PIA to ensure that all privacy issues are effectively managed throughout the development of this cross agency IT investment.
h. Internal Flow or Collection ­ when alteration of a business process results in significant new uses or disclosures of information or incorporation into the system of additional items of information in identifiable form: ■ For example, agencies that participate in E­Gov initiatives could see major changes in how they conduct business internally or collect information, as a result of new business processes or E­Gov requirements. In most cases the focus will be on integration of common processes and supporting data. Any business change that results in substantial new requirements for information in identifiable form could warrant examination of privacy issues.
i. Alteration in Character of Data ­ when new information in identifiable form added to a collection raises the risks to personal privacy (for example, the addition of health or financial information)
3. No PIA is required where information relates to internal government operations, has been previously assessed under an evaluation similar to a PIA, or where privacy issues are unchanged, as in the following circumstances: a. for government­run websites, IT systems or collections of information to the extent that they do not collect or maintain information in identifiable form about members of the general public (this includes government personnel and government contractors and consultants);6 b. for government­run public websites where the user is given the option of contacting the site operator for the limited purposes of providing feedback (e.g., questions or comments) or obtaining additional information; c. for national security systems defined at 40 U.S.C. 11103 as exempt from the definition of information technology (see section 202(i) of the E­Government Act); d. when all elements of a PIA are addressed in a matching agreement governed by the computer matching provisions of the Privacy Act (see 5 U.S.C. §§ 552a(8­10), (e)(12), (o), (p), (q), (r), (u)), which specifically provide privacy protection for matched information; e. when all elements of a PIA are addressed in an interagency agreement permitting the merging of data for strictly statistical purposes and where the resulting data are protected from improper disclosure and use under Title V of the E­Government Act of 2002; f. if agencies are developing IT systems or collecting non­identifiable information for a discrete purpose, not involving matching with or retrieval from other databases that generates information in identifiable form; g. for minor changes to a system or collection that do not create new privacy risks.
4. Update of PIAs: Agencies must update their PIAs to reflect changed information collection authorities, business processes or other factors affecting the collection and handling of information in identifiable form.
C. Conducting a PIA.

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1. Content. a. PIAs must analyze and describe: i. what information is to be collected (e.g., nature and source); ii. why the information is being collected (e.g., to determine eligibility); iii. intended use of the information (e.g., to verify existing data); iv. with whom the information will be shared (e.g., another agency for a specified programmatic purpose); v. what opportunities individuals have to decline to provide information (i.e., where providing information is voluntary) or to consent to particular uses of the information (other than required or authorized uses), and how individuals can grant consent; vi. how the information will be secured (e.g., administrative and technological controls7); and vii. whether a system of records is being created under the Privacy Act, 5 U.S.C. 552a. b. Analysis: PIAs must identify what choices the agency made regarding an IT system or collection of information as a result of performing the PIA.
2. Agencies should commence a PIA when they begin to develop a new or significantly modified IT system or information collection: a. Specificity. The depth and content of the PIA should be appropriate for the nature of the information to be collected and the size and complexity of the IT system. i. IT development stage. PIAs conducted at this stage: 1. should address privacy in the documentation related to systems development, including, as warranted and appropriate, statement of need, functional requirements analysis, alternatives analysis, feasibility analysis, benefits/cost analysis, and, especially, initial risk assessment; 2. should address the impact the system will have on an individual’s privacy, specifically identifying and evaluating potential threats relating to each of the elements identified in section II.C.1.a.(i)­(vii) above, to the extent these elements are known at the initial stages of development; 3. may need to be updated before deploying the system to consider elements not identified at the concept stage (e.g., retention or disposal of information), to reflect a new information collection, or to address choices made in designing the system or information collection as a result of the analysis. ii. Major information systems. PIAs conducted for these systems should reflect more extensive analyses of: 1. the consequences of collection and flow of information, 2. the alternatives to collection and handling as designed, 3. the appropriate measures to mitigate risks identified for each alternative and, 4. the rationale for the final design choice or business process. iii. Routine database systems. Agencies may use a standardized approach (e.g., checklist or template) for PIAs involving simple systems containing routine information and involving limited use and access. b. Information life cycle analysis/collaboration. Agencies must consider the information “life cycle” (i.e., collection, use, retention, processing, disclosure and destruction) in evaluating how information handling practices at each stage may affect individuals’ privacy. To be comprehensive and meaningful, privacy impact assessments require collaboration by program experts as well as experts in the areas of information technology, IT security, records management and privacy.
3. Review and publication. a. a. Agencies must ensure that: i. the PIA document and, if prepared, summary are approved by a “reviewing official” (the agency CIO or other agency head designee, who is other than the official procuring the system or the official who conducts the PIA); ii. for each covered IT system for which 2005 funding is requested, and consistent with previous guidance from OMB, the PIA is submitted to the Director of OMB no later than October 3, 2003 (submitted electronically to PIA@omb.eop.gov along with the IT investment’s unique identifier as described in OMB Circular A­11, instructions for the Exhibit 3008); and iii. the PIA document and, if prepared, summary, are made publicly available (consistent with executive branch policy on the release of information about systems for which funding is proposed). 1. Agencies may determine to not make the PIA document or summary publicly available to the extent that publication would raise security concerns, reveal classified (i.e., national security) information or sensitive information (e.g., potentially damaging to a national interest, law enforcement effort or competitive business interest) contained in an assessment9. Such information shall be protected and handled consistent with the Freedom of Information Act (FOIA). 2. Agencies should not include information in identifiable form in their privacy impact assessments, as there is no need for the PIA to include such

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information. Thus, agencies may not seek to avoid making the PIA publicly available on these grounds.
D. Relationship to requirements under the Paperwork Reduction Act (PRA)10. 1. Joint Information Collection Request (ICR) and PIA. Agencies undertaking new electronic information collections may conduct and submit the PIA to OMB, and make it publicly available, as part of the SF83 Supporting Statement (the request to OMB to approve a new agency information collection). 2. If Agencies submit a Joint ICR and PIA: a. All elements of the PIA must be addressed and identifiable within the structure of the Supporting Statement to the ICR, including: i. a description of the information to be collected in the response to Item 1 of the Supporting Statement11; ii. a description of how the information will be shared and for what purpose in Item 2 of the Supporting Statement12; iii. a statement detailing the impact the proposed collection will have on privacy in Item 2 of the Supporting Statement13; iv. a discussion in item 10 of the Supporting Statement of: 1. whether individuals are informed that providing the information is mandatory or voluntary 2. opportunities to consent, if any, to sharing and submission of information; 3. how the information will be secured; and 4. whether a system of records is being created under the Privacy Act)14. b. For additional information on the requirements of an ICR, please consult your agency’s organization responsible for PRA compliance. 3. Agencies need not conduct a new PIA for simple renewal requests for information collections under the PRA. As determined by reference to section II.B.2. above, agencies must separately consider the need for a PIA when amending an ICR to collect information that is significantly different in character from the original collection.
E. Relationship to requirements under the Privacy Act of 1974, 5 U.S. C. 552a.
1. Agencies may choose to conduct a PIA when developing the System of Records (SOR) notice required by subsection (e)(4) of the Privacy Act, in that the PIA and SOR overlap in content (e.g., the categories of records in the system, the uses of the records, the policies and practices for handling, etc.).
2. Agencies, in addition, may make the PIA publicly available in the Federal Register along with the Privacy Act SOR notice.
3. Agencies must separately consider the need for a PIA when issuing a change to a SOR notice (e.g., a change in the type or category of record added to the system may warrant a PIA).
III. Privacy Policies on Agency Websites
A. Privacy Policy Clarification. To promote clarity to the public, agencies are required to refer to their general web site notices explaining agency information handling practices as the “Privacy Policy.”
B. Effective Date. Agencies are expected to implement the following changes to their websites by December 15, 2003.
C. Exclusions: For purposes of web privacy policies, this guidance does not apply to: 1. information other than “government information” as defined in OMB Circular A­130; 2. agency intranet web sites that are accessible only by authorized government users (employees, contractors, consultants, fellows, grantees); 3. national security systems defined at 40 U.S.C. 11103 as exempt from the definition of information technology (see section 202(i) of the E­government Act).
D. Content of Privacy Policies. 1. Agency Privacy Policies must comply with guidance issued in OMB Memorandum 99­18 and must now also include the following two new content areas: a. Consent to collection and sharing15. Agencies must now ensure that privacy policies: i. inform visitors whenever providing requested information is voluntary; ii. inform visitors how to grant consent for use of voluntarily­provided information; and iii. inform visitors how to grant consent to use mandatorily­provided information for other than statutorily­mandated uses or authorized routine uses under the Privacy Act. b. Rights under the Privacy Act or other privacy laws16. Agencies must now also notify web­site visitors of their rights under the Privacy Act or other privacy­protecting laws that may primarily apply to specific agencies (such as the Health Insurance Portability and Accountability Act of 1996, the IRS Restructuring and Reform Act of 1998, or the Family Education Rights and Privacy Act): i. in the body of the web privacy policy;

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ii. via link to the applicable agency regulation (e.g., Privacy Act regulation and pertinent system notice); or
iii. via link to other official summary of statutory rights (such as the summary of Privacy Act rights in the FOIA/Privacy Act Reference Materials posted by the Federal Consumer Information Center at www.Firstgov.gov).
2. Agency Privacy Policies must continue to address the following, modified, requirements: a. Nature, purpose, use and sharing of information collected . Agencies should follow existing policies (issued in OMB Memorandum 99­18) concerning notice of the nature, purpose, use and sharing of information collected via the Internet, as modified below: i. Privacy Act information. When agencies collect information subject to the Privacy Act, agencies are directed to explain what portion of the information is maintained and retrieved by name or personal identifier in a Privacy Act system of records and provide a Privacy Act Statement either: 1. at the point of collection, or 2. via link to the agency’s general Privacy Policy18. ii. “Privacy Act Statements.” Privacy Act Statements must notify users of the authority for and purpose and use of the collection of information subject to the Privacy Act, whether providing the information is mandatory or voluntary, and the effects of not providing all or any part of the requested information. iii. Automatically Collected Information (site management data). Agency Privacy Policies must specify what information the agency collects automatically (i.e., user’s IP address, location, and time of visit) and identify the use for which it is collected (i.e., site management or security purposes). iv. Interaction with children: Agencies that provide content to children under 13 and that collect personally identifiable information from these visitors should incorporate the requirements of the Children’s Online Privacy Protection Act (“COPPA”) into their Privacy Policies (see Attachment C)19. v. Tracking and customization activities.Agencies are directed to adhere to the following modifications to OMB Memorandum 00­13 and the OMB follow­up guidance letter dated September 5, 2000: 1. Tracking technology prohibitions: a. agencies are prohibited from using persistent cookies or any other means (e.g., web beacons) to track visitors’ activity on the Internet except as provided in subsection (b) below; b. agency heads may approve, or may authorize the heads of sub­ agencies or senior official(s) reporting directly to the agency head to approve, the use of persistent tracking technology for a compelling need. When used, agency’s must post clear notice in the agency’s privacy policy of: ■ the nature of the information collected; ■ the purpose and use for the information; ■ whether and to whom the information will be disclosed; and ■ the privacy safeguards applied to the information collected. c. agencies must report the use of persistent tracking technologies as authorized for use by subsection b. above (see section VII)20. 2. The following technologies are not prohibited: a. Technology that is used to facilitate a visitor’s activity within a single session (e.g., a “session cookie”) and does not persist over time is not subject to the prohibition on the use of tracking technology. b. Customization technology (to customize a website at the visitor’s request) if approved by the agency head or designee for use (see v.1.b above) and where the following is posted in the Agency’s Privacy Policy: ■ the purpose of the tracking (i.e., customization of the site); ■ that accepting the customizing feature is voluntary; ■ that declining the feature still permits the individual to use the site; and ■ the privacy safeguards in place for handling the information collected. c. Agency use of password access to information that does not involve “persistent cookies” or similar technology. vi. Law enforcement and homeland security sharing: Consistent with current practice, Internet privacy policies may reflect that collected information may be shared and protected as necessary for authorized law enforcement, homeland security and national security activities. b. Security of the information21. Agencies should continue to comply with existing requirements for computer security in administering their websites22 and post the following information in their Privacy Policy:

Case 1:18-cv-02711-DLF Document 8-7 Filed 01/18/19 Page 8 of 42
i. in clear language, information about management, operational and technical controls ensuring the security and confidentiality of personally identifiable records (e.g., access controls, data storage procedures, periodic testing of safeguards, etc.), and
ii. in general terms, information about any additional safeguards used to identify and prevent unauthorized attempts to access or cause harm to information and systems. (The statement should be at a level to inform the public that their information is being protected while not compromising security.)
E. Placement of notices. Agencies should continue to follow the policy identified in OMB Memorandum 99­18 regarding the posting of privacy policies on their websites. Specifically, agencies must post (or link to) privacy policies at: 1. their principal web site; 2. any known, major entry points to their sites; 3. any web page that collects substantial information in identifiable form.
F. Clarity of notices. Consistent with OMB Memorandum 99­18, privacy policies must be: 1. clearly labeled and easily accessed; 2. written in plain language; and 3. made clear and easy to understand, whether by integrating all information and statements into a single posting, by layering a short “highlights” notice linked to full explanation, or by other means the agency determines is effective.
IV. Privacy Policies in Machine­Readable Formats
A. Actions. 1. Agencies must adopt machine readable technology that alerts users automatically about whether site privacy practices match their personal privacy preferences. Such technology enables users to make an informed choice about whether to conduct business with that site. 2. OMB encourages agencies to adopt other privacy protective tools that become available as the technology advances.
B. Reporting Requirement. Agencies must develop a timetable for translating their privacy policies into a standardized machine­readable format. The timetable must include achievable milestones that show the agency’s progress toward implementation over the next year. Agencies must include this timetable in their reports to OMB (see Section VII).
V. Privacy Policies Incorporated by this Guidance
In addition to the particular actions discussed above, this guidance reiterates general directives from previous OMB Memoranda regarding the privacy of personal information in federal records and collected on federal web sites. Specifically, existing policies continue to require that agencies:
A. assure that their uses of new information technologies sustain, and do not erode, the protections provided in all statutes relating to agency use, collection, and disclosure of personal information;
B. assure that personal information contained in Privacy Act systems of records be handled in full compliance with fair information practices as set out in the Privacy Act of 1974;
C. evaluate legislative proposals involving collection, use and disclosure of personal information by the federal government for consistency with the Privacy Act of 1974;
D. evaluate legislative proposals involving the collection, use and disclosure of personal information by any entity, public or private, for consistency with the Privacy Principles;
E. ensure full adherence with stated privacy policies.
VI. Agency Privacy Activities/Designation of Responsible Official Because of the capability of information technology to capture and disseminate information in an instant, all federal employees and contractors must remain mindful of privacy and their obligation to protect information in identifiable form. In addition, implementing the privacy provisions of the E­Government Act requires the cooperation and coordination of privacy, security, FOIA/Privacy Act and project officers located in disparate organizations within agencies. Clear leadership and authority are essential.
Accordingly, this guidance builds on policy introduced in Memorandum 99­05 in the following ways:
A. Agencies must: 1. inform and educate employees and contractors of their responsibility for protecting information in identifiable form; 2. identify those individuals in the agency (e.g., information technology personnel, Privacy Act Officers) that have day­to­day responsibility for implementing section 208 of the E­Government Act, the Privacy Act, or other privacy laws and policies. 3. designate an appropriate senior official or officials (e.g., CIO, Assistant Secretary) to serve as the agency’s principal contact(s) for information technology/web matters and for privacy policies. The designated official(s) shall coordinate implementation of OMB web and privacy policy and guidance. 4. designate an appropriate official (or officials, as appropriate) to serve as the “reviewing official(s)” for agency PIAs.

Case 1:18-cv-02711-DLF Document 8-7 Filed 01/18/19 Page 9 of 42
B. OMB leads a committee of key officials involved in privacy that reviewed and helped shape this guidance and that will review and help shape any follow­on privacy and web­privacy­related guidance. In addition, as part of overseeing agencies’ implementation of section 208, OMB will rely on the CIO Council to collect information on agencies’ initial experience in preparing PIAs, to share experiences, ideas, and promising practices as well as identify any needed revisions to OMB’s guidance on PIAs.
VII. Reporting Requirements Agencies are required to submit an annual report on compliance with this guidance to OMB as part of their annual E­ Government Act status report. The first reports are due to OMB by December 15, 2003. All agencies that use information technology systems and conduct electronic information collection activities must complete a report on compliance with this guidance, whether or not they submit budgets to OMB.
Reports must address the following four elements:
A. Information technology systems or information collections for which PIAs were conducted. Include the mechanism by which the PIA was made publicly available (website, Federal Register, other), whether the PIA was made publicly available in full, summary form or not at all (if in summary form or not at all, explain), and, if made available in conjunction with an ICR or SOR, the publication date.
B. Persistent tracking technology uses. If persistent tracking technology is authorized, include the need that compels use of the technology, the safeguards instituted to protect the information collected, the agency official approving use of the tracking technology, and the actual privacy policy notification of such use.
C. Agency achievement of goals for machine readability: Include goals for and progress toward achieving compatibility of privacy policies with machine­readable privacy protection technology.
D. Contact information. Include the individual(s) (name and title) appointed by the head of the Executive Department or agency to serve as the agency’s principal contact(s) for information technology/web matters and the individual (name and title) primarily responsible for privacy policies.
.........................................................................................................................................................................................................................................
Attachment B
E­Government Act of 2002
Pub. L. No. 107­347, Dec. 17, 2002
SEC. 208. PRIVACY PROVISIONS.
A. PURPOSE. — The purpose of this section is to ensure sufficient protections for the privacy of personal information as agencies implement citizen­centered electronic Government.
B. PRIVACY IMPACT ASSESSMENTS.—
1. RESPONSIBILITIES OF AGENCIES.— a. IN GENERAL.—An agency shall take actions described under subparagraph (b) before— i. developing or procuring information technology that collects, maintains, or disseminates information that is in an identifiable form; or ii. initiating a new collection of information that— 1. will be collected, maintained, or disseminated using information technology; and 2. includes any information in an identifiable form permitting the physical or online contacting of a specific individual, if identical questions have been posed to, or identical reporting requirements imposed on, 10 or more persons, other than agencies, instrumentalities, or employees of the Federal Government. b. AGENCY ACTIVITIES. —To the extent required under subparagraph (a), each agency shall— i. conduct a privacy impact assessment; ii. ensure the review of the privacy impact assessment by the Chief Information Officer, or equivalent official, as determined by the head of the agency; and iii. if practicable, after completion of the review under clause (ii), make the privacy impact assessment publicly available through the website of the agency, publication in the Federal Register, or other means. c. SENSITIVE INFORMATION. —Subparagraph (b)(iii) may be modified or waived for security reasons, or to protect classified, sensitive, or private information contained in an assessment. d. COPY TO DIRECTOR. —Agencies shall provide the Director with a copy of the privacy impact assessment for each system for which funding is requested.
2. CONTENTS OF A PRIVACY IMPACT ASSESSMENT. — a. IN GENERAL. —The Director shall issue guidance to agencies specifying the required contents of a privacy impact assessment. b. GUIDANCE. — The guidance shall— i. ensure that a privacy impact assessment is commensurate with the size of the information system being assessed, the sensitivity of information that is in an identifiable form in that system, and the risk of harm from unauthorized release of that information; and ii. require that a privacy impact assessment address— 1. what information is to be collected; 2. why the information is being collected; 3. the intended use of the agency of the information; 4. with whom the information will be shared;

Case 1:18-cv-02711-DLF Document 8-7 Filed 01/18/19 Page 10 of 42
5. what notice or opportunities for consent would be provided to individuals regarding what information is collected and how that information is shared;
6. how the information will be secured; and 7. whether a system of records is being created under section 552a of title 5, United
States Code, (commonly referred to as the `Privacy Act'). 3. RESPONSIBILITIES OF THE DIRECTOR.—The Director shall—
a. develop policies and guidelines for agencies on the conduct of privacy impact assessments; b. oversee the implementation of the privacy impact assessment process throughout the Government;
and c. require agencies to conduct privacy impact assessments of existing information systems or ongoing
collections of information that is in an identifiable form as the Director determines appropriate.
C. PRIVACY PROTECTIONS ON AGENCY WEBSITES. —
1. PRIVACY POLICIES ON WEBSITES. — a. GUIDELINES FOR NOTICES. —The Director shall develop guidance for privacy notices on agency websites used by the public. b. CONTENTS. —The guidance shall require that a privacy notice address, consistent with section 552a of title 5, United States Code— i. what information is to be collected; ii. why the information is being collected; iii. the intended use of the agency of the information; iv. with whom the information will be shared; v. what notice or opportunities for consent would be provided to individuals regarding what information is collected and how that information is shared; vi. how the information will be secured; and vii. the rights of the individual under section 552a of title 5, United States Code (commonly referred to as the `Privacy Act'), and other laws relevant to the protection of the privacy of an individual.
2. PRIVACY POLICIES IN MACHINE­READABLE FORMATS. — The Director shall issue guidance requiring agencies to translate privacy policies into a standardized machine­readable format.
D. DEFINITION. —In this section, the term `identifiable form' means any representation of information that permits the identity of an individual to whom the information applies to be reasonably inferred by either direct or indirect means.
Attachment C
This attachment is a summary by the Federal Trade Commission of its guidance regarding federal agency compliance with the Children’s Online Privacy Protection Act (COPPA).
The hallmarks of COPPA for purposes of federal online activity are (i) notice of information collection practices (ii) verifiable parental consent and (iii) access, as generally outlined below:
• Notice of Information Collection Practices
Agencies whose Internet sites offer a separate children’s area and collect personal information from them must post a clear and prominent link to its Internet privacy policy on the home page of the children’s area and at each area where it collects personal information from children. The privacy policy should provide the name and contact information of the agency representative required to respond to parental inquiries about the site. Importantly, the privacy policy should inform parents about the kinds of information collected from children, how the information is collected (directly, or through cookies), how the information is used, and procedures for reviewing/deleting the information obtained from children.
In addition, the privacy policy should inform parents that only the minimum information necessary for participation in the activity is collected from the child.In addition to providing notice by posting a privacy policy, notice of an Internet site’s information collection practices must be sent directly to a parent when a site is requesting parental consent to collection personal information from a child. This direct notice should tell parents that the site would like to collect personal information from their child, that their consent is required for this collection, and how consent can be provided. The notice should also contain the information set forth in the site’s privacy policy, or provide an explanatory link to the privacy policy.
• Verifiable Parental Consent
With limited exceptions, agencies must obtain parental consent before collecting any personal information from children under the age of 13. If agencies are using the personal information for their internal use only, they may obtain parental consent through an e­mail message from the parent, as long as they take additional steps to increase the likelihood that the parent has, in fact, provided the consent. For example, agencies might seek confirmation from a parent in a delayed confirmatory e­mail, or confirm the parent’s consent by letter or phone call23.

Case 1:18-cv-02711-DLF Document 8-7 Filed 01/18/19 Page 11 of 42
However, if agencies disclose the personal information to third parties or the public (through chat rooms or message boards), only the most reliable methods of obtaining consent must be used. These methods include: (i) obtaining a signed form from the parent via postal mail or facsimile, (ii) accepting and verifying a credit card number in connection with a transaction, (iii) taking calls from parents through a toll­free telephone number staffed by trained personnel, or (iv) email accompanied by digital signature.
Although COPPA anticipates that private sector Internet operators may share collected information with third parties (for marketing or other commercial purposes) and with the public (through chat rooms or message boards), as a general principle, federal agencies collect information from children only for purposes of the immediate online activity or other, disclosed, internal agency use. (Internal agency use of collected information would include release to others who use it solely to provide support for the internal operations of the site or service, including technical support and order fulfillment.) By analogy to COPPA and consistent with the Privacy Act, agencies may not use information collected from children in any manner not initially disclosed and for which explicit parental consent has not been obtained. Agencies’ Internet privacy policies should reflect these disclosure and consent principles.
COPPA’s implementing regulations include several exceptions to the requirement to obtain advance parental consent where the Internet operator (here, the agency) collects a child’s email address for the following purposes: (i) to provide notice and seek consent, (ii) to respond to a one­time request from a child before deleting it, (iii) to respond more than once to a specific request, e.g., for a subscription to a newsletter, as long as the parent is notified of, and has the opportunity to terminate a continuing series of communications, (iv) to protect the safety of a child, so long as the parent is notified and given the opportunity to prevent further use of the information, and (v) to protect the security or liability of the site or to respond to law enforcement if necessary.
Agencies should send a new notice and request for consent to parents any time the agency makes material changes in the collection or use of information to which the parent had previously agreed. Agencies should also make clear to parents that they may revoke their consent, refuse to allow further use or collection of the child’s personal information and direct the agency to delete the information at any time.
• Access
At a parent’s request, agencies must disclose the general kinds of personal information they collect online from children as well as the specific information collected from a child. Agencies must use reasonable procedures to ensure they are dealing with the child’s parent before they provide access to the child’s specific information, e.g., obtaining signed hard copy of identification, accepting and verifying a credit card number, taking calls from parents on a toll­free line staffed by trained personnel, email accompanied by digital signature, or email accompanied by a PIN or password obtained through one of the verification methods above.
In adapting the provisions of COPPA to their Internet operations, agencies should consult the FTC’s web site at http://www.ftc.gov/privacy/privacyinitiatives/childrens.html or call the COPPA compliance telephone line at (202) 326­3140.
Attachment D
Summary of Modifications to Prior Guidance
This Memorandum modifies prior guidance in the following ways:
* Internet Privacy Policies (Memorandum 99­18):
• must identify when tracking technology is used to personalize the interaction, and explain the purpose of the
feature and the visitor’s option to decline it.
• must clearly explain when information is maintained and retrieved by personal identifier in a Privacy Act
system of records; must provide (or link to) a Privacy Act statement (which may be subsumed within agency’s Internet privacy policy) where Privacy Act information is solicited.
• should clearly explain an individual’s rights under the Privacy Act if solicited information is to be maintained in
a Privacy Act system of records; information about rights under the Privacy Act may be provided in the body of the web privacy policy or via link to the agency’s published systems notice and Privacy Act regulation or other summary of rights under the Privacy Act (notice and explanation of rights under other privacy laws should be handled in the same manner).
• when a Privacy Act Statement is not required, must link to the agency’s Internet privacy policy explaining the
purpose of the collection and use of the information (point­of­collection notice at agency option).

Case 1:18-cv-02711-DLF Document 8-7 Filed 01/18/19 Page 12 of 42 • must clearly explain where the user may consent to the collection or sharing of information and must notify
users of any available mechanism to grant consent.
• agencies must undertake to make their Internet privacy policies “readable” by privacy protection technology
and report to OMB their progress in that effort.
• must adhere to the regulatory requirements of the Children’s Online Privacy Protection Act (COPPA) when
collecting information electronically from children under age 13.
*Tracking Technology (Memorandum 00­13):
• prohibition against tracking visitors’ Internet use extended to include tracking by any means (previous
guidance addressed only “persistent cookies”).? authority to waive the prohibition on tracking in appropriate circumstances may be retained by the head of an agency, or may be delegated to (i) senior official(s) reporting directly to the agency head, or to (ii) the heads of sub­agencies.? agencies must report the use of tracking technology to OMB, identifying the circumstances, safeguards and approving official.
• agencies using customizing technology must explain the use, voluntary nature of and the safeguards
applicable to the customizing device in the Internet privacy policy.
• agency heads or their designees may approve the use of persistent tracking technology to customize Internet
interactions with the government.
* Privacy responsibilities (Memorandum 99­05)
• agencies to identify individuals with day­to­day responsibility for implementing the privacy provisions of the E­
Government Act, the Privacy Act and any other applicable statutory privacy regime.
• agencies to report to OMB the identities of senior official(s) primarily responsible for implementing and
coordinating information technology/web policies and privacy policies.
1. Agencies may, consistent with individual practice, choose to extend the protections of the Privacy Act and E­ Government Act to businesses, sole proprietors, aliens, etc.
2. Information in identifiable form is defined in section 208(d) of the Act as “any representation of information that permits the identity of an individual to whom the information applies to be reasonably inferred by either direct or indirect means.” Information “permitting the physical or online contacting of a specific individual” (see section 208(b)(1)(A)(ii)(II)) is the same as “information in identifiable form.”
3. Clinger­Cohen Act of 1996, 40 U.S.C. 11101(6). 4. Clinger­Cohen Act of 1996, 40 U.S.C. 11103. 5. In addition to these statutorily prescribed activities, the E­Government Act authorizes the Director of OMB to
require agencies to conduct PIAs of existing electronic information systems or ongoing collections of information in identifiable form as the Director determines appropriate. (see section 208(b)(3)(C)). 6. Information in identifiable form about government personnel generally is protected by the Privacy Act of 1974. Nevertheless, OMB encourages agencies to conduct PIAs for these systems as appropriate. 7. Consistent with agency requirements under the Federal Information Security Management Act, agencies should: (i) affirm that the agency is following IT security requirements and procedures required by federal law and policy to ensure that information is appropriately secured, (ii) acknowledge that the agency has conducted a risk assessment, identified appropriate security controls to protect against that risk, and implemented those controls, (iii) describe the monitoring/testing/evaluating on a regular basis to ensure that controls continue to work properly, safeguarding the information, and (iv) provide a point of contact for any additional questions from users. Given the potential sensitivity of security­related information, agencies should ensure that the IT security official responsible for the security of the system and its information reviews the language before it is posted. 8. PIAs that comply with the statutory requirements and previous versions of this Memorandum are acceptable for agencies’ FY 2005 budget submissions. 9. Section 208(b)(1)(C). 10. See 44 USC Chapter 35 and implementing regulations, 5 CFR Part 1320.8. 11. Item 1 of the Supporting Statement reads: “Explain the circumstances that make the collection of information necessary. Identify any legal or administrative requirements that necessitate the collection. Attach a copy of the appropriate section of each statute and regulation mandating or authorizing the collection of information.” 12. Item 2 of the Supporting Statement reads: “Indicate how, by whom, and for what purpose the information is to be used. Except for a new collection, indicate the actual use the agency has made of the information received from the current collection.” 13. Item 2 of the Supporting Statement reads: “Indicate how, by whom, and for what purpose the information is to be used. Except for a new collection, indicate the actual use the agency has made of the information received from the current collection.” 14. Item 10 of the Supporting Statement reads: “Describe any assurance of confidentiality provided to respondents and the basis for the assurance in statute, regulation, or agency policy.” 15. Section 208(c)(1)(B)(v). 16. Section 208(c)(1)(B)(vii).

Case 1:18-cv-02711-DLF Document 8-7 Filed 01/18/19 Page 13 of 42
17. Section 208(c)(1)(B)(i­iv). 18. When multiple Privacy Act Statements are incorporated in a web privacy policy, a point­of­collection link must
connect to the Privacy Act Statement pertinent to the particular collection. 19. Attachment C contains a general outline of COPPA’s regulatory requirements. Agencies should consult the
Federal Trade Commission’s COPPA compliance telephone line at (202)­326­3140 or website for additional information at: http://www.ftc.gov/privacy/privacyinitiatives/childrens.html. 20. Consistent with current practice, the agency head or designee may limit, as appropriate, notice and reporting of tracking activities that the agency has properly approved and which are used for authorized law enforcement, national security and/or homeland security purposes. 21. Section 208(c)(1)(B)(vi). 22. Federal Information Security Management Act of 2002 (Title III of P.L. 107­347), OMB’s related security guidance and policies (Appendix III to OMB Circular A­130, “Security of Federal Automated Information Resources”) and standards and guidelines development by the National Institute of Standards and Technologies. 23. This standard was set to expire in April 2002, at which time the most verifiable methods of obtaining consent would have been required; however, in a Notice of Proposed Rulemaking, published in the Federal Register on October 31, 2001, the FTC has proposed that this standard be extended until April 2004. 66 Fed. Reg. 54963.

Case 1:18-cv-02711-DLF Document 8-7 Filed 01/18/19 Page 14 of 42
Exhibit 16

vt:nsus l'~ted.States·
2010

U.S. DEPARTMENT OF COMMERCE

This is the official form for all the people at this address.

Economics and Statistics Administration U.S. CENSUS BUREAU

It is quick and easy, and your answers are protected by law.

Use a blue or black pen.
Start here

5. Please provide information for each person living here. Start with a
person living here who owns or rents this house, apartment, or mobile home. If the owner or renter lives somewhere else, start with any adult living here. This will be Person 1.
What is Person 1’s name? Print name below.

The Census must count every person living in the United States on April 1, 2010.

Last Name

Before you answer Question 1, count the people living in this house, apartment, or mobile home using our guidelines.

First Name

□ MI

• Count all people, including babies, who live and sleep here

6. What is Person 1’s sex? Mark I J K ONE box.

most of the time.

□ Male □ Female

The Census Bureau also conducts counts in institutions and other places, so:
Y • Do not count anyone living away either at college or in the Armed Forces.
D PD I._______. • Do not count anyone in a nursing home, jail, prison, detention facility, etc., on April 1, 2010.
O • Leave these people off your form, even if they will return to live here after they leave college, the nursing home, the C military, jail, etc. Otherwise, they may be counted twice.
The Census must also include people without a permanent
L place to stay, so: A • If someone who has no permanent place to stay is staying
here on April 1, 2010, count that person. Otherwise, he or
N she may be missed in the census.
1. How many people were living or staying in this house,
IO apartment, or mobile home on April 1, 2010?
[I] I Number of people =
T 2. Were there any additional people staying here A April 1, 2010 that you did not include in Question 1?
Mark I J K all that apply.
M □ Children, such as newborn babies or foster children
I □ Relatives, such as adult children, cousins, or in-laws
R □ Nonrelatives, such as roommates or live-in baby sitters
□ People staying here temporarily
O □ No additional people F 3. Is this house, apartment, or mobile home —
Mark I J K ONE box.
IN □ Owned by you or someone in this household with a mortgage or loan? Include home equity loans.
I □ Owned by you or someone in this household free and

7. What is Person 1’s age and what is Person 1’s date of birth?

Please report babies as age 0 when the child is less than 1 year old.

Print numbers in boxes.

Age on April 1, 2010

Month Day

Year of birth

➜ NOTE: Please answer BOTH Question 8 about Hispanic origin and
Question 9 about race. For this census, Hispanic origins are not races.
8. Is Person 1 of Hispanic, Latino, or Spanish origin?
□ No, not of Hispanic, Latino, or Spanish origin □ Yes, Mexican, Mexican Am., Chicano □ Yes, Puerto Rican □ Yes, Cuban □ Yes, another Hispanic, Latino, or Spanish origin — Print origin, for example,
Argentinean, Colombian, Dominican, Nicaraguan, Salvadoran, Spaniard, and so on. C

I
9. What is Person 1’s race? Mark I J K one or more boxes.
□ White □ Black, African Am., or Negro □ American Indian or Alaska Native — Print name of enrolled or principal tribe. C

I

I I I

□ Asian Indian □ Japanese

□ Chinese

□ Korean

□ Filipino

□ Vietnamese

□ Other Asian — Print race, for
example, Hmong, Laotian, Thai,

Pakistani, Cambodian, and so on. C

I I
□ Native Hawaiian □ Guamanian or Chamorro □ Samoan □ Other Pacific Islander — Print
race, for example, Fijian, Tongan, and so on. C

I I I I I I I I I I I I I I I I I I

clear (without a mortgage or loan)?
□ Rented? □ Occupied without payment of rent? 4. What is your telephone number? We may call if we
don’t understand an answer.

□ Some other race — Print race. C
II I I I I I I I I I I I I I I I I I
10. Does Person 1 sometimes live or stay somewhere else?

Area Code + Number

□ No □ Yes — Mark I J K all that apply.

–

–

□ In college housing □ In the military

□ For child custody □ In jail or prison

OMB No. 0607-0919-C: Approval Expires 12/31/2011.
Form D-61 (1-15-2009)

□ At a seasonal

□ In a nursing home

or second residence □ For another reason

➜ If more people were counted in Question 1, continue with Person 2.

USCENSUSBUREAU

1. Print name of Person 2
I Last Name

I I I I I I I I I

1. Print name of Person 3
Last Name

I □ First Name I I I I I I I I I I I I MI
2. How is this person related to Person 1? Mark I J K ONE box.

□ First Name

MI

2. How is this person related to Person 1? Mark I J K ONE box.

□ Husband or wife

□ Parent-in-law

□ Biological son or daughter □ Son-in-law or daughter-in-law

□ Adopted son or daughter □ Stepson or stepdaughter

□ Other relative □ Roomer or boarder

□ Brother or sister

□ Housemate or roommate

□ Father or mother

□ Unmarried partner

□ Grandchild

□ Other nonrelative

3. What is this person’s sex? Mark I J K ONE box.

□ Husband or wife

□ Parent-in-law

□ Biological son or daughter □ Son-in-law or daughter-in-law

□ Adopted son or daughter □ Other relative

□ Stepson or stepdaughter □ Roomer or boarder

□ Brother or sister

□ Housemate or roommate

□ Father or mother

□ Unmarried partner

□ Grandchild

□ Other nonrelative

3. What is this person’s sex? Mark I J K ONE box.

□ Male □ Female 4. What is this person’s age and what is this person’s date of birth?

Y Please report babies as age 0 when the child is less than 1 year old.

Print numbers in boxes.

P Age on April 1, 2010

Month Day

Year of birth

□ Male □ Female 4. What is this person’s age and what is this person’s date of birth?

Please report babies as age 0 when the child is less than 1 year old.

Print numbers in boxes.

Age on April 1, 2010

Month Day

Year of birth

□□ 1 111 DO D ...__I____ ➜ NOTE: Please answer BOTH Question 5 about Hispanic origin and C Question 6 about race. For this census, Hispanic origins are not races.
5. Is this person of Hispanic, Latino, or Spanish origin?
L □ No, not of Hispanic, Latino, or Spanish origin
□ Yes, Mexican, Mexican Am., Chicano
A □ Yes, Puerto Rican
□ Yes, Cuban
N □ Yes, another Hispanic, Latino, or Spanish origin — Print origin, for example, Argentinean, Colombian, Dominican, Nicaraguan, Salvadoran, Spaniard, and so on. C

➜ NOTE: Please answer BOTH Question 5 about Hispanic origin and
Question 6 about race. For this census, Hispanic origins are not races.
5. Is this person of Hispanic, Latino, or Spanish origin? □ No, not of Hispanic, Latino, or Spanish origin □ Yes, Mexican, Mexican Am., Chicano □ Yes, Puerto Rican □ Yes, Cuban □ Yes, another Hispanic, Latino, or Spanish origin — Print origin, for example,
Argentinean, Colombian, Dominican, Nicaraguan, Salvadoran, Spaniard, and so on. C

TIO 6. What is this person’s race? Mark I J K one or more boxes. A □ White
□ Black, African Am., or Negro
M □ American Indian or Alaska Native — Print name of enrolled or principal tribe. C

6. What is this person’s race? Mark I J K one or more boxes. □ White □ Black, African Am., or Negro □ American Indian or Alaska Native — Print name of enrolled or principal tribe. C

R I □ Asian Indian □ Japanese

O □ Chinese

□ Korean

F □ Filipino

□ Vietnamese

□ Other Asian — Print race, for
IN example, Hmong, Laotian, Thai,

Pakistani, Cambodian, and so on. C

□ Native Hawaiian □ Guamanian or Chamorro □ Samoan □ Other Pacific Islander — Print
race, for example, Fijian, Tongan, and so on. C

I I I I I I I I I I

□ Asian Indian □ Japanese

□ Chinese

□ Korean

□ Filipino

□ Vietnamese

□ Other Asian — Print race, for
example, Hmong, Laotian, Thai,

Pakistani, Cambodian, and so on. C

I I I I I I I
□ Native Hawaiian □ Guamanian or Chamorro □ Samoan □ Other Pacific Islander — Print
race, for example, Fijian, Tongan, and so on. C

□ Some other race — Print race. C

I I I I I I I I I I I I I I I I I I I I
7. Does this person sometimes live or stay somewhere else?

□ No □ Yes — Mark I J K all that apply.

□ In college housing □ In the military □ At a seasonal
or second residence

□ For child custody □ In jail or prison □ In a nursing home □ For another reason

➜ If more people were counted in Question 1 on the front page, continue with Person 3.

□ Some other race — Print race. C

7. Does this person sometimes live or stay somewhere else?

□ No □ Yes — Mark I J K all that apply.

□ In college housing □ In the military □ At a seasonal
or second residence

□ For child custody □ In jail or prison □ In a nursing home □ For another reason

➜ If more people were counted in Question 1 on the front page, continue with Person 4.

1. Print name of Person 4
Last Name

1. Print name of Person 5

Last Name

I I

□ First Name

MI

2. How is this person related to Person 1? Mark I J K ONE box.

□ First Name

MI

2. How is this person related to Person 1? Mark I J K ONE box.

□ Husband or wife □ Biological son or daughter □ Adopted son or daughter

□ Parent-in-law □ Son-in-law or daughter-in-law □ Other relative

□ Stepson or stepdaughter □ Roomer or boarder

□ Brother or sister

□ Housemate or roommate

□ Father or mother

□ Unmarried partner

□ Grandchild

□ Other nonrelative

3. What is this person’s sex? Mark I J K ONE box.

□ Husband or wife □ Biological son or daughter □ Adopted son or daughter

□ Parent-in-law □ Son-in-law or daughter-in-law □ Other relative

□ Stepson or stepdaughter □ Roomer or boarder

□ Brother or sister

□ Housemate or roommate

□ Father or mother

□ Unmarried partner

□ Grandchild

□ Other nonrelative

3. What is this person’s sex? Mark I J K ONE box.

□ Male □ Female 4. What is this person’s age and what is this person’s date of birth?

Y Please report babies as age 0 when the child is less than 1 year old.

Print numbers in boxes.

P Age on April 1, 2010

Month Day

Year of birth

□ Male □ Female 4. What is this person’s age and what is this person’s date of birth?

Please report babies as age 0 when the child is less than 1 year old.

Print numbers in boxes.

Age on April 1, 2010

Month Day

Year of birth

D ITJ ...__I____. DO D ...__I____. ➜ NOTE: Please answer BOTH Question 5 about Hispanic origin and C Question 6 about race. For this census, Hispanic origins are not races.
5. Is this person of Hispanic, Latino, or Spanish origin?
L □ No, not of Hispanic, Latino, or Spanish origin
□ Yes, Mexican, Mexican Am., Chicano
A □ Yes, Puerto Rican
□ Yes, Cuban
N □ Yes, another Hispanic, Latino, or Spanish origin — Print origin, for example, Argentinean, Colombian, Dominican, Nicaraguan, Salvadoran, Spaniard, and so on. C

➜ NOTE: Please answer BOTH Question 5 about Hispanic origin and
Question 6 about race. For this census, Hispanic origins are not races.
5. Is this person of Hispanic, Latino, or Spanish origin? □ No, not of Hispanic, Latino, or Spanish origin □ Yes, Mexican, Mexican Am., Chicano □ Yes, Puerto Rican □ Yes, Cuban □ Yes, another Hispanic, Latino, or Spanish origin — Print origin, for example,
Argentinean, Colombian, Dominican, Nicaraguan, Salvadoran, Spaniard, and so on. C

I I I I I I I I I I I I I I I I I I I TIO 6. What is this person’s race? Mark I J K one or more boxes. A □ White
□ Black, African Am., or Negro
M □ American Indian or Alaska Native — Print name of enrolled or principal tribe. C

6. What is this person’s race? Mark I J K one or more boxes. □ White □ Black, African Am., or Negro □ American Indian or Alaska Native — Print name of enrolled or principal tribe. C

I I I I I I I R □ Asian Indian O □ Chinese F □ Filipino

□ Japanese □ Korean □ Vietnamese

□ Other Asian — Print race, for
IN example, Hmong, Laotian, Thai,

Pakistani, Cambodian, and so on. C

□ Native Hawaiian □ Guamanian or Chamorro □ Samoan □ Other Pacific Islander — Print
race, for example, Fijian, Tongan, and so on. C

□ Asian Indian □ Japanese

□ Chinese □ Filipino

□ Korean □ Vietnamese

□ Other Asian — Print race, for
example, Hmong, Laotian, Thai,

Pakistani, Cambodian, and so on. C

□ Native Hawaiian □ Guamanian or Chamorro □ Samoan □ Other Pacific Islander — Print
race, for example, Fijian, Tongan, and so on. C

IIIIIIIIIIIII IIIII

□ Some other race — Print race. C

□ Some other race — Print race. C

I I I I I I I I I I I I I I I I I I I I
7. Does this person sometimes live or stay somewhere else?

□ No □ Yes — Mark I J K all that apply.

□ In college housing □ In the military □ At a seasonal
or second residence

□ For child custody □ In jail or prison □ In a nursing home □ For another reason

➜ If more people were counted in Question 1 on the front page, continue with Person 5.

II I I I I I I I I I I I I I I

I I I

7. Does this person sometimes live or stay somewhere else?

□ No □ Yes — Mark I J K all that apply.

□ In college housing □ In the military □ At a seasonal
or second residence

□ For child custody □ In jail or prison □ In a nursing home □ For another reason

➜ If more people were counted in Question 1 on the front page, continue with Person 6.

1. Print name of Person 6
Last Name

I I I I I I I I I

First Name

111111

11111

I MI □

2. How is this person related to Person 1? Mark I J K ONE box.

□ Husband or wife

□ Parent-in-law

□ Biological son or daughter □ Son-in-law or daughter-in-law

□ Adopted son or daughter □ Other relative

□ Stepson or stepdaughter □ Roomer or boarder

□ Brother or sister

□ Housemate or roommate

□ Father or mother

□ Unmarried partner

□ Grandchild

□ Other nonrelative

3. What is this person’s sex? Mark I J K ONE box.

□ Male □ Female 4. What is this person’s age and what is this person’s date of birth?

Please report babies as age 0 when the child is less than 1 year old. Print numbers in boxes.

Age on April 1, 2010

Month Day

Year of birth

D D I.._______,

➜ NOTE: Please answer BOTH Question 5 about Hispanic origin and

Question 6 about race. For this census, Hispanic origins are not races.
5. Is this person of Hispanic, Latino, or Spanish origin?
L □ No, not of Hispanic, Latino, or Spanish origin
□ Yes, Mexican, Mexican Am., Chicano
A □ Yes, Puerto Rican
□ Yes, Cuban
N □ Yes, another Hispanic, Latino, or Spanish origin — Print origin, for example, Argentinean, Colombian, Dominican, Nicaraguan, Salvadoran, Spaniard, and so on. C

TIO 6. What is this person’s race? Mark I J K one or more boxes. A □ White
□ Black, African Am., or Negro
M □ American Indian or Alaska Native — Print name of enrolled or principal tribe. C

R □ Asian Indian O □ Chinese F □ Filipino

□ Japanese □ Korean □ Vietnamese

□ Other Asian — Print race, for
IN example, Hmong, Laotian, Thai,

Pakistani, Cambodian, and so on. C

□ Native Hawaiian

□ Guamanian or Chamorro

□ Samoan

□

Other Pacific Islander — Print race, for example, Fijian, Tongan,

and so on. C

COPY
➜ If more people live here, turn the page and continue.

□ Some other race — Print race. C

II I I I I I I I I I I I I I I I I I
7. Does this person sometimes live or stay somewhere else?

□ No □ Yes — Mark I J K all that apply.

□ In college housing □ In the military □ At a seasonal
or second residence

□ For child custody □ In jail or prison □ In a nursing home □ For another reason

➜ If more than six people were counted in Question 1 on the front page, turn the page and continue.

Form D-61 (1-15-2009)

Use this section to complete information for the rest of the people you counted in Question 1 on the front page. We may call for additional information about them.

Person 7 Sex

Last Name

First Name

Age on April 1, 2010 Date of Birth

MI
□
Related to Person 1?

□ Male
-□ Female
Person 8
Sex
□ Male
-□ Female
Person 9
Sex
□ Male
-□ Female
Person 10
Sex
□ Male
-□ Female
Person 11
Sex
□ Male
-□ Female
Person 12
Sex

Month Day

Year

□ Yes

I

□ DI

□ No

Last Name

First Name

MI

Y□ Age on April 1, 2010

Date of Birth Month Day

Year

I □ DI OP Last Name

First Name

L C □ Age on April 1, 2010

Date of Birth Month Day

Year

I □ DINA Last Name

First Name

TIO □ Age on April 1, 2010

Date of Birth Month Day

Year

I M□ A DI Last Name

First Name

INI FOR □ DI I □ Age on April 1, 2010

Date of Birth Month Day

Year
I I I

Related to Person 1?
□ Yes □ No
MI
Related to Person 1?
□ Yes □ No
MI
Related to Person 1?
□ Yes □ No
MI
Related to Person 1?
□ Yes □ No

Last Name

First Name

MI

I ID I

I

I

I

I

I

I

I

I

I

I

I

Age on April 1, 2010 Date of Birth

Related to Person 1?

□ Male □ Female

Month Day

Year

□ DI I I I I

□ Yes □ No

Thank you for completing your official 2010 Census form.

~ FOR OFFICIAL USE ONLY

JIC1

JIC2

IONAL COPY If your enclosed postage-paid envelope is missing, please mail your completed form to: T U.S. Census Bureau A National Processing Center
1201 East 10th Street Jeffersonville, IN 47132
RM If you need help completing this form, call 1-866-872-6868 between 8:00 a.m. and 9:00 p.m.,
7 days a week. The telephone call is free.
O TDD — Telephone display device for the hearing impaired. Call 1-866-783-2010 between F 8:00 a.m. and 9:00 p.m., 7 days a week. The telephone call is free. IN ¿NECESITA AYUDA? Si usted necesita ayuda para completar este cuestionario, llame al
1-866-928-2010 entre las 8:00 a.m. y 9:00 p.m., 7 días a la semana. La llamada telefónica es gratis.
The U.S. Census Bureau estimates that, for the average household, this form will take about 10 minutes to complete, including the time for reviewing the instructions and answers. Send comments regarding this burden estimate or any other aspect of this burden to: Paperwork Reduction Project 0607-0919-C, U.S. Census Bureau, AMSD-3K138, 4600 Silver Hill Road, Washington, DC 20233. You may e-mail comments to <Paperwork@census.gov>; use "Paperwork Project 0607-0919-C" as the subject.
Respondents are not required to respond to any information collection unless it displays a valid approval number from the Office of Management and Budget.

Case 1:18-cv-02711-DLF Document 8-7 Filed 01/18/19 Page 21 of 42
Exhibit 17

12/4/2018

Case 1:18-cv-0271Pr1iv-aDcy,LOFfﬁce Dof oPrcivuacmy aendnOtp8en-G7oveFrnmileendt, U0.S1. /D1e8pa/r1tm9ent oPf Caogmemer2ce2 of 42

.h__tlt.p:..:../;../;w._.w_ w .o_s_ec_._do_c_•.g::o_:v.../;_.o.p:.o".".g""/-'p'-_ri_va_c..y.a/C_..;e_..n_s_u_s--=p--ia_s_.h_t_m_l____
4 captures
2 Feb 2017 - 26Jun 2017

__[.flQ] JAN FEB MAY
02 ►
2016 2017 2018

0 ⍰❎
f
▾ About this capture

HOME PRIVACY

OPEN GOVERNMENT

FOIA

PRIVACY ACT

FACA

DIRECTIVES

ABOUT CONTACT US

U.S. Census Bureau Privacy Impact Assessments (PIAs) and Privacy Threshold Analysis (PTA)

System Name
• CEN01 Data Communications

Approval

PTA

PIA

Date

PIA

4/23/2015

• CEN02 Lenel

PIA

8/8/2016

• CEN03 Economic Census and Surveys and
Special Processing

PIA

6/28/2016

• CEN04 Commerce Business Systems

PIA

3/4/2015

• CEN05 Field Systems Major Application
System

PIA

6/29/2015

• CEN06 National Processing Center (NPC)

PIA

8/20/2014

• CEN08 Decennial

PIA

8/11/2014

• CEN09 Cloud Services

PIA

10/16/2016

• CEN11 Demographic Census, Surveys, and
Special Processing

PIA

7/1/2014

• CEN12 AESDirect

PIA

9/17/2014

• CEN13 Center for Economic Studies
https://web.archive.org/web/20170202092009/http://www.osec.doc.gov/opog/privacy/Census-pias.html

PIA

6/2/2015

1/3

12/4/2018

Case 1:18-cv-0271Pr1iv-aDcy,LOFfﬁce Dof oPrcivuacmy aendnOtp8en-G7oveFrnmileendt, U0.S1. /D1e8pa/r1tm9ent oPf Caogmemer2ce3 of 42

.h__tlt.p:..:../;../;w._.w_ w .o_s_ec_._do_c_•.g::o_:v.../;_.o.p:.o".".g""/-'p'-_ri_va_c..y.a/C_..;e_..n_s_u_s--=p--ia_s_.h_t_m_l____
CEN14 Longitudinal Employer-Household 4 captureDs ynamics (LEHD)
2 Feb 2017 - 26Jun 2017

__[.flQ] JAN FEB MAY
02PI►A
2016 2017 2018

0
9/17/2014
▾ About this capture

• CEN15 Centurion

PIA

2/10/2015

• CEN17 Client Services General Support
System

PIA

8/8/2016

• CEN18 Enterprise Applications

PIA

6/7/2016

• CEN20 Budget Division Applications

PIA

5/5/2016

• CEN21 Human Resources Division
Applications

PIA

8/8/2016

• CEN25 Ofﬁce of Information Security (OIS)
Systems

PIA

10/1/2014

• CEN26 SharePoint

PIA

7/16/2015

• CEN30 Amercian Community Survey

PIA

3/24/2015

• CEN31 Administrative Systems Vol. II

PIA

4/27/2016

• CEN33 DataWeb

PIA

2/4/2015

• CEN34 Foreign Trade Division Applications

PIA

6/2/2014

• CEN35 Governments Division Applications

PIA

11/4/2014

• CEN36 integrated Computer Assisted Data
Entry (iCADE), Census Image Retrieval
Application (CIRA), and MOJO Enhanced
Operational Control System

PIA

7/15/2015

• Automated Export System (AES)

PIA

8/11/2014

https://web.archive.org/web/20170202092009/http://www.osec.doc.gov/opog/privacy/Census-pias.html

2/3

12/4/2018

Case 1:18-cv-0271Pr1iv-aDcy,LOFfﬁce Dof oPrcivuacmy aendnOtp8en-G7oveFrnmileendt, U0.S1. /D1e8pa/r1tm9ent oPf Caogmemer2ce4 of 42

.h__tlt.p:..:../;../;w._.w_ w .o_s_ec_._do_c_•.g::o_:v.../;_.o.p:.o".".g""/-'p'-_ri_va_c..y.a/C_..;e_.n._s_u_s--=p--ia_s_.h_t_m_l____
Customer Experience Management (CEM) Pilot 4 capturePs roject
2 Feb 2017 - 26Jun 2017

__.l [fQ] JAN FEB MAY
02PI►A
2016 2017 2018

0
4/23/2015
▾ About this capture

• Social Media and Web 2.0 Websites and
Applications (Third Party Website with PII)

PIA

3/31/2015

Questions and Comments
Send Questions, Comments or Complaints on the Commerce Privacy program to CPO@doc.gov.
Ofﬁce of Privacy and Open Government Ofﬁce of the Chief Financial Ofﬁcer and Assistant Secretary for Administration U.S. Department of Commerce Page last updated: December 13, 2016

https://web.archive.org/web/20170202092009/http://www.osec.doc.gov/opog/privacy/Census-pias.html

3/3

Case 1:18-cv-02711-DLF Document 8-7 Filed 01/18/19 Page 25 of 42
Exhibit 18

Case 1:18-cv-02711-DLF Document 8-7 Filed 01/18/19 Page 26 of 42

BYLAWS OF
THE ELECTRONIC PRIVACY INFORMATION CENTER (“EPIC”)
As Adopted As of March 16, 2000, As Amended May 1, 2007,
As Amended February 8, 2010, As Amended February 1, 2015, As Amended January 26, 2018

ARTICLE I NAME AND PURPOSES
Section 1.01. Name. The name of the organization is ELECTRONIC PRIVACY INFORMATION CENTER.
Section 1.02. Purpose. The Corporation is organized for the charitable and educational purposes of promoting personal privacy and constitutional rights.
ARTICLE II AUTHORITY AND DUTIES OF DIRECTORS
Section 2.01. Authority of Directors. The Board of Directors ("the Board") is the policy‑making body and may exercise all the powers and authority granted to the Corporation by law.
Section 2.02. Number, Selection, and Tenure. The Board shall consist of no more than fifteen (15) nor less than seven (7) Directors, all of whom must be Members of the Corporation, elected in staggered terms of three (3) years, nominated from among its Members, and confirmed by the Board. A director may serve for any number of terms, consecutive or otherwise. Directors will be elected by the directors then in office. The Board will seek to promote pluralism and diversity among its membership.
Section 2.03. Compensation. Board members shall not be compensated for serving on the Board, but may be reimbursed for actual expenses incurred on behalf of the Corporation. Board members who also serve as employees of the Corporation may be compensated for their service as employees. No more than one (1) paid staff member shall serve as a voting member of the Board. A paid staff member serving on the Board shall not serve as the Chair or Treasurer.
Section 2.04. Resignation and Removal. Resignations are effective upon receipt by the Secretary of written notification, or receipt by the President or other officer if the Secretary is resigning. One or more Directors may be removed at a meeting called for that purpose, with or without cause, by such vote as would suffice for the Director's election.
Section 2.05. Vacancies. Vacancies existing by reason of resignation, death, incapacity or removal before the expiration of a term shall be filled by a majority vote of the remaining

Bylaws of the Electronic Privacy

1

Information Center (“EPIC”)

(January 2018)

Case 1:18-cv-02711-DLF Document 8-7 Filed 01/18/19 Page 27 of 42

directors.
Section 2.06. Meetings. The Board shall hold at least one regular meeting annually. Regular meetings shall be at such times and places as the Board shall determine. Special meetings may be called by any two directors with telephone or written notice.
If an officer or director fails to attend three (3) consecutive meetings of the Board or Executive Committee, the Executive Committee shall evaluate the officer's or director's contribution to the work of the Corporation, his or her reasons for not attending the meetings, as well as any other relevant factors, and if it appears to be in the best interest of the Corporation, may declare the position vacant.
Section 2.07. Quorum and Voting. A quorum shall consist of a majority of the total number of Board members in office. All decisions will be by majority vote of those present at a meeting at which a quorum is present.
Section 2.08. Action Without a Meeting. Any action required or permitted to be taken at a meeting of the Board (including amendment of these Bylaws or the Articles of Incorporation) or of any committee may be taken without a meeting if all the members of the Board or committee consent in writing to taking the action without a meeting and to approving the specific action. Such consents shall have the same force and effect as a unanimous vote of the Board or of the committee as the case may be.
Section 2.09. Participation in Meeting by Conference Telephone. Any or all members of the Board may participate in a meeting by conference telephone or similar communications equipment, so long as members participating in such meeting can hear one another.
Section 2.10. Committees. The Board may, by resolution adopted by a majority of the Directors in office, establish committees of the Board composed of at least two (2) Directors.
Other committees not having and exercising the authority of the Board in the management of the corporation may be designated and appointed by a resolution adopted by a majority of the directors present at a meeting at which a quorum is present. Such committees shall consist of at least two members.
The standing committees of the Board shall be an Executive Committee, composed of the officers, and the Program and Litigation Committee, Finances and Fundraising Committee, Management and Staffing Committee, and Engagement and Outreach Committee. The names of these committees may be changed by resolution of the Board.
For both types of committees, the Board may make provisions for appointment of the chair, establish procedures to govern their activities, and delegate authority as may be necessary or desirable for the efficient management of the property, affairs, business, and/or activities of the Corporation.

Bylaws of the Electronic Privacy

2

Information Center (“EPIC”)

(January 2018)

Case 1:18-cv-02711-DLF Document 8-7 Filed 01/18/19 Page 28 of 42

ARTICLE III AUTHORITY AND DUTIES OF OFFICERS
Section 3.01. Officers. The officers of the Corporation shall be a President, a Chair, a Secretary, a Treasurer, and such other officers as the Board may designate. Two or more offices may be held by the same person, except the offices of secretary and president.
Section 3.02. Election of Officers; Terms of Office. Officers shall serve one (1) year terms. The President, the Secretary, and the Treasurer shall be elected by the Board at its annual meeting in each year. The terms of office shall expire at the next succeeding annual meeting and shall be filled by the Board, at a meeting or by action in writing pursuant to Section 2.08 for a term expiring at the next succeeding annual meeting. Officers shall be eligible for reelection.
Vacancies existing by reason of resignation, death, incapacity or removal before the expiration of a term shall be filled by the Board for the remainder of the unexpired term.
Section 3.03. Resignation. Resignations are effective upon receipt by the Secretary of a written notification, or receipt by the President if the Secretary is resigning.
Section 3.04. Removal. An officer may be removed by the Board at a meeting, or by action in writing pursuant to Section 2.08 whenever in the Board's judgment the best interests of the Corporation will be served thereby. The removal of a person from corporate office will not terminate or otherwise affect any contractual relationship between that individual and the corporation.
ARTICLE IV INDEMNIFICATION
Section 4.01. Definitions. “Matter” shall mean any actual or threatened civil, criminal, or administrative action, arbitration proceeding, claim, suit, proceeding, or appeals therefrom, or any criminal, administrative, or Congressional (or other body’s) investigation, hearing, or other proceeding. “Eligible Person” shall mean any person who at any time was or is a director, a member or any committee or subcommittee, an officer, employee, or volunteer of the corporation.
Section 4.02. Right to Indemnification. Any Eligible Person made a party to or involved in a Matter by reason of his or her position with or service to the corporation shall, to the fullest extent permitted by law, be indemnified by the corporation against all liabilities and all expenses reasonably incurred by him or her arising out of or in connection with such Matter, except in relation to Matters as to which (i) the Eligible Person failed to act in good faith and for a purpose which he or she reasonably believed to be in the best interests of the corporation, or (ii) in the case of a criminal Matter, the person had reasonable cause to believe that his or her conduct was unlawful, or (iii) the person shall be adjudged to be liable for willful misconduct in the performance of a duty, or in the case of a Matter settled by agreement, the settlement shall be predicated on such a liability.

Bylaws of the Electronic Privacy

3

Information Center (“EPIC”)

(January 2018)

Case 1:18-cv-02711-DLF Document 8-7 Filed 01/18/19 Page 29 of 42

Section 4.03. Limitation on Right of Indemnification. Except where an Eligible Person has been successful on the merits with respect to such Matter, any indemnification hereunder shall be made only after (i) the Board (acting by a quorum consisting of Directors who were not involved in such Matter) determines that the Eligible Person met the applicable indemnification standard set forth in section 4.02 above; or (ii) in the absence of a quorum, a finding is rendered in a written opinion by independent legal counsel that the person or persons met the applicable indemnification standard set forth in section 4.02 above.
Section 4.04. Other Rights. The right of indemnification provided hereunder shall not be deemed exclusive of any other right to which any person may be entitled in addition to the indemnification provided hereunder. This indemnification shall in the case of the death of the person entitled to indemnification, inure to the benefit of his or her heirs, executors or other lawful representative.
Section 4.05. Interim Indemnification. The corporation shall, with respect to a Matter described in section 4.02, advance attorneys fees as interim indemnification to any Eligible Person if the following conditions are satisfied: (i)(a) the Board (acting by a quorum consisting of Directors who are not involved in such litigation) determines that the Eligible Person is likely to meet the applicable indemnification standard set forth in section 4.02 above, or (b) in the absence of such a quorum, a finding is rendered in a written opinion by independent legal counsel that the Eligible Person is likely to meet the applicable indemnification standard set forth in section 4.02 above; and (ii) the Eligible Person (a) requests interim indemnification, (b) agrees to repay the interim indemnification promptly upon a determination unfavorable to him or her under section 4.03, and (c) deposits a bond or equivalent security.
Section 4.06. Insurance. The Board may authorize the purchase of and maintain insurance on behalf of any Eligible Person against any liability asserted against or incurred by him which arises out of such person's status in such capacity, or out of acts taken in such capacity, whether or not the Corporation would have the power to indemnify the person against that liability under law.
ARTICLE V MEMBERS
Section 5.01. Qualifications. The Corporation shall designate as Members, following nomination by the current Members and a vote of the Board, distinguished experts in law, technology, and public policy.
Section 5.02. Advisory Board. Members shall sit on the Advisory Board, where they shall provide guidance for the work of the Corporation, participate in the activities of the Corporation, offer support for the Corporation, and provide leadership for the Corporation
Section 5.03. Dues. Members shall pay dues in an amount and on a schedule established by the Board. There shall be provisions for lifetime memberships.
Section 5.04. Service on Committees. Members may serve on Board committees.

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Section 5.05. Annual Meeting. There shall be an annual meeting, open to all Members of the Corporation.
Section 5.05. Annual Evaluation. The Members shall provide an annual evaluation of the Corporation, which shall be reported to the Board of Directors at the Annual Meeting.

ARTICLE VI FINANCIAL ADMINISTRATION
Section 6.01. Fiscal Year. The fiscal year of the Corporation shall be January 1 -December 31 but may be changed by resolution of the Board.
Section 6.02. Checks, Drafts, Etc. All checks, orders for the payment of money, and insurance certificates shall be signed or endorsed by an officer or officers or agent or agents of the Corporation and in a manner as shall from time to time be determined by resolution of the Board or of any committee to which such authority has been expressly delegated by the Board.
Section 6.03. Contracts. Unless the Board determines otherwise by resolution, the President, Secretary, Treasurer, Board Chair and Chair of the Executive Committee shall all be authorized to execute contracts on behalf of the corporation.
These individuals may, with written notice to the Board, delegate this authority to employees or volunteers subject to limitations upon the delegated authority as may be necessary or expedient for running the affairs of the corporation. Unless otherwise expressly determined by the Board, no other individuals shall be authorized to bind the corporation to any contract, including the chair of any committee other than the Executive Committee.
Section 6.04. Deposits and Accounts. All funds of the Corporation, not otherwise employed, shall be deposited in general or special accounts in the banks, trust companies, or other depositories as the Board or any committee to which such authority has been delegated by the Board may select, or as may be selected by any officer or officers or agent or agents of the Corporation, to whom such power may be delegated by the Board. For the purpose of deposit and for the purpose of collection for that account of the Corporation, checks, drafts, and other orders of theCorporation may be endorsed, assigned, and delivered on behalf of the Corporation by any officer or agent of the Corporation.
Section 6.05. Annual Financial Statements. Complete financial statements shall be presented to and reviewed by the Board after the close of each fiscal year.
ARTICLE VII CONFLICTS OF INTEREST
Section 7.01. Disclosure of Financial Interests. To identify possible conflicts of interest, all directors, officers, and members of any committee exercising Board- delegated powers must

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disclose to the Board, or to the members of such committee, the existence of any financial interest in any entity with which s/he knows or has reason to know the Corporation or any legally related organization has or is negotiating a transaction or arrangement, and all material facts related to that interest. Financial interests include any direct or indirect relationship, through business, investment, or family, such as actual or potential ownership or investment interests or compensation arrangements. Directors shall also disclose any fiduciary duty to a person or entity other than the Corporation that might jeopardize the director's ability to exercise independent judgment and act in the best interests of the Corporation. The fact that a director, officer, or committee member is also a director or officer or member of a not‑for‑profit organization that obtains or seeks funds from institutions or individuals from which the Corporation also obtains or seeks funds shall not by itself be deemed to be a conflict of interest.
Section 7.02. Determination of Conflicts of Interest. After the interested person has delivered all relevant information and has retired from the room, the Board or committee must determine whether or not the financial interest creates a conflict of interest that merits recusal of the interested Director from consideration of the matter.
Section 7.03. Resolution of Conflicts of Interest. If the Board determines that a conflict of interest does exist, it must ensure that the interested director(s) do not participate in final decision making with regard to the transaction. The Board may approve the transaction or arrangement, or some alternative if it determines it: a) is in the organization's best interests and for its own benefit; b) is fair and reasonable to the organization; and c) is the most advantageous transaction or arrangement the organization can obtain with reasonable efforts under the circumstances.
Section 7.04. Violation of Conflict of Interest Policy. If an officer, director, or member of a committee with Board-delegated powers violates this conflict of interest policy, the Board, in order to protect the Corporation's best interests, may take appropriate disciplinary action against the interested person. Such action may include formal reprimand, cancellation of the transaction or arrangement generating the conflict, suspension of employment, and/or removal from the Board.
Section 7.05. Distribution of Conflict of Interest Policy. All officers, directors, and members of committees with Board-delegated powers shall receive a copy of the Conflict of Interest Policy, as it appears in these By-laws. All officers, directors, and members of committees with Boarddelegated powers shall sign an annual statement declaring that the person: received a copy of the policy; has read and understands the policy; and agrees to comply with the policy.
ARTICLE VIII COMPENSATION
The Board shall adopt a policy establishing procedures for reviewing and setting financial compensation to any individual exercising substantial influence over the corporation to ensure that such compensation is no more than reasonable anddoes not otherwise result in an excess benefit to the person, and requiring that adequate documentation be maintained to support the basis for setting such compensation.

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ARTICLE IX RECORD KEEPING
The Secretary or his or her designee shall keep or cause to be kept adequate minutes of all Board or committee meetings, and all meetings of committees with Board-designated powers reflecting at a minimum the names of those in attendance, any resolutions passed and the outcomes of any votes taken. When potential conflicts of interests are discussed, the minutes shall include: the names of the persons who disclosed financial interests; the nature of the financial interests; whether or not the Board determined that a conflict existed; the names of the persons present for the discussions and votes related to the relevant transaction or arrangement; the content of those discussions, including any alternative transactions or arrangements; and a record of the vote. At the request of any participating Board member, the records of such discussions and individual votes may be kept sealed, with only the outcome reported publicly.
ARTICLE X ANNUAL REPORTS
An annually updated written account of the Corporation's purposes, structure, programs and financial condition shall be published and made publicly available. The annual report shall contain: a description of the Corporation's purpose(s); descriptions of its overall programs, activities and accomplishments; a statement of its eligibility to receive deductible contributions; information about the governing body and structure, including identification of officers, directors, and chief administrative personnel; and the audited financial statements or, at a minimum, a comprehensive financialsummary that reflects all revenue, reports expenses by program, management and fund‑raising categories, and reports year‑end balances.
ARTICLE XI AMENDMENT OF BYLAWS
These Bylaws may be amended by a majority vote of the Board, provided seven (7) days' prior notice is given of the proposed amendment or provided all members of the Board waive such notice, or by unanimous consent in writing without a meeting pursuant to Section 2.08.

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Exhibit 19

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PREPARED STATEMENT OF
RON JARMIN, PhD. PERFORMING THE NON-EXCLUSIVE FUNCTIONS AND DUTIES OF
THE DIRECTOR U.S. CENSUS BUREAU
and
EARL COMSTOCK DIRECTOR, OFFICE OF POLICY AND STRATEGIC PLANNING
U.S. DEPARTMENT OF COMMERCE
Before the Committee on Oversight and Government Reform U.S. House of Representatives
“Progress Report on the 2020 Census”
8 May 2018
Good afternoon, Chairman Gowdy, Ranking Member Cummings, and members of the Committee. We welcome this opportunity to update you on the status of the 2020 Census. Before we begin, we would like to thank Congress for the Census Bureau’s recent appropriation, which underscores Congress’ commitment to a successful 2020 Census. The Department of Commerce and Census Bureau share your commitment and today we will provide a brief review of our progress to conduct a complete and accurate census.
2018 End-to-End Census Test We are in the midst of the 2018 End-to-End Census Test. This is our final major field test before the 2020 Census. We are testing the interfaces between 44 IT systems critical for the 2020 Census, and their integration with the 24 major operations that are part of the 2018 End-to-End Census Test.
Tomorrow, we begin the Nonresponse Follow-up Operations for the 2018 End-to-End Census Test. Nonresponse Follow-up is an eight-week field operation to gather responses from households that have not yet responded by Internet, telephone, or paper questionnaire. Approximately 56 percent of households in the test did not respond to the Census questionnaire, so we will send approximately 900 enumerators to knock on doors and gather the information. This key operation involves 31 systems with appropriate interfaces, and will provide important feedback as we prepare to conduct the 2020 Census.

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The 2018 End-to-End Census Test’s Nonresponse Follow-up operation began in August 2017 with the Address Canvassing operation in three locations: Pierce County, Washington; the Bluefield-Beckley-Oak Hill, West Virginia area; and, Providence County, Rhode Island. These locations allowed the Census Bureau to test systems with and without Internet connectivity and to study critical address list development operations in a wide range of geographical situations including rural and mountainous areas. Importantly, in areas with low Internet connectivity Census Bureau field staff were able to receive their assignments and submit their payroll and operational data at the beginning or end of their shifts. By design, staff began and ended their shifts in areas with Internet connectivity so that they could do this. They did not require Internet access while they were actually conducting the listing operation. We were able to successfully integrate with the operational control system in field conditions. We also integrated with the other decennial systems effectively, such as the system we are using to provide directional information to staff ensuring they complete their work in the most efficient manner possible. Additionally, we tested the implementation of the independent quality control component, which ensures the proper disposition of cases in real time providing us with important information when cases fail to pass quality control.
The 2017 Address Canvassing operation revealed areas where our systems and operations need to improve, especially with regard to training. Some of these areas are being addressed as we continue to refine our training modules. Address listing is a complicated process and we have identified ways to improve technical training. The West Virginia site, in particular, experienced connectivity issues. The challenge of unreliable wireless signals is one of the reasons that site was chosen. Because of connectivity issues, some of the employees hired to carry out the address listing operation had difficulty completing the self-paced online training at their home. We continue to examine the experiences of our listers so that we can enhance this functionality and improve both systems and operations.
Just as we learned a great deal from the Address Canvassing operation, we are learning from the operations conducted in Providence. We will continue to make the necessary adjustments to our systems and operations in response to what we observe and experience during the 2018 End-toEnd Census Test.
We opted to conduct the 2018 End-to-End Test in Providence County because it represents an ideal location for testing data collection operations. It offers many different situations and provides challenges that we will face across the country in 2020, and its demographics mirror those of the nation. Providence County has a population of over 600,000, more than a quartermillion housing units, and historically hard-to-count populations. Providence County provides an opportunity to test all of the systems and operations planned for the 2018 End-to-End Census Test. Providence County’s urban areas include high vacancy rates, and neighborhoods and housing that have undergone considerable conversion for many years. This allows us to validate our address canvassing operation (for example, identifying split or converted housing units). There also is a solid presence of Group Quarters, which are residences that contain multiple unrelated residents, allowing us to conduct that operation.
The test’s self-response phase began with a series of mailings that were sent to housing units beginning in mid-March. We received a high number of responses through the Internet—almost
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64 percent of the total responses. Households also are responding by telephone (6 percent) or returning the paper questionnaire by mail (30 percent). However, consistent with our planned approach for the 2020 Census, households only received a questionnaire on the first mailing if the household does not have strong Internet connectivity or if the household is considered unlikely to use the Internet. Households with older people often fall into this latter category. Regardless, every household that had not responded after three mailings received a paper questionnaire on the fourth mailing.
The remaining peak operations in Providence, Rhode Island, are Group Quarters, Update Leave, and Nonresponse Follow-up. The Group Quarters operation is designed to enumerate people who live in places such as college dormitories, skilled nursing facilities, and prisons. The Update Leave operation is designed for areas that do not have a city-style address, such as “100 Main Street,” where the address and the geographic location of the housing units are linked. Areas without city-style addresses are most common in rural areas where mailing addresses are grouped together (e.g., multiple mail boxes grouped together at the end of a rural road) and not tied to the geographic location of the actual housing unit (e.g., Post Office Boxes). During Update Leave, field staff will update our address list and leave a questionnaire packet at each household in this area. Those who do not respond are included in the Nonresponse Follow-up operation where we collect information by sending a census enumerator to interview the household.
All of the planned innovations for the 2020 Census are coming together in the 2018 End-to-End Census Test and the lessons learned will provide a firm foundation for success in 2020. We are looking closely at data from the Address Canvassing operation to make sure that our blend of inoffice and in-field Address Canvassing meets our standards for an accurate and comprehensive address list. The Internet and telephone response modes are being thoroughly tested, as is the Paper Data Capture operation. We also are making it easier for people to respond in real time with a smart phone or a tablet. Field staff will collect information using hand-held devices and their work will be managed efficiently and effectively by leveraging automated processes. Finally, we will continue to examine the use of administrative records to inform final determinations about our ability to improve the efficiency of the Nonresponse Follow-up operation using information that people have already provided to the government. During and after the test, we will adjust the systems and operations based on what we learned to make sure that both are ready for the 2020 Census.
Systems Readiness We developed a comprehensive schedule for developing and integrating the key systems for the 2018 End-to-End Census Test. Each system has its own well-defined scope, requirements, schedule, and costs, and each is overseen by experienced project management teams. As we enter the peak operations of the test, 40 out of the 44 systems supporting the test have been deployed. No system will be released without completing the necessary integration testing and security authorizations. All 44 are on track to be fully integrated and deployed when they are needed to support operations in the test.
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The Census Bureau has been working closely with the Government Accountability Office (GAO) to ensure that the Census Bureau and the GAO share a consistent understanding of the status of systems readiness, and we both are monitoring final development and testing of the remaining systems needed for the 2018 End-to-End Census Test. All of our systems for the 2020 Census are being integrated through a contracted solution that the Census Bureau refers to as the “technical integrator.”
The Census Bureau’s Office of Information Security, under the guidance of the Department of Commerce’s Chief Information Officer, is working with the technical integrator to ensure that the systems are secure and are authorized to operate (ATO) before going live. The ATO process is critical because it ensures that cybersecurity standards are addressed and risks are minimized for all systems based on federal policies and procedures. GAO is reviewing our progress to ensure that our processes and procedures within our Systems Engineering and Integration framework are consistent with GAO’s best practices. We value GAO’s independent assessment and are appreciative of their continued assessment and support.
With respect to the 2018 End-to-End Census Test and looking forward to the 2020 Census, the Census Bureau is maintaining a well-defined schedule and framework for releasing systems for the remainder of the 2018 Test and then for the 2020 Census. Lessons learned from the 2018 Test will be incorporated to enhance and improve the systems. We also have a well-developed process for conducting the scalability tests on our systems during 2018. The technical integrator is enabling the scalability test using infrastructure in the cloud and the data center. Conducting the scalability tests is a major milestone this year, and we are eager to meet this milestone and fine tune our systems to scale to predicted peak loads in 2020.
Finally, we are engaging with the private sector and the federal government intelligence community in the area of cybersecurity to ensure the information we collect is protected, that we can withstand the threat of cyber attacks, and, if necessary, contain a threat in a way that sustains service and maintains public trust.
2020 Operations Already Underway: LUCA, In-Office Address Canvassing, and Delivery of the 2020 Census Questions Even as we are in the midst of the 2018 End-to-End Census Test, key operations for the 2020 Census are already up and running. Today, we would like to summarize our progress on the Local Update of Census Addresses (LUCA) program, In-Office Address Canvassing, and the delivery of the 2020 Census planned questions to Congress.
LUCA, which began last year, provides tribal, state, and local governments an opportunity to review and comment on the Census Bureau’s address list, while following the requirements of Title 13. More than eleven thousand governmental units, 45 states, the District of Columbia, and the Commonwealth of Puerto Rico, as well as major counties and cities, and tribal governments, have registered for the 2020 Census LUCA program. These registrations exceed those for the 2010 Census program and we are pleased that they cover more than 98 percent of both the country’s housing units and the population. The Census Bureau has begun sending these governments their address packages so that they can conduct their review. As of today,
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approximately 1200 hundred governments have returned their packages to the Census Bureau, and of these about 30 percent of the submissions have not made any changes to the address list.
The In-Office Address Canvassing operation is one of the important innovations in the 2020 Census. Since 2015, we have been updating the most recent Census Bureau address list with new information from the United States Postal Service and data from tribal, state, and local governments and third parties (i.e., commercial vendors). We also review satellite imagery to help determine where address changes are occurring. Based on these changes, the Census Bureau will develop a plan for capturing those changes. This plan will include In-Field Address Canvassing where address updates cannot be obtained or verified or in areas undergoing rapid change. The number of addresses requiring In-Field Address Canvassing is expected to be approximately 30 percent of the total number of addresses, compared to 100 percent in 2010.
The Census Bureau is required by Section 141(f) of Title 13 of the U.S. Code to submit the subjects proposed for the next census to Congress no later than three years before April 1st of the upcoming decennial year. A document fulfilling that requirement was submitted to Congress on March 28, 2017. Section 141(f) also requires the questions proposed to be included in the next census be submitted to Congress no later than two years before Census Day, which will be April 1, 2020. The document that fulfilled this requirement for the 2020 Census, and the American Community Survey, was delivered to Congress on March 29, 2018. Pursuant to the Paperwork Reduction Act of 1995, later this year the Census Bureau will provide the public an opportunity to comment on the proposed questions, and then send the proposed questions to OMB.
As background, we would like to provide an overview of the process for determining the content on the 2020 Census and the American Community Survey. The Department of Commerce and the Census Bureau conduct a rigorous legal, technical, program, and policy review of each question to determine whether it should be included for the Decennial Census Program, which includes the 2020 Census and the American Community Survey. When it passed Title 13, Congress delegated to the Secretary of Commerce the authority to determine content for the Decennial Census Program.
Throughout each decade, regular content reviews are conducted to ensure that the information collected through the Decennial Census Program is required by federal programs. In December 2017, the Department of Justice requested that the Census Bureau reinstate a citizenship question on the 2020 Census to provide census block level citizenship voting age population data, which DOJ finds critical to its enforcement of Section 2 of the Voting Rights Act. This request underwent a thorough legal, technical, and policy review. On March 26, 2018, the Secretary of Commerce directed the Census Bureau to reinstate the citizenship question on the 2020 Census.
For the 2020 Census, the Census Bureau will use the citizenship question currently used on the American Community Survey. A question on citizenship has been asked on the American Community Survey each year since 2005 and also was asked on the long form censuses in 1970, 1980, 1990, and 2000.
The Census Bureau currently is taking steps to make the necessary operational adjustments to all data collection and processing systems to include the new question. The Census Bureau also is
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taking steps to further enhance its administrative record data sets, protocols, and statistical models to provide more complete and accurate data. As is our standard practice, the Census Bureau will conduct research and develop this administrative records use strategy in an open and transparent manner, consulting with expert groups and stakeholders.
In addition to citizenship, the 2020 Census will ask questions about age, sex, race, Hispanic origin, relationship, and tenure. Some operational questions, such as name and telephone number, also are asked to better administer the data collection process and to ensure greater accuracy of the data collected. Contact information is not part of the published data and all data collected is carefully protected, as mandated by federal law, to maintain confidentiality and respect the personal information of respondents.
The document Questions Planned for the 2020 Census and American Community Survey, which was delivered to Congress on March 29, 2018, includes images of each question, information about why we ask each question, and the federal and selected local community uses of the data.
American Community Survey data are critical for communities and businesses nationwide. The American Community Survey is the nation’s premier survey, providing the only source of comparable data for all of America’s communities, and will continue to cover more than 35 topics, for example, school enrollment, veteran status and period of service, home value, and computer and Internet use. In 2019 and 2020, the Census Bureau will implement several changes to make it easier for respondents to answer the survey questions and improve the quality of the American Community Survey data.
The 2020 Census also is conducted in the Island Areas of American Samoa, the Commonwealth of the Northern Mariana Islands, Guam, and the U.S. Virgin Islands. For the 2020 Island Areas Censuses, we plan to use a modified version of the American Community Survey form that better meets the needs of the Island Areas. For example, we do not plan to ask about home heating fuel but do plan to ask about sewage disposal and source of water. This innovative approach of using existing data collection and processing systems will enable the Census Bureau to more quickly and efficiently tabulate and publish data from the 2020 Census for the Island Areas.
Enumerating Traditionally Undercounted Populations To ensure a complete and accurate census we also must encourage people to respond. As in past decennial censuses, we will mount a robust Communications and Partnership Program to encourage everyone to respond, including those who are traditionally hard to count. People may be hard to count for different reasons, such as those who are highly mobile, homeless, living in remote areas, living in gated communities, or other reasons.
For the 2020 Census, we are building a research foundation for our Integrated Partnership and Communications Program that is stronger than in 2010. We recently conducted the Census Barriers, Attitudes and Motivators Survey (CBAMS), which consisted of two components. First, a quantitative survey was mailed out to 50,000 households. We expect to receive data from this survey in the summer, which will give us important information about the major population
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groups in the country. The second component consists of qualitative focus groups that will allow us to hone in on the attitudes and motivators of smaller population groups and populations that cannot be well represented in the quantitative survey, including Native Americans, Alaska Natives, and people who speak languages other than English or are not proficient in English.
The information we receive from CBAMS will be combined with other data at the Census Bureau that we are using to develop models projecting the likelihood of people to respond. Along with the information from CBAMS, this information will provide us with the strongest research foundation we have ever had. These research efforts will help us ensure that our messaging is as effective as possible and that our advertising and partnership efforts are welldirected. Finally, with the support of the recent appropriation, we are looking at other important communications activities and building out our partnership staff earlier than planned.
We recognize that communications and partnerships are at the heart of reaching traditionally hard-to-count populations. Extensive advertising in media consumed by specific populations is critical. In addition to traditional media, we will be active in digital media and on the Web. Our advertising and partnership support materials will be in multiple languages and we will develop and implement a Statistics in Schools program that will help young people understand the importance of responding to the census so that they can take the message home to their families.
We also plan to strengthen our national and local partnerships. We are currently reaching out to major corporations and national organizations, two years ahead of Census Day, so that they can build support for the 2020 Census into their business plans. This is the earliest we have ever started this effort. In addition, seasoned partnership specialists, many with decades of experience, have been working since January 2017 to help tribal, state, and local governments develop Complete Count Committees, which bring leaders and government officials together to develop plans to support the 2020 Census. As we ramp up to 1,000 partnership specialists in FY 2019, our goal is to exceed the 248,000 community partners we had in 2010. Our partners are the trusted voices in communities across the country. They include schools, hospitals, clinics, legal aid centers, faith-based organizations, and businesses large and small. Census partners help people understand that responding to the census is safe and important, and that their responses are confidential and protected by law.
Our efforts to reach traditionally undercounted populations do not stop with communications and partnerships. Through our language program, we will make it possible to respond to the Census in 12 languages, in addition to English, covering nearly 99 percent of the population, or 87 percent of those with limited English proficiency. Language support materials will be provided in a total of 59 languages, and we are developing templates to help our partners carry our messaging in the languages and dialects spoken by small population groups throughout the country.
To reach people who live in different places and situations, the Integrated Partnership and Communications Program will be the most tailored in our history. In fact, most of the operations we have mentioned —from our field operations, to our communication and partnership efforts, to our language program—are designed to reach people who live in different places or situations. We tailor our operations for rural areas and for areas that have experienced natural disasters.
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With that in mind, we also would like to share that we recently made the decision to extend the Update Leave operation that we described earlier across the entire Commonwealth of Puerto Rico. This will help us ensure that our address list is correct and that we are adapting to any changes caused by Hurricane Maria. We will make similar changes to other areas as necessary, including the Gulf States impacted by flooding, and those parts of the Western states that experienced wildfires. We also conduct a specific operation in remote Alaska that starts in January of 2020 before the tundra thaws and many people leave their villages. These are only some of the many other examples of the steps we take to adapt our operations to the unique places where people live.
Finally, we are asking federal, state, and local leaders to encourage their constituents to stand up and be counted. We ask that leaders remind the public that the answers they provide on a census form are confidential and protected by law. It is important that community leaders ensure the public knows that census answers may not be used for law enforcement or any other purpose that would reveal a person’s identity or how an individual responded to a question. The Census Bureau is bound by Title 13 of the United States Code. This law not only provides authority for the work we do, but also provides strong protection for the information we collect from individuals and businesses.
Anyone who handles census data swears an oath for life to keep those data confidential. Under Title 13, private information is never published. It is against the law to disclose or publish private information. The information the Census Bureau collects cannot be used for any reason except to produce statistics, and violations of Title 13 are punishable by fines and up to five years in prison. The Census Bureau trains every employee, including its field enumerators, on the importance of protecting private information and the importance of the oath, as well as the fact that penalties for violating this law are applicable for a lifetime. Public encouragement and reassurance of this law and our commitment to protecting confidentiality would help achieve our goal of a complete and accurate census in 2020.
2020 Census Activities Supported by the FY 2019 President’s Budget Looking forward, the FY 2019 President’s Budget requested $3.8 billion for the Census Bureau, which includes $3.1 billion to support the 2020 Census. As noted above, the Census Bureau appreciates Congress’ support for the decennial census and the inclusion of an additional $1.1 billion beyond the program’s estimate for 2018 (including contingency funds) in the 2018 Omnibus appropriations act. These funds will help provide financial certainty to the program as we transition from FY 2018 to FY 2019, and represent a down payment on the $3.1 billion requested in 2019 to continue all preparatory activities and existing field operations.
As we move into 2019, we will undertake a wide range of simultaneous activities designed to finalize preparations for the 2020 Census as outlined in the President’s budget. Key activities for the 2020 Census will take place in 2019. We will make final refinements for all systems to ensure they meet all requirements, are secured, are tested, and are seamlessly integrated. The field offices and other field infrastructure must be stood up nationwide in 2019, with the first 40 Area Census Offices (ACO) opening between January and March of 2019, and the remaining 208 offices opening in the summer of 2019. The ACOs will house the managers, staff, materials,
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and equipment needed to support the hundreds of thousands of Census Bureau employees conducting local census operations. Partnership Specialists will work throughout 2019 to build the network of more than 300,000 census partners who will be the trusted voices to encourage communities across the nation to respond to the 2020 Census. In October 2018, we will begin the full-scale development and implementation of all aspects of the communications program, including the establishment of the media spend plans, messaging, and the creative treatments of the advertising campaign. This work lays the foundation for our first advertising buys for the 2020 Census in May 2019. In 2019, we will conduct the first major field operation for the 2020 Census, which is the InField Address Canvassing we mentioned earlier. In this operation, we send field staff to check the accuracy of the addresses in areas that are the most difficult to canvass and cannot be updated by the In-Office Address Canvassing Operation. Approximately 76,000 address canvassing listers and supervisors will be trained and sent into the field to complete this difficult and important work from mid-August to early October of 2019. Recruitment for this operation will take place in the spring of 2019, with training beginning in summer 2019. The operation itself will begin in late summer and stretch to early fall. The physical printing of the majority of the paper materials for the 2020 Census will begin in June 2019. We also will finalize and secure all of the operations and systems related to the use of administrative records and third-party data and ensure they are working together in preparation for use in the 2020 Census. Both the 2020 Census and the American Community Survey are essential to the Census Bureau's mission to serve as the leading source of data about our nation’s people and economy. All of the censuses and surveys we conduct are important, and we appreciate Congress’ support for our work. With less than two years until Census Day, though, we think the Congress is appropriately focused on the 2020 Census, and as you can see, we are now moving ahead at full speed. Much work remains, but we are well-positioned to get it done so that we can conduct a complete and accurate 2020 Census. We look forward to answering your questions.
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 Case 1:18-cv-02711-DLF Document 20 Filed 03/11/19 Page 1 of 2
IN THE UNITED STATES DISTRICT COURT FOR THE DISTRICT OF COLUMBIA

ELECTRONIC PRIVACY INFORMATION CENTER,
Plaintiff,
v.
UNITED STATES DEPARTMENT OF COMMERCE, et al.,
Defendants.

Civil Action No. 1:18-cv-02711 (DLF)

DEFENDANTS’ MOTION TO DISMISS

Defendants United States Department of Commerce and United States Census Bureau, by

their undersigned counsel, hereby move pursuant to Rule 12(b)(1) and Rule 12(b)(6) of the Federal

Rules of Civil Procedure for dismissal of this action for lack of subject matter jurisdiction and for

failure to state a claim upon which relief may be granted. The grounds for the aforementioned

motion are set forth in the accompanying Memorandum in Support of Defendants’ Motion to

Dismiss. A proposed order is also submitted.

Dated: March 11, 2019

Respectfully submitted,

JOSEPH H. HUNT Assistant Attorney General Civil Division

CARLOTTA P. WELLS Assistant Branch Director

/s/ Kristina A. Wolfe KRISTINA A. WOLFE

Case 1:18-cv-02711-DLF Document 20 Filed 03/11/19 Page 2 of 2
JOSEPH E. BORSON Trial Attorneys United States Department of Justice Civil Division, Federal Programs Branch 1100 L Street, N.W. Washington, DC 20530 Phone: (202) 353-4519 Email: kristina.wolfe@usdoj.gov
Counsel for Defendants

Case 1:18-cv-02711-DLF Document 20-1 Filed 03/11/19 Page 1 of 37
IN THE UNITED STATES DISTRICT COURT FOR THE DISTRICT OF COLUMBIA

ELECTRONIC PRIVACY INFORMATION CENTER,
Plaintiff,
v.
UNITED STATES DEPARTMENT OF COMMERCE, et al.,
Defendants.

Civil Action No. 1:18-cv-02711 (DLF)

DEFENDANTS’ MEMORANDUM IN SUPPORT OF THEIR MOTION TO DISMISS

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INTRODUCTION .......................................................................................................................... 1 BACKGROUND ............................................................................................................................ 2 I. STATUTORY BACKGROUND........................................................................................ 2 II. FACTUAL BACKGROUND. ............................................................................................ 4 STANDARD OF REVIEW ............................................................................................................ 8 ARGUMENT .................................................................................................................................. 9 I. PLAINTIFF LACKS STANDING. .................................................................................... 9 II. PLAINTIFF FAILS TO STATE A CLAIM. .................................................................... 17
1. The Census Bureau Has Not “Initiated a New Collection of Information.”......... 19 2. Plaintiff is Not Likely to Show That its Claims Are Ripe or That it States a
Claim Under the APA. .......................................................................................... 26 CONCLUSION............................................................................................................................. 30
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TABLE OF AUTHORITIES
CASES
Abbott Labs. v. Gardner, 387 U.S. 136 (1967)............................................................................................................ 26, 27
Am. Legal Found. v. FCC, 808 F.2d 84 (D.C. Cir. 1987) .................................................................................................... 17
Am. Library Ass’n v. FCC, 401 F.3d 489 (D.C. Cir. 2005) .................................................................................................. 11
Am. Petroleum Inst. v. EPA, 683 F.3d 382 (D.C. Cir. 2012) ............................................................................................ 26, 27
Ashcroft v. Iqbal, 556 U.S. 662 (2009).................................................................................................................... 9
Ass’n of Flight Attendants-CWA, AFL-CIO v. U.S. Dep’t of Transp., 564 F.3d 462 (D.C. Cir. 2009) .................................................................................................. 17
Atherton v. D.C. Office of the Mayor, 567 F.3d 672 (D.C. Cir. 2009) .................................................................................................... 9
Barr v. Clinton, 370 F.3d 1196 (D.C. Cir. 2004) .................................................................................................. 8
Bell Atl. Corp. v. Twombly, 550 U.S. 544 (2007).................................................................................................................... 9
Belmont Abbey Coll. v. Sebelius, 878 F. Supp. 2d 25 (D.D.C. 2012) ...................................................................................... 26, 27
Bennett v. Spear, 520 U.S. 154 (1997).................................................................................................................. 28
BP Am. Prod. Co. v. Burton, 549 U.S. 84 (2006).................................................................................................................... 19
Clapper v. Amnesty Int’l USA, 568 U.S. 398 (2013).................................................................................................................. 12
Davis v. FEC, 554 U.S. 724 (2008).................................................................................................................. 10
Dep’t of Justice v. Reporters Comm. for Freedom of Press, 489 U.S. 749 (1989).................................................................................................................. 14 ii

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Elec. Privacy Info. Ctr. v. Presidential Advisory Comm’n on Election Integrity, 266 F. Supp. 3d 297 (D.D.C. 2017) .......................................................................................... 16
Elec. Privacy Info. Ctr. v. Presidential Advisory Comm’n on Election Integrity, 878 F.3d 371 (D.C. Cir. 2017) ........................................................................................... passim
Elec. Privacy Info. Ctr. v. U.S. Dep’t of Commerce, __ F. Supp. 3d __, 2019 WL 498520 (D.D.C. Feb. 8, 2019), appeal filed, No. 19-5031 (D.C. Cir. Feb. 21, 2019) ........................................................ passim
Fed. Election Comm’n v. Akins, 524 U.S. 11 (1998).................................................................................................................... 14
Friends of Animals v. Jewell, 824 F.3d 1033 (D.C. Cir. 2016) ................................................................................................ 15
Friends of Animals v. Jewell, 828 F.3d 989 (D.C. Cir. 2016) ............................................................................................ 13, 15
Fund Democracy, LLC v. SEC, 278 F.3d 21 (D.C. Cir. 2002) .............................................................................................. 16, 17
FW/PBS, Inc. v. City of Dallas, 493 U.S. 215 (1990).................................................................................................................. 10
Hazardous Waste Treatment Council v. Reilly, 938 F.2d 1390 (D.C. Cir. 1991) ................................................................................................ 29
Her Majesty the Queen in Right of Ontario v. EPA, 912 F.2d 1525 (D.C. Cir. 1990) ................................................................................................ 29
Kelso v. U.S. Dep’t of State, 13 F. Supp. 2d 1 (D.D.C. 1998) ................................................................................................ 19
Khadr v. United States, 529 F.3d 1112 (D.C. Cir. 2008) .................................................................................................. 8
Knight v. Comm’r, 552 U.S. 181 (2008).................................................................................................................. 21
Kokkonen v. Guardian Life Ins. Co. of Am., 511 U.S. 375 (1994).................................................................................................................... 8
Lujan v. Defs. of Wildlife, 504 U.S. 555 (1992)............................................................................................................ 10, 14
Lujan v. Nat’l Wildlife Fed’n., 497 U.S. 871 (1990).................................................................................................................. 30
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Nat’l Treasury Emps. Union v. United States, 101 F.3d 1423 (D.C. Cir. 1996) ................................................................................................ 10
New York v. U.S. Dep’t of Commerce, 351 F. Supp. 3d 502 (S.D.N.Y. 2019), cert granted, 2019 WL 331100 (U.S. Feb. 15, 2019)............................................................................... 11, 12
Norton v. S. Utah Wilderness, All., 542 U.S. 55 (2004).............................................................................................................. 29, 30
Porter v. CIA, 778 F. Supp. 2d 60 (D.D.C. 2011) .............................................................................................. 9
Pub. Citizen v. Dep’t of Justice, 491 U.S. 440 (1989).................................................................................................................. 14
Sebelius v. Cloer, 569 U.S. 369 (2013).................................................................................................................. 19
Sierra Club v. EPA, 292 F.3d 895 (D.C. Cir. 2002) .................................................................................................. 10
Sierra Club v. Thomas, 828 F.2d 783 (D.C. Cir. 1987), partially abrogated by statute on other grouds as reported by, Mexichem Specialty Resins, Inc. v. EPA, 787 F.3d 544 (D.C. Cir. 2015)............ 29
Sinochem Int’l Co. v. Malay Int’l Shipping Corp., 549 U.S. 422 (2007).................................................................................................................... 9
Speelman v. United States, 461 F. Supp. 2d 71 (D.D.C. 2006) .............................................................................................. 8
Town of Chester v. Laroe Estates, Inc., 137 S. Ct. 1645 (2017) .............................................................................................................. 10
Trudeau v. FTC, 456 F.3d 178 (D.C. Cir. 2006) .................................................................................................. 28
Vill. of Bensenville v. FAA, 376 F.3d 1114 (D.C. Cir. 2004) ................................................................................................ 27
Warth v. Seldin, 422 U.S. 490 (1975).................................................................................................................. 10
Wyo. Outdoor Council v. U.S. Forest Serv., 165 F.3d 43 (D.C. Cir. 1999) .................................................................................................... 27
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STATUTES 5 U.S.C. § 551............................................................................................................................... 29 5 U.S.C. § 552a ............................................................................................................................... 3 5 U.S.C. § 704............................................................................................................................... 28 5 U.S.C. § 706................................................................................................................. 2, 7, 28, 29 13 U.S.C. § 1 et seq......................................................................................................................... 4 13 U.S.C. § 2................................................................................................................................... 4 13 U.S.C. § 4................................................................................................................................... 4 13 U.S.C. § 5................................................................................................................................... 4 13 U.S.C. § 8................................................................................................................................. 12 13 U.S.C. § 9........................................................................................................................... 11, 12 13 U.S.C. § 141............................................................................................................................... 4 13 U.S.C. § 221............................................................................................................................. 24 44 U.S.C. § 3501 et seq............................................................................................................... 2, 3 44 U.S.C. § 3502.................................................................................................................... passim 44 U.S.C. § 3506....................................................................................................................... 4, 24 44 U.S.C. § 3507....................................................................................................................... 4, 24 44 U.S.C. § 3512........................................................................................................................... 24 E-Government Act, Pub. L. 107-347, 116 Stat. 2899 (2002),
codified at 44 U.S.C. § 3501.............................................................................................. passim RULES Fed. R. Civ. P. 12 ........................................................................................................................ 8, 9 REGULATIONS 5 C.F.R. § 1320.3 .......................................................................................................................... 25 5 C.F.R. § 1320.10 ........................................................................................................................ 24
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U.S. CONSTITUTION U.S. Const. art. I, § 2....................................................................................................................... 4 OTHER AUTHORITIES Elec. Privacy Info. Ctr., About,
https://www.epic.org/epic/about.html....................................................................................... 16 EPIC Bylaws,
https://www.epic.org/epic/bylaws.pdf ...................................................................................... 16 Merriam-Webster Dictionary,
https://www.merriam-webster.com/dictionary/initiate ............................................................. 19 Office of Management & Budget, Circular No. A-130, Appendix II-10,
https://obamawhitehouse.archives.gov/sites/default/files/omb/assets/OMB/circulars/ a130/ a130revised.pdf ............................................................................................................... 18 U.S. Census Bureau, 2020 Census Operational Plan: A New Design for the 21st Century 97 (Dec. 2018), https://www2.census.gov/programs-surveys/decennial/2020/program-management/ planning-docs/2020-oper-plan4.pdf.......................................................................................... 22 U.S. Census Bureau, Archive of American Community Survey Questions, https://www.census.gov/programs-surveys/acs/methodology/questionnaire-archive.html ........ 5 U.S. Census Bureau, Measuring America: The Decennial Censuses From 1790 to 2000, https://www2.census.gov/library/publications/2002/dec/pol_02-ma.pdf ................................... 5 U.S. Census Bureau, Privacy Impact Assessment for the CEN08 Decennial Information Technology Divisions (DITD) (Sept. 27, 2018), http://www.osec.doc.gov/opog/privacy/Census%20PIAs/CEN08_PIA_SAOP_ Approved.pdf ............................................................................................................................ 18 U.S. Census Bureau, Questionnaires, https://www.census.gov/history/www/through_the_decades/questionnaires/............................ 5
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INTRODUCTION The E-Government Act of 2002 requires that Federal agencies publish a Privacy Impact Assessment (“PIA”), if practicable, before “initiating a new collection of information.” Plaintiff, the Electronic Privacy Information Center (“Plaintiff”) seeks an injunction against the Department of Commerce and the Census Bureau (“Defendants”) prohibiting them from taking further steps to implement a citizenship question on the 2020 Decennial Census until such time as they complete and make publicly available a PIA that specifically addresses the collection of citizenship information for each information technology system involved in the collecting and processing of respondent information. Plaintiff argues that the Census Bureau was required to publish a PIA addressing the inclusion of a citizenship question on the 2020 Decennial Census questionnaire as of March 26, 2018, the date that the Secretary of Commerce announced his decision to include that question on the 2020 Decennial Census. To begin, Plaintiff lacks standing. The inclusion of a citizenship question on the 2020 Decennial Census inflicts no cognizable harm on Plaintiff or its “members” (to the extent that individuals on Plaintiff’s advisory board qualify as members), and neither Plaintiff nor its “members” have a sufficient informational interest in compelling publication of an updated PIA specifically addressing the collection of citizenship data now, as opposed to later. That is particularly true because the relevant provision of the E-Government Act protects individuals “by requiring an agency to fully consider their privacy before collecting their personal information,” Elec. Privacy Info. Ctr. v. Presidential Advisory Comm’n on Election Integrity, 878 F.3d 371, 378 (D.C. Cir. 2017), not by creating a broad public right to information. Nor, as this Court has already noted, would an injunction enjoining the Census Bureau from including the citizenship question on the 2020 Decennial Census redress the alleged informational injury. Mem. Op., Elec. Privacy
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Info. Ctr. v. U.S. Dep’t of Commerce, __ F. Supp. 3d __, 2019 WL 498520, at *9 (D.D.C. Feb. 8, 2019), appeal filed, No. 19-5031 (D.C. Cir. Feb. 21, 2019).
Furthermore, as this Court has already correctly determined – Plaintiff’s claims fail on the merits. See id. at *8. Plaintiff’s lawsuit is premature because the Census Bureau’s obligation to complete, and if practicable, publish an updated PIA specifically addressing the inclusion of a citizenship question on the 2020 Decennial Census has not yet ripened. The obligation to complete and publish, if practicable, a PIA attaches only once the agency “initiat[es] a new collection of information.” E-Government Act, Pub. L. 107-347, 116 Stat. 2899 (2002), § 208(b)(1)(A)(ii). As this Court held, this phrase “initiating a new collection of information,” means “to require at least one instance of ‘obtaining, causing to be obtained, soliciting, or requiring the disclosure . . . of facts or opinions.” Mem. Op. at 17, 2019 WL 498520, at *8 (quoting 44 U.S.C. § 3502(3)(A)). “This interpretation is fatal to the plaintiff’s [Administrative Procedure Act (“APA”)] claims. [Defendants] did not act contrary to the E-Government Act by deciding to collect citizenship data before conducting, reviewing, or releasing a PIA specifically addressing the decision to reinstate a citizenship question on the 2020 Decennial Census. See 5 U.S.C. § 706(2). Nor have the Defendants ‘unlawfully withheld’ agency action by declining to modify their existing PIA earlier required by the statute. See id. § 706(1).” Id. Accordingly, and following its earlier, correct, reasoning, this Court should dismiss Plaintiff’s Complaint in its entirety.
BACKGROUND I. STATUTORY BACKGROUND.
The E-Government Act of 2002, Pub. L. 107-347, 116 Stat. 2899 (2002), codified at 44 U.S.C. § 3501 note (hereinafter “E-Government Act” or “E-Gov. Act”), requires Federal agencies to have performed and, if practicable, publish a Privacy Impact Assessment (“PIA”) when
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“developing or procuring information technology that collects, maintains, or disseminates information that is in an identifiable form,” or, consistent with the Paperwork Reduction Act, 44 U.S.C. § 3501, et seq., when “initiating a new collection of information” that “will be collected, maintained, or disseminated using information technology” and “includes any information in an identifiable form permitting the physical or online contacting of a specific individual.” E-Gov. Act § 208(b)(1)(A)(i), (ii); see also Office of Management and Budget, Memorandum M-03-22, OMB Guidance for Implementing the Privacy Provisions of the E-Government Act. “The purpose of this [requirement] is to ensure sufficient protections for the privacy of personal information as agencies implement citizen-centered electronic Government.” E-Gov. Act, § 208(a).
Among other things, the PIA is to address “what information is to be collected,” “why the information is being collected,” “the intended use of the agency of the information,” “with whom the information will be shared,” “what notice or opportunities for consent would be provided to individuals regarding what information is collected and how that information is shared,” “how the information will be secured,” and “whether a system of records is being created under” 5 U.S.C. § 552a (commonly referred to as the Privacy Act). E-Gov. Act § 208(b)(2)(B)(ii). After completion of the PIA, and before “initiating a new collection of information,” the agency is directed to, “if practicable, . . . make the privacy impact assessment publicly available through the website of the agency, publication in the Federal Register, or other means.” Id. § 208(b)(1)(B)(iii) (emphasis added).
The E-Government Act incorporates several provisions of the Paperwork Reduction Act, including the Act’s definitions. E-Gov. Act § 201 (“Except as otherwise provided, in this title the definitions under sections 3502 and 3601 of title 44, United States Code, shall apply.”). The Paperwork Reduction Act, in turn, requires Federal agencies seeking to collect information to first
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publish a notice in the Federal Register and allow 60 days for submission of comments. 44 U.S.C. § 3506(c)(2)(A); see also id. § 3502(3) (defining “collection of information”). After considering the submitted comments, the agency must then submit its information collection request to the Director of the Office of Management and Budget (“OMB”) for review. See id. § 3507(c)(3). The agency must also publish a second notice in the Federal Register to inform the public that the information collection request has been submitted to OMB and that additional comments may be directed to OMB. Id. § 3507(a)(1)(D). OMB must allow 30 days for public comment prior to approving or disapproving an information collection request. Id. § 3507(b), (e)(1). The EGovernment Act does not require a similar notice-and-comment process. II. FACTUAL BACKGROUND.
The Constitution requires that an “actual Enumeration” of the population be conducted every ten years in order to allocate representatives in Congress among the States, and vests Congress with the authority to conduct that census “in such Manner as they shall by Law direct.” U.S. Const. art. I, § 2, cl. 3. The Census Act, 13 U.S.C. § 1 et seq., delegates to the Secretary of Commerce the responsibility to conduct the decennial census “in such form and content as he may determine,” and “authorize[s] [him] to obtain such other census information as necessary.” Id. § 141(a). The Census Bureau assists the Secretary in performing this duty. See id. §§ 2, 4. The Act directs that the Secretary “shall prepare questionnaires, and shall determine the inquiries, and the number, form, and subdivisions thereof, for the statistics, surveys, and censuses provided for in this title.” 13 U.S.C. § 5. Nothing in the Act directs the contents of the questions included on the decennial census.
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On March 26, 2018, the Secretary of Commerce announced his decision to include a citizenship question on the 2020 Decennial Census questionnaire.1 See Declaration of Robin J.
Bachman, Chief Privacy Officer, United States Census Bureau (“Bachman Decl.”), ¶ 10, ECF No.
12-2. At the time of the announcement, pursuant to Section 208 of the E-Government Act, the
Census Bureau was in its annual process of reviewing its published Privacy Impact Assessment of
a primary information technology system used to administer the decennial census – CEN08. See
Bachman Decl. ¶¶ 3, 9, 10. CEN08 is owned by the Decennial Information Technology Division
(“DITD”) and is used to manage the development and implementation of a number of decennial
census applications, including the Census Schedule A Human Resources Recruiting and Payroll
Systems (“C-SHaRPS”), the Third-Party Fingerprinting System, and the Control and Response
Data System (“CaRDS”). Id. ¶ 3. These applications contain several categories of information,
including hiring and personnel data and data collected from decennial census respondents. Id.
CEN08 shares information with several other of the Census Bureau’s information technology
systems, such as CEN21 (Human Resources Application), CEN05 (Field Systems Major
Application System), CEN11 (Demographic Census, Surveys, and Special Processing), and
CEN13 (Center for Economic Studies). Id. ¶ 14. CEN18 (Enterprise Applications) is the
1 With the exception of 1840, decennial censuses from 1820 to 1880 asked for citizenship or birthplace information in some form, and decennial censuses from 1890 through 1950 specifically requested citizenship information. See U.S. Census Bureau, Measuring America: The Decennial Censuses From 1790 to 2000, at 6-13, https://www2.census.gov/library/ publications/2002/dec/pol_02-ma.pdf (“Measuring America”). Decennial censuses from 1960 to 2000 asked a portion of the population questions about the respondent’s birthplace or citizenship. Id. at 72-73, 78, 91-92; U.S. Census Bureau, Questionnaires, https://www.census.gov/ history/www/through_the_decades/questionnaires/. Beginning in 2005, the Census Bureau began collecting citizenship information through the American Community Survey (“ACS”), which is sent yearly to about one in 38 households. See U.S. Census Bureau, Archive of American Community Survey Questions, https://www.census.gov/programs-surveys/acs/methodology/ questionnaire-archive.html (noting citizenship questions on every ACS questionnaire).
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information technology system that facilitates the passing of information from CEN08 to these other information technology systems. Id. The Census Bureau updates its PIAs on a regular basis, and will continue to do so. See id. ¶¶ 9, 15. Current versions of the PIAs are published on Defendants’ websites. See, e.g. U.S. Census Bureau, Privacy Impact Assessments (PIAs) and Privacy Threshold Analysis (PTAs), http://www.osec.doc.gov/opog/privacy/Census-pias.html?#.
During the annual privacy review of CEN08, the Census Bureau updated the CEN08 PIA to reflect the Census Bureau’s intent to include citizenship status among the personally identifying information (“PII”) to be collected during the 2020 Decennial Census and its then assessment of the confidentiality risk level of collecting PII. Bachman Decl. ¶ 10. The updated PIA was published on Commerce and the Census Bureau’s websites on June 26, 2018. Id. ¶ 10 & Ex. A. The Census Bureau also updated the PIAs for CEN05, CEN11, CEN13, CEN18, and CEN21 during this time and likewise published the updated assessments on its website. See id. ¶¶ 9, 15.
The Census Bureau further updated the PIA for CEN08 in July 2018 to reflect employment recruiting and hiring activities for the 2020 Decennial Census. Bachman Decl. ¶ 13 & Ex. B. These updates focused on the collection of fingerprints and other personnel information during the application and hiring process for potential Census Bureau employees. Id. The updated PIA noted that the fingerprint and personnel information would be shared with other Federal agencies for the purposes of conducting background investigations and administering human resource programs, such as payroll. Id. The Census Bureau is currently in the process of updating the CEN08 PIA as it continues to refine its operations for the 2020 Decennial Census. See id. ¶¶ 6, 9. The PIAs for CEN05, CEN11, CEN13, and CEN18 are also currently under review to determine whether updates are warranted. See id. ¶ 15.
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Decennial census respondent information collected through CEN08 and processed by or stored in other Census Bureau information technology systems, such as CEN05 and CEN11, is collected pursuant to the proscriptions of Title 13 of the United States Code, which requires that the Census Bureau maintain the confidentiality of the information it collects. Bachman Decl. ¶ 14. Indeed, Title 13 mandates that the Census Bureau only use the respondent information it collects for statistical purposes and expressly prohibits both the publication of personally identifying information and the use of collected information to a respondent’s detriment. Id. ¶¶ 14, 16.
Plaintiff filed this lawsuit on November 20, 2018. It alleges that Defendants have violated the APA, 5 U.S.C. §§ 706(1), 706(2)(A), (C), by failing to conduct and publish Privacy Impact Assessments by March 26, 2018, that specifically address the collection of citizenship information for the information technology (“IT”) systems that will be collecting, processing, and storing 2020 Decennial Census respondent information, as required by Section 208 the E-Government. See Compl. ¶¶ 47, 49, 53-62, 65, ECF No. 1. Plaintiff seeks an order “suspend[ing] and revok[ing]” Defendants’ decision to collect citizenship data through the 2020 Census until such time as Defendants have “conducted, reviewed, and published the full and complete Privacy Impact Assessments required by [the privacy provisions] of [the] E-Government Act of 2002.” Compl., Request for Relief ¶ B. Plaintiff also seeks an order (1) expressly removing the citizenship question from the 2020 Census, (2) enjoining Defendants from “any action in furtherance of Defendants’ plan to collect citizenship data through the 2020 Census until” they have completed and published the Privacy Impact Assessments required by the privacy provisions of the EGovernment Act of 2002, and (3) requiring Defendants to conduct, review, and publish the full and complete Privacy Impact Assessments. Id. ¶¶ C-E.
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Nearly two months later, on January 18, 2019, Plaintiff moved for a preliminary injunction asserting it is entitled to such extraordinary relief because “the Census Bureau’s failure to publish legally required privacy impact assessments causes [it] irreparable harm and conflicts with the public interest.” Mem. in Supp of Pl.’s Mot. for a Prelim Inj, at 15, ECF No. 8-1 (“Pl.’s Prelim. Inj. Mem”). Plaintiff sought an order “preventing Defendants . . . from (1) implementing the [] March 26, 2018 decision to add a citizenship question to the 2020 Census, and (2) otherwise initiating any collection of citizenship status information that would be obtained through the 2020 Census” until final adjudication of the merits of its claims. Pl’s. Mot. for a Prelim. Inj., at 1, ECF No. 8. On February 8, 2019, this Court denied Plaintiff’s motion, concluding, inter alia, that “EPIC is . . . unlikely to succeed on the merits.” Mem. Op.,2019 WL 498520, at *8.
STANDARD OF REVIEW Motions brought pursuant to Federal Rule of Civil Procedure 12(b)(1) challenge a district court’s jurisdiction over the action. See Fed. R. Civ. P. 12(b)(1). In reviewing a motion to dismiss under Rule 12(b)(1), a court is guided by the principle that “[f]ederal courts are courts of limited jurisdiction.” Kokkonen v. Guardian Life Ins. Co. of Am., 511 U.S. 375, 377 (1994). A party claiming subject matter jurisdiction bears the burden of demonstrating that such jurisdiction exists. Khadr v. United States, 529 F.3d 1112, 1115 (D.C. Cir. 2008). Though a court must give the plaintiff the benefit of inferences that can be derived from the facts alleged in the complaint, Barr v. Clinton, 370 F.3d 1196, 1199 (D.C. Cir. 2004), “the Court need not accept factual inferences drawn by plaintiffs if those inferences are not supported by facts alleged in the complaint, nor must the Court accept plaintiffs’ legal conclusions.” Speelman v. United States, 461 F. Supp. 2d 71, 73 (D.D.C. 2006). When a defendant raises an issue of subject matter jurisdiction under Rule 12(b)(1), the Court must resolve the jurisdictional issue before it proceeds to the merits of the
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plaintiff’s claims. See, e.g., Sinochem Int’l Co. v. Malay Int’l Shipping Corp., 549 U.S. 422, 43031 (2007).
To survive a motion to dismiss under Federal Rule of Civil Procedure 12(b)(6), “a complaint must contain sufficient factual matter, accepted as true, to ‘state a claim to relief that is plausible on its face.’” Ashcroft v. Iqbal, 556 U.S. 662, 678 (2009) (quoting Bell Atl. Corp. v. Twombly, 550 U.S. 544, 570 (2007)). In reviewing a motion to dismiss under Rule 12(b)(6), the Court will ordinarily “accept as true all of the factual allegations contained in the complaint,” Atherton v. D.C. Office of the Mayor, 567 F.3d 672, 681 (D.C. Cir. 2009) (citation and quotations omitted), and construe it in the plaintiff’s favor. Porter v. CIA, 778 F. Supp. 2d 60, 65 (D.D.C. 2011). However, “the tenet that a court must accept as true all of the allegations contained in a complaint is inapplicable to legal conclusions” or “[t]hreadbare recitals of the elements of a cause of action, supported by mere conclusory statements.” Iqbal, 556 U.S. at 678.
ARGUMENT I. PLAINTIFF LACKS STANDING.
Plaintiff seeks broad relief in this lawsuit. Plaintiff asks this Court to, inter alia, “[h]old unlawful and set aside the Defendants’ decision to collect citizenship data through the 2020 Census, Defendants’ placement of a citizenship question on the 2020 Census, and Defendants’ initiation of the citizenship data collection process,” Compl. Req. Relief ¶ A, to “suspend and revoke their decision [to] collect citizenship data,” and to “revoke and remove the citizenship question from the 2020 Census” until Defendants have conducted another PIA specifically addressing the collection of citizenship data, id. ¶¶ B-C, to “cease and desist from any action in furtherance of Defendant’s plan to collect citizenship data” until Defendants have conducted another PIA specifically addressing the collection of citizenship data, id. ¶ D, and then, perhaps
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for completeness, to “conduct, review, and publish” a PIA for the collection of citizenship data, id. ¶ E. Plaintiff lacks Article III standing necessary to justify this relief.
The doctrine of standing, an essential aspect of the Article III case-or-controversy requirement, demands that a plaintiff have “a personal stake in the outcome of the controversy [so] as to warrant his invocation of federal-court jurisdiction[.]” Warth v. Seldin, 422 U.S. 490, 498 (1975) (citation omitted). At its “irreducible constitutional minimum,” the standing doctrine requires a plaintiff, as the party invoking the Court’s jurisdiction, to establish three elements: (1)a concrete and particularized injury-in-fact, either actual or imminent, (2) a causal connection between the injury and defendants’ challenged conduct, and (3) a likelihood that the injury suffered will be redressed by a favorable decision. Lujan v. Defs. of Wildlife, 504 U.S. 555, 560-61 (1992) (citations omitted). Facts demonstrating each of these elements “must affirmatively appear in the record” and “cannot be inferred argumentatively from averments in the [plaintiff’s] pleadings.” FW/PBS, Inc. v. City of Dallas, 493 U.S. 215, 231 (1990) (citation omitted); see also Sierra Club v. EPA, 292 F.3d 895, 900 (D.C. Cir. 2002). “‘[S]tanding is not dispensed in gross’[,] . . . [t]o the contrary, ‘a plaintiff must demonstrate standing for each claim he seeks to press and for each form of relief that is sought.’” Town of Chester v. Laroe Estates, Inc., 137 S. Ct. 1645, 1650 (2017) (quoting Davis v. FEC, 554 U.S. 724, 734 (2008)).
An organization can assert standing either on its own behalf (organizational standing) or on behalf of its members (associational, sometimes called representational, standing). See Nat’l Treasury Emps. Union v. United States, 101 F.3d 1423, 1427 (D.C. Cir. 1996)). The D.C. Circuit has explicitly held that Plaintiff lacks organizational standing to seek relief under section 208 of the E-Government Act. See EPIC v. PACEI II, 878 F.3d at 378-379. Consequently, Plaintiff here tries to justify standing under a representational standing theory. As we discuss at greater length
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below, Plaintiff cannot invoke representational standing because Plaintiff is not a membership organization. See infra at 15-17.
Even assuming, however, that Plaintiff was properly described as a membership organization, it has not established that any of its claimed “members”—that is, the individuals on its advisory board—would have “standing to sue in her or his own right.” Am. Library Ass’n v. FCC, 401 F.3d 489, 492 (D.C. Cir. 2005).
Plaintiff suggests that the addition of a citizenship question on the 2020 Decennial Census questionnaire “presents unique threats to privacy” and “personal security.” Compl. ¶ 36. But any claim that the inclusion of a citizenship question jeopardizes the privacy interests of Plaintiff’s advisory board would be “pure speculation,” as the District Court for the Southern District of New York recently concluded in holding that privacy interests did not provide standing to challenge the inclusion of the citizenship question. New York v. U.S. Dep’t of Commerce, 351 F. Supp. 3d 502, 619 (S.D.N.Y. 2019).2 As that court explained, any suggestion that individuals will be injured by the Census Bureau’s potential misuse of data collected during the 2020 Decennial Census, see, e.g., Compl. ¶ 40, is flatly at odds with the governing statute. Pursuant to Title 13 of the United States Code, “it would be illegal for the Department of Commerce to ‘make any publication whereby the data furnished by any particular establishment or individual . . . can be identified.” New York, 351 F. Supp. 3d at 618-619 (quoting 13 U.S.C. § 9(a)(2)). Accordingly, “the Census Bureau will apply ‘disclosure avoidance techniques’ to any data to ensure that information concerning particular respondents is not identifiable.” Id. at 619. Moreover, the statute precludes
2 The court found that the plaintiffs had standing on other grounds and held that the inclusion of the question was arbitrary and capricious. See New York, 351 F. Supp. 3d at 606, 647. The Supreme Court granted certiorari before judgment and will hear the case this term. See 2019 WL 331100 (U.S. Feb. 15, 2019).
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Defendants from “us[ing]” census information “for any purpose other than the statistical purposes for which it is supplied,” and even where the Secretary of Commerce provides other government agencies with aggregate statistical information, the information cannot “be used to the detriment of any respondent or other person to whom such information relates.” 13 U.S.C. §§ 8(c), 9(a)(1).
Any speculation that Plaintiff may offer to the contrary, cf., e.g., Compl. ¶ 40, is just that – speculation – and such speculative fears are “insufficient to create standing.” Clapper v. Amnesty Int’l USA, 568 U.S. 398, 417 (2013); see also N.Y. v. U.S. Dep’t of Commerce, 351 F. Supp. 3d at 619 (“But it is pure speculation to suggest that the Census Bureau will not comply with its legal obligations to ensure the privacy of respondents’ data . . . .”). None of Plaintiff’s allegations in this case cast doubt on the correctness of the New York court’s ruling, which it issued after an eight-day bench trial. See id. at 516. Plaintiff, therefore, lacks standing to challenge the underlying agency action here (the addition of a citizenship question to the 2020 Decennial Census), and a theory of injury to privacy accordingly cannot be the basis for an injunction prohibiting Defendants from taking further steps to implement a citizenship question on the 2020 Decennial Census.
Unable to identify any cognizable threat to a privacy interest, Plaintiff alleges that its advisory board members and Board of Directors have an abstract informational interest in reviewing a PIA that specifically addresses the collection of citizenship data – a PIA Plaintiff contends Defendants were required to publish before March 26, 2018. But as this Court has already noted, a theory of informational injury likewise would not entitle Plaintiff to most of the relief it seeks – orders enjoining, suspending, revoking, removing, or ceasing the planning of the citizenship question until such time as Defendants have conducted a PIA that specifically addresses the collection of citizenship data. See Mem. Op., 2019 WL 498520, at *9. The Census Bureau has explained that it will conduct at least one more annual review of the relevant PIAs before
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initiating a collection of information for the 2020 Decennial Census. See Bachman Decl. ¶¶ 9, 15. Whether it does so before or after it distributes census forms has no bearing whatsoever on Plaintiff’s claimed informational interest, and—as this Court has already held—an order “‘halting’ the ‘collecting of . . . data’ cannot redress an informational injury under the E-Government Act.’” Mem. Op., 2019 WL 498520, at *9 (quoting EPIC v. PACEI II, 878 F.3d at 380).
Because the only question here is one of timing, the Court need not determine whether Plaintiff’s claim of informational injury would provide standing if the Census Bureau had determined that it would not revise the relevant PIAs prior to initiating a collection of information for the 2020 Decennial Census. “To carry its burden of demonstrating a ‘sufficiently concrete and particularized informational injury,’ [] plaintiff must show that [at least one of its members] “‘(1) [] has been deprived of information that, on [his or her] interpretation, a statute requires the government or a third party to disclose [], and (2) [] suffers, by being denied access to that information, the type of harm Congress sought to prevent by requiring disclosure.’” EPIC v. PACEI II, 878 F.3d at 378 (quoting Friends of Animals v. Jewell, 828 F.3d 989, 992 (D.C. Cir. 2016)). An asserted informational injury to Plaintiff’s “members” resulting from alleged delay in publishing an updated PIA is not the type of harm that Congress sought to avert when it enacted section 208. That provision, as the D.C. Circuit explained, “protect[s] individuals . . . by requiring an agency to fully consider their privacy before collecting their personal information.” Id. (second emphasis added); see also E-Gov. Act § 208(a), (establishing that the purpose of section 208 “is to ensure sufficient protections for the privacy of personal information as agencies implement citizen-centered electronic Government”).
While other provisions of the E-Government Act make express that their purpose is to increase transparency, see E-Gov. Act §§ 204(a)(1), 207(a), section 208 does not create a
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freestanding right to information. It instead protects individual privacy by requiring that agencies improve their internal decisionmaking by conducting and internally reviewing Privacy Impact Assessments. The requirement that an agency make the Privacy Impact Assessment public, “if practicable,” “after completion of” that internal review does not create an informational right in members of the public whose privacy is not, as explained above, threatened. See supra at 11-12 (explaining that inclusion of the citizenship question inflicts no cognizable privacy harm on Plaintiff’s purported “members”); see also Lujan, 504 U.S. at 572 & n.7 (explaining that a plaintiff has standing to “enforce a procedural requirement the disregard of which could impair a separate concrete interest of theirs” but that “persons who have no concrete interests affected” have no such procedural right).
Indeed, comparing the E-Government Act to other statutes that courts have found sufficient for informational standing illustrates the different purposes of disclosure between statutes that provide for informational standing and those, like the Act, that do not. The Federal Election Campaign Act, for example, was designed to disclose information about political contributors and nondisclosure was the type of injury that Act was designed to remedy. See Fed. Election Comm’n v. Akins, 524 U.S. 11, 20 (1998). Similarly, the Freedom of Information Act was designed to afford citizens an opportunity to “to be informed about ‘what their government is up to,’” Dep’t of Justice v. Reporters Comm. for Freedom of Press, 489 U.S. 749, 773 (1989), and an agency’s failure to comply with the Act’s disclosure requirements constitutes an injury sufficient to confer standing, Pub. Citizen v. Dep’t of Justice, 491 U.S. 440, 449-50 (1989). And the Federal Advisory Committee Act was likewise designed to allow members of the public to scrutinize the activities of advisory committees, and, therefore, failure to comply with its informational disclosure provision could create a cognizable injury in fact. See id. Other statutes, such as section 10(c) of
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the Endangered Species Act, have been held to create informational standing because they specifically “invite the submission from interested parties” after a notice has been published, so that the public may “meaningfully participate in the Act’s permitting process.” Friends of Animals v. Jewell, 824 F.3d 1033, 1041 (D.C. Cir. 2016). Here, by contrast, the E-Government Act has no post-publication public participation requirement nor is it primarily designed to foster public disclosure; instead, it is an internal decisionmaking statute that is of a different sort than that of the sort that normally supports an informational standing claim. Cf. Mem. Op., 2019 WL 498520, at *8 (“Congress’s focus on ensuring ‘protections’ when agencies ‘implement’ electronic Government shows that § 208’s provisions – including the requirement to prepare PIAs – were not meant to discourage agencies from collecting personal information but rather to ensure that they have sufficient protections in place before they do.”).
Any alleged informational injury is particularly remote here, where the dispute is simply one of timing: Plaintiff certainly cannot show that, if its advisory board members and Board of Directors must wait some additional weeks or months to review an updated PIA specifically addressing the collection of citizenship data for the 2020 Decennial Census, they will “suffer[] . . . the type of harm Congress sought to prevent by requiring disclosure” in section 208—which is, again, a provision aimed at improving internal agency decisionmaking that on its face imposes no timing requirements whatsoever for publication. EPIC v. PACEI II, 878 F.3d at 378 (quoting Friends of Animals v. Jewell, 828 F.3d 989, 992 (D.C. Cir. 2016)).
Finally, although the Court need not reach the issue, Plaintiff is not a membership organization or its functional equivalent and thus cannot proceed on a theory of representational standing. Plaintiff advanced its representational theory of standing in bringing a claim for relief pursuant to section 208 of the E-Government Act in Electronic Privacy Information Center v.
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Presidential Advisory Commission on Election Integrity. The district court in that case determined that Plaintiff had failed to demonstrate it had representational standing to bring its claim because, inter alia, it was neither a membership organization nor the functional equivalent of a membership organization. Elec. Privacy Info. Ctr. v. Presidential Advisory Comm’n on Election Integrity (“EPIC v. PACEI I”), 266 F. Supp. 3d 297, 307-09 (D.D.C. 2017). Plaintiff subsequently abandoned any theory of representational standing on appeal in that case. See EPIC v. PACEI II, 878 F.3d at 381.
Before bringing this lawsuit, Plaintiff amended its Articles of Incorporation and Bylaws to refer to the individuals on its advisory board and Board of Directors as “members” and to require that they begin paying some unspecified amount of “dues.” See Compl. ¶ 10; see also EPIC Bylaws §§ 2.02, 5.02-05, https://www.epic.org/epic/bylaws.pdf. But Plaintiff cannot circumvent its lack of organizational standing by simply renaming its board members and charging them a fee. Plaintiff continues to lack the indicia of a membership organization or its functional equivalent. See Fund Democracy, LLC v. SEC, 278 F.3d 21, 25 (D.C. Cir. 2002). Plaintiff does not “serve[] a specialized segment of the . . . community,” represent individuals with “all of the indicia of membership in an organization,” or have fortunes “closely tied to those of its constituency.” Id. at 26. To the contrary, notwithstanding its recent decision to begin charging its board members a fee, Plaintiff continues to assert on its website that its primary objective is to serve the public at large by “focus[ing] public attention on emerging privacy and civil liberties issues and . . . protect[ing] privacy, freedom of expression, and democratic values in the information age.” As a result, Plaintiff asserts that it “ha[s] no clients, no customers, and no shareholders.” Elec. Privacy Info. Ctr., About, https://www.epic.org/epic/about.html (last visited Mar. 4, 2019). Unlike the “members” of a genuine membership organization, whose “fortunes . . . [are] closely tied to those
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of [the organization],” Fund Democracy, 278 F.3d at 26, individuals on Plaintiff’s advisory board and Board of Directors are no more affected by the organization’s activities than other members of the public. See, e.g., Am. Legal Found. v. FCC, 808 F.2d 84, 89-90 (D.C. Cir. 1987) (“With its broadly defined mission as a ‘media watchdog,’ ALF serves no discrete, stable group of persons with a definable set of common interests.”).
In any event, as discussed above, even if the Court were to conclude Plaintiff has transformed itself into a membership organization that represents the interests of its advisory board and Board of Directors, none of those individuals have standing to sue on their own behalf, for the reasons discussed above – section 208 does not confer informational standing. See Ass’n of Flight Attendants-CWA, AFL-CIO v. U.S. Dep’t of Transp., 564 F.3d 462, 464 (D.C. Cir. 2009) (observing that to establish representational standing, a plaintiff must show, among other things, that “its members would otherwise have standing to sue in their own right”). II. PLAINTIFF FAILS TO STATE A CLAIM.
Section 208(b) of the E-Government Act, requires an agency to complete, and, if practicable, publish, a Privacy Impact Assessment before “initiating a new collection of information.” E-Gov. Act §§ 208(b)(1)(A)(ii), (b)(1)(B). Plaintiff argues that the Census Bureau was required to have published an assessment that specifically addresses the collection of citizenship data as of March 26, 2018, the date that the Secretary of Commerce “ordered the [reinstatement] of a citizenship question to the 2020 Census,” because the Secretary’s decision, it states, “initiat[ed] a new collection of citizenship status information.”3 Pl.’s Prelim. Inj. Mem. at
3 The E-Government Act also requires an agency to complete a PIA before “developing or procuring information technology that collects, maintains, or disseminates information that is in an identifiable form.” E-Gov. Act § 208(b)(1)(A)(i). Plaintiff’s complaint, however, only alleges violation of the E-Government Act’s “initiating a new collection of information” requirement, see
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19; Compl. ¶ 63. Plaintiff’s claim utterly fails as a matter of statutory construction. The EGovernment Act only requires that the Census Bureau complete and, if practicable, publish a PIA before initiating a new collection of information within the meaning of that Act – and because the Bureau has not yet started collecting citizenship information from the public for the 2020 Decennial Census, it has not violated the E-Government Act.4 Accordingly, as this Court has already concluded, Plaintiff cannot state a claim.
One initial note about terminology. The E-Government Act refers to “Privacy Impact Assessments” to mean both the formal notice that must, if practicable, be published on the agency’s website, in the Federal Register, or made publicly available by other means, see E-Gov. Act §§ 208 (b)(1)(B), (c), as well as the analysis that the agency conducts on an ongoing basis to ensure the continued adequacy of its IT systems. See Office of Management & Budget, Circular No. A-130, Appendix II-10 (“A PIA is an analysis of how PII is handled to ensure that handling conforms to applicable privacy requirements, determine the privacy risks associated with an information system or activity, and evaluate ways to mitigate the privacy risks. A PIA is both an analysis and a formal document detailing the process and the outcome of the analysis.”), https://obamawhitehouse.archives.gov/sites/default/files/omb/assets/OMB/circulars/a130/ a130revised.pdf; see also Bachman Decl. ¶ 4.

Compl. ¶¶ 14, 50, 65, 72; see also Pl.’s Prelim. Inj. Mem. at 19-21, and so only that requirement is at issue in this case.

4 Furthermore, the Census Bureau had a published PIA in place at the time Plaintiff initiated this

lawsuit which did reference the Bureau’s intent to collect citizenship data. See U.S. Census Bureau,

Privacy Impact Assessment for the CEN08 Decennial Information Technology Divisions (DITD)

(Sept.

27,

2018),

http://www.osec.doc.gov/opog/privacy/Census%20PIAs/

CEN08_PIA_SAOP_Approved.pdf.

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This case is only about the timing of formal written notification about the outcome of the PIA process, as Plaintiff itself makes clear. See Compl. ¶¶ 50-51, 69, 75; see also Pl.’s Prelim. Inj Mem. at 38 (claiming that its members have “sought and were denied information which the Government is required to disclose under section 208 of the E-Government Act,” and basing its sole claim to informational standing on that purported non-disclosure). The agency must satisfy that obligation, in turn, before “initiating a new collection of information.” E-Gov. Act §§ 208(b)(1)(A)(ii), (b)(1)(B). Accordingly, unless otherwise stated, this brief’s references to a “Privacy Impact Assessment” or a “PIA” refer to the formal document that must, if practicable, be published or otherwise made publicly available before the agency may collect information.
1. The Census Bureau Has Not “Initiated a New Collection of Information.” “As in any statutory construction case, ‘[the court] start[s], of course, with the statutory text,’ and proceed[s] from that understanding that ‘[u]nless otherwise defined, statutory terms are generally interpreted in accordance with their ordinary meaning.’” Sebelius v. Cloer, 569 U.S. 369, 376 (2013) (quoting BP Am. Prod. Co. v. Burton, 549 U.S. 84, 91 (2006)). Here, the statutory trigger for the E-Government Act is whether an agency is “initiating a new collection of information.” E-Gov. Act § 208(b)(1)(A)(ii). If it is, the agency must first have conducted and, if practicable, made public a PIA. If it is not, the agency’s obligations under the Act will not have yet ripened. Here, as Plaintiff previously acknowledged, the Census Bureau has not yet asked the public to respond to the 2020 Decennial Census questionnaire and, thus, has not “initiat[ed] a new collection of information.” The E-Government Act does not define the term “initiating,” although, as Plaintiff recognized, the common definition of “initiate” means “[c]ommence” or “start.” Pl.’s Prelim. Inj. Mem. at 19 (quoting Kelso v. U.S. Dep’t of State, 13 F. Supp. 2d 1, 9 (D.D.C. 1998)); see also Merriam-Webster Dictionary, https://www.merriam-webster.com/dictionary/initiate (“to
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cause or facilitate the beginning of: set going”); Mem. Op., 2019 WL 498520, at *4 (additional definitions). “Initiating,” therefore, means something akin to “starting.” See Mem. Op., 2019 WL 498529, at *4 (“These definitions share a focus on the beginning, starting, or commencing of a course of conduct.”).
The term “collection of information,” E-Gov. Act § 208(b)(1)(A)(ii) however, is specifically defined in the statute. The E-Government Act provides that “in this title the definition under sections 3502 and 3601 of title 44, United States Code, shall apply.” E-Gov. Act § 201. Section 3502 of Title 44, in turn, defines “collection of information” to “mean[] the obtaining, causing to be obtained, soliciting, or requiring the disclosure to third parties or the public, of facts or opinions by or for an agency, regardless of form of format, calling for [certain quantities or types of information].” 44 U.S.C. § 3502(3)(A). Putting these two definitions together, then, an agency must have conducted and, if practicable, published a PIA before (1) starting (2) the obtaining or soliciting of information from the public – or, said differently, before it actually starts to ask the public to submit Census information. That has not occurred yet – nor does Plaintiff state that it has in its papers – and therefore the Census Bureau has not “initiat[ed] a new collection of information.” See also Mem. Op., 2019 WL 498520, at *4 (“While Secretary Ross decided to collect citizenship information . . . the defendants have yet to actually begin obtaining, soliciting, or requiring the disclosure of any citizenship data.”).
This is the best reading of the statute. Notably, the use of the present tense gerunds in the definition of “collection of information” (e.g., “obtaining” or “causing to be obtained”), indicates that the collection is a present-tense activity, in other words, that the collection of information occurs when the agency actually is soliciting information from the public, not merely when it is planning to collect that information in the future. And because the verb “initiating” modifies the
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present tense gerunds that make up “collection of information,” the statute on its face contemplates that the agency must complete its analysis and, if practicable, publish the PIA before it starts to obtain information from the public – or before it starts to mail or distribute census forms to individuals.
This reading accords with how the phrase “initiating” is used in other legal contexts. As this Court has observed, “[c]ourts routinely use the phrase ‘initiating an action’ to refer to the filing of the complaint. And it would be unusual – if not downright misleading – to claim to have ‘initiated’ a lawsuit when in fact one had merely decided which claims to allege in the complaint.” Mem. Op., 2019 WL 498520, at *5 (citations omitted). Moreover, had Congress intended to require a PIA before “planning” or “providing for” a new collection of information, it could have done so. See id. The fact that it chose not to “strongly supports rejecting” such an interpretation here. Id. (quoting Knight v. Comm’r, 552 U.S. 181, 188 (2008)).
This reading is also consistent with how courts and other agencies have interpreted Section 208 – as a requirement to complete and, if practicable, publish a PIA before starting to solicit information from the public. The D.C. Circuit has stated as much. See EPIC v. PACEI II, 878 F.3d at 378 (“As we read it, the provision [Section 208] is intended to protect individuals . . . by requiring an agency to fully consider their privacy before collecting their personal information.”) (second emphasis added). Additionally, the Office of Management and Budget (“OMB”), which administers the Paperwork Reduction Act from which the E-Government Act borrows its definition section, similarly defines “[c]ollection of information” to mean “the obtaining, causing to be obtained, soliciting, or requiring the disclosure . . . of information.” 5 C.F.R. § 1320.3(c). Applying a common-sense reading to this definition, the Census Bureau must complete and, if practicable, publish a PIA before it begins obtaining, soliciting, or requiring the disclosure of
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information from a third party; in other words, before it sends out a document requesting a Census response from a member of the public.
Plaintiff argued in support of its motion for a preliminary injunction and in its complaint that the Census Bureau began “initiating a new collection of information” when the Secretary of Commerce made the decision to include a citizenship question on the 2020 Decennial Census questionnaire on March 26, 2018. Pl.’s Prelim. Inj. Mem. at 20; see also Compl. ¶¶ 50-51, 63. But there is no basis in the E-Government Act’s text for such a construction. The Census Bureau has not asked any member of the public to submit that information; indeed, as Plaintiff has previously acknowledged, the Census Bureau has not even begun printing, addressing, or mailing census forms, and will not begin the first of these steps (printing) until June 2019. See U.S. Census Bureau, 2020 Census Operational Plan: A New Design for the 21st Century 97 (Dec. 2018), https://www2.census.gov/programs-surveys/decennial/2020/program-management/planningdocs/2020-oper-plan4.pdf; Pl.’s Prelim. Inj. Mem. at 31. And, of course, the Census Bureau will not actually solicit responses to any questions until later. Plaintiff’s argument, therefore, is the same as saying that a person has “commenced the soliciting” of a wedding RSVP as soon as a couple decides what information to include in the wedding invitation, but before the invitation is even printed, much less sent. That reading belies common sense – a person “commences the solicitation” of the wedding RSVP when they send the invitation. So too here: the Bureau “commences the solicitation” of the response to the decennial census when it mails the form or asks the question, not when the Secretary decided what questions should be included in the questionnaire. See also Mem. Op., 2019 WL 498520, at *4 (“To build on the wedding analogy, a couple does not ‘initiate’ their marriage by getting engaged or choosing a wedding date, even if those actions ordinarily serve as a final – and binding – decision to tie the knot. As each subsequent
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anniversary celebration makes clear, they will not have ‘initiated’ their marriage until the wedding day.”)
Next, Plaintiff noted in its memorandum supporting its motion for a preliminary injunction that “[a]n agency need not actually acquire ‘facts or opinions’ for the collection of information to exist, so long as the process of ‘obtaining,’ ‘soliciting,’ or ‘requiring. . . disclosure’ is underway.” Pl.’s Prelim. Inj. Mem. at 20 (quoting 44 U.S.C. § 3502(3)(A)). This is true, but irrelevant. Defendants acknowledge that an agency has “initiat[ed] the collection of information” once it makes the request of a member of the public, even if it has yet to receive an answer (in this context, when the Census Bureau mails the questionnaire but before it receives a response). But because the Census Bureau has yet to ask the question, or, in the words of the statute, to start soliciting or obtaining a response, this fact is of no legal significance. See Mem. Op., 2019 WL 498520, at *6 (“Consequently, ‘initiating’ a ‘collection of information’ – even if viewed as a process – still requires the beginning of at least one of these actions [obtaining, causing information to be obtained, soliciting information, or requiring the disclosure of information].”).
Plaintiff also contended in its preliminary injunction papers that the obligation to complete and publish a PIA that specifically addresses the collection of citizenship data matured as of March 26, 2018 – the date “the Bureau introduced a new requirement that census respondents disclose ‘facts or opinions’ to ‘third parties or the public.’” Pl.’s Prelim. Inj. Mem. at 21; see also 44 U.S.C. § 3502(3) (defining “collection of information” to include “requiring the disclosure” of information). But the Secretary’s memorandum announcing his decision to collect citizenship information during the 2020 Decennial Census did not require third parties to disclose information, it simply directed the Census Bureau to include a citizenship question on the 2020 Decennial Census questionnaire. See Mem. Op., 2019 WL 498520, at *4. Only once the
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citizenship question is asked of a respondent via a Paperwork Reduction Act-approved decennial census questionnaire or form does the requirement to disclose information ripen.5 See 13 U.S.C. § 221(a) (individuals are required to respond to “any of the questions on any schedule submitted to him in connection with any census or survey”); see also 44 U.S.C. § 3512(a) (“no person shall be subject to any penalty for failing to comply with a collection of information” absent that collection’s approval pursuant to the Paperwork Reduction Act). See Mem. Op., 2019 WL 498520, at *6 (holding that Plaintiff’s argument that the Secretary had “literally ‘requir[ed] the disclosure of facts or opinions to third parties’” in March 2018 as “simply not true”).
Plaintiff further stated in support of its motion for a preliminary injunction that the Census Bureau has “introduced a definite ‘plan . . . calling for the collection or disclosure of information.’” Pl.’s Prelim. Inj. Mem. at 21 (quoting 5 C.F.R. § 1320.3(c)). This argument refers to a subcomponent of OMB’s Paperwork Reduction Act regulations. Those OMB regulations note that “[a]s used in this Part,” referring to Paperwork Reduction Act obligations not at issue here, “‘collection of information,’ refers to the act of collecting or disclosing information, to the information to be collected or disclosed, to a plan and/or an instrument calling for the collection or disclosure of information, or any of these, as appropriate.” 5 C.F.R. § 1320.3(c). (This qualification appears to refer to the fact that the Paperwork Reduction Act’s regulations sometimes use “collection of information” as a verb, and sometimes as a noun to describe a package of information that must be submitted to OMB for approval, e.g., 5 C.F.R. § 1320.10.) Even this
5 As noted above, the Paperwork Reduction Act requires federal agencies seeking to collect information to first publish a notice in the Federal Register and allow 60 days for submission of comments. 44 U.S.C. § 3506(c)(2)(A); see also id. § 3502(3) (defining “collection of information”). After considering the submitted comments, the agency must then submit its information collection request to the Director of the Office of Management and Budget for review and approval. See id. § 3507(c)(3).
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definition – which does not explicitly apply outside Paperwork Reduction Act regulations – is consistent with the government’s interpretation. The only new element that the definition provides to “collection of information” is that the term can be, in certain contexts, a “plan and/or an instrument calling for the collection or disclosure of information.” 5 C.F.R. § 1320.3(c); see also Mem. Op., 2019 WL 498520, at *7 (noting the Court’s skepticism about importing the Paperwork Reduction Act’s regulatory definitions to the E-Government Act context).
But even if this definition did apply in this context, “[i]nitiating an instrument calling for the disclosure of information” is just another way of saying that the Bureau has posed the citizenship question to a member of the public via a questionnaire and solicited a response. Similarly, “initiating a plan calling for the disclosure of information” is best read to refer to the Census Bureau having started to solicit information from members of the public via the implementation of its process for soliciting such responses (i.e., starting the process of asking for and collecting census responses, or begun executing that solicitation plan), if, indeed, it makes sense at all in this context. As this Court explained, “even if the OMB regulations did apply, they would not change the outcome here”: “[t]o ‘initiate’ a ‘plan’ would still mean to commence it or put it into action, not merely to announce it.” Mem. Op., 2019 WL 498520, at *7.
Plaintiff attempts to contort the OMB regulations to state that an agency initiates a collection of information, and therefore must publish, if practicable, a PIA, once the agency has started planning to collect information. But the OMB regulations mention a “plan,” not “planning.” See 5 C.F.R. § 1320.3. Nor would it make sense to say that the agency must complete and, if practicable, publish a PIA before it has “started planning” the information collection. Before publication of a PIA, among other things, Section 208 of the E-Government Act requires that the agency have already identified what information is to be collected, as well as why, and
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how it will be used, and the IT security measures that will be in place to protect such data. See EGov. Act § 208(b)(2)(B). But this is information that can only be known – and therefore published – during or even at the conclusion of the planning process, not before the planning has begun. Plaintiff’s construction is thus incompatible with the structure of the statute itself.
2. Plaintiff is Not Likely to Show That its Claims Are Ripe or That it States a Claim Under the APA.
When it denied Plaintiff’s motion for a preliminary injunction, this Court declined to rely on concepts of ripeness and finality, stating that “these arguments would only be relevant if EPIC sought to challenge, prospectively, the agencies’ failure to conduct or release adequate PIAs in the future.” Mem. Op., 2019 WL 498520, at *8 n.10. The Court need not reconsider those conclusions here; the Court can dismiss the case for lack of standing or, if the Court finds it has jurisdiction, for failure to state a claim. But Defendants preserve their argument that, because the Census Bureau has not yet “initiat[ed] a new collection of information,” E-Gov. Act § 208(b)(1)(A)(ii), Plaintiff’s claims do not satisfy the elements of prudential ripeness. As Defendants explained in opposing Plaintiff’s motion for a preliminary injunction, “[t]he ripeness doctrine generally deals with when a federal court can or should decide a case.” Am. Petroleum Inst. v. EPA, 683 F.3d 382, 386 (D.C. Cir. 2012). “The doctrine’s purpose is ‘to prevent the courts, through avoidance of premature adjudication, from entangling themselves in abstract disagreements over administrative policies, and also to protect the agencies from judicial interference until an administrative decision has been formalized and its effects felt in a concrete way by the challenging parties.’” Belmont Abbey Coll. v. Sebelius, 878 F. Supp. 2d 25, 37 (D.D.C. 2012) (quoting Abbott Labs. v. Gardner, 387 U.S. 136, 148-49 (1967)). Ripeness has both constitutional and prudential elements, and in general, prudential ripeness requires that the parties “permit[] the administrative process to reach its end,” since that “can at least solidify or simplify the factual context and narrow the legal issues
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at play.” Am. Petroleum Inst., 683 F.3d at 387; see also id. (“Put simply, the doctrine of prudential ripeness ensures that Article III courts make decisions only when they have to, and then, only once.”).
Prudential ripeness has two elements – the fitness of the issue for judicial review and the extent to which withholding a decision will cause hardship to the parties. See Abbott Labs., 387 U.S. at 149. “The fitness requirement is primarily meant to protect ‘the agency’s interest in crystallizing its policy before that policy is subjected to judicial review and the court’s interests in avoiding unnecessary adjudication and in deciding issues in a concrete setting.’” Am. Petroleum Inst., 683 F.3d at 387 (quoting Wyo. Outdoor Council v. U.S. Forest Serv., 165 F.3d 43, 49 (D.C. Cir. 1999)). In general, a matter is not fit for judicial review if the “Court could not know what shape the final [determination] would take.” Belmont Abbey Coll., 878 F. Supp. 2d at 39.
Here, as discussed above, the Census Bureau is not yet required to publish, if practicable, a final PIA, and the context of the eventual final PIA - which the Census Bureau must complete before initiating the collection of information - remains inchoate. Until that threshold is passed, this dispute is not fit for review. Nor does “Plaintiff face[] any hardship that would outweigh the Court’s interest in deferring review.” Id. at 41. For this inquiry, courts “consider ‘not whether the [parties] have suffered any ‘direct hardship,’ but whether postponing judicial review would impose an undue burden on them or would benefit the court.’” Vill. of Bensenville v. FAA, 376 F.3d 1114, 1120 (D.C. Cir. 2004). Plaintiff has not shown that allowing the Census Bureau to issue a PIA under the timeframe permitted by the E-Government Act would impose an undue burden on its members.
Nor has Plaintiff stated a claim under the APA. It first states that it is “aggrieved by the Census Bureau’s unlawful initiation of a new collection of information without first completing
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the required privacy impact assessments.” Pl.’s Prelim. Inj. Mem. at 24 (citing Compl. ¶¶ 64-70). Defendants assume this is an allegation that the Census Bureau has taken action that is “arbitrary, capricious, an abuse of discretion, or otherwise not in accordance with law.” 5 U.S.C. § 706(2)(A). But this claim is not likely to succeed for two reasons. First, as discussed above, the Census Bureau has not acted arbitrarily, capriciously, or contrary to law; rather, it has adhered to the timing requirements set out by the E-Government Act.
Second, and relatedly, the Census Bureau’s non-issuance of a final PIA with regard to the citizenship question does not constitute final agency action. Defendants again acknowledge that the Court declined to rely on principles of finality in denying Plaintiff’s motion for a preliminary injunction, see Mem. Op., 2019 WL 498520, at *8 n.10, but Defendants briefly restate the argument here. Only “final agency action,” as opposed to action that is “preliminary, procedural, or intermediate,” is reviewable under the APA. 5 U.S.C. § 704; see also Trudeau v. FTC, 456 F.3d 178, 184-85 (D.C. Cir. 2006) (final agency action is a necessary requirement for a plaintiff to state a cause of action under the APA). Whether agency action is “final,” in turn, is governed by the Supreme Court’s decision in Bennett v. Spear, 520 U.S. 154 (1997). “First, the action must mark the consummation of the agency’s decisionmaking process – it must not be of a merely tentative or interlocutory nature. And second, the action must be one by which rights or obligations have been determined, or from which legal consequences will flow.” Id. at 177-78 (internal citations omitted).
As Plaintiff noted in its memorandum in support of its preliminary injunction motion, the Secretary’s March 26, 2018, decision to direct the Census Bureau to include a citizenship question on the 2020 Decennial Census questionnaire constitutes final agency action by the Commerce Department. See Pl.’s Prelim. Inj. Mem. at 24-25. But that decision is not challenged in this case.
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The decision at issue here is whether the Census Bureau has taken final agency action with respect
to publishing a PIA for the 2020 Decennial Census questionnaire including a citizenship question.
And here, as the Census Bureau has noted, the CEN08 PIA, as with its other PIAs, will continue
to be reviewed and updated as the agency’s 2020 Decennial Census operations become more
refined.6 See Bachman Decl. ¶¶ 6, 9, 15 (discussing future PIA updates). This process is not,
therefore, final.
Plaintiff also alleges a violation of section 706(1) of the APA to “compel agency action
unlawfully withheld or unreasonably delayed.” 5 U.S.C. § 706(1). “[A] claim under § 706(1) can
proceed only where a plaintiff asserts that an agency failed to take a discrete agency action that it
is required to take.” Norton v. S. Utah Wilderness All. (“SUWA”), 542 U.S. 55, 64 (2004). This
provision is similar to a mandamus remedy, and requires “a specific, unequivocal command.” Id.
at 63. Here, however, Section 208(b) does not unequivocally require the Census Bureau to publish
any PIA regarding the 2020 Decennial Census questionnaire at this time – at best, as discussed
above, the language is ambiguous. Nor does Section 208(b) unequivocally require the Census
6 Nor can Plaintiff argue that Defendants have “fail[ed] to act” within the meaning of 5 U.S.C. § 551(13). A “failure to act” claim must still satisfy the final agency action requirement, and in the context of section 706(2), the D.C. Circuit has emphasized that the agency must have finalized a decision not to issue a final decision, i.e., to have decided never to issue a PIA with regard to the decennial census questionnaire. The fact that the agency has simply not yet taken action is not reviewable. See, e.g., Sierra Club v. Thomas, 828 F.2d 783, 793 (D.C. Cir. 1987) (concluding that “EPA’s failure as yet to issue a final rule” does not “reflect[] an acknowledged EPA decision to [not regulate certain strip mines].”), partially abrogated by statute on other grounds, as reported by Mexichem Specialty Resins, Inc. v. EPA, 787 F.3d 544, 553 n.6 (D.C. Cir. 2015); Her Majesty the Queen in Right of Ontario v. EPA, 912 F.2d 1525, 1531 (D.C. Cir. 1990) (“[A]lthough . . . the EPA concededly made no final decision on petitioners’ request that the section 115 remedial process be initiated, it clearly and unequivocally rejected . . . petitioners’ requests for a separate proceeding[.]”) (emphasis added); see also Hazardous Waste Treatment Council v. Reilly, 938 F.2d 1390, 1396 (D.C. Cir. 1991) (agency statements that “do not constitute a definitive position . . . such that they represent a final statement of the agency’s position” do not constitute final agency action).
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Bureau to publish any PIA regarding the 2020 Decennial Census questionnaire at all. Section

208(b) provides agencies with discretion in making PIAs publicly available by noting that

publication is required only “if practicable.” E-Gov. Act § 208(b)(1)(B)(iii).

Finally, Plaintiff cannot attempt to challenge the PIA-process itself, i.e., the process by

which Defendants continually reexamine their IT systems. See OMB Circulator A-130, supra.

Even if Plaintiff claimed standing for such a claim, and it does not, see Compl. ¶¶ 68-69, 74-75;

Pl.’s Prelim. Inj. Mem. at 37-40, such a legal claim would be the “kind of broad programmatic

attack” that the Supreme Court has repeatedly rejected. See SUWA, 542 U.S. at 64 (citing Lujan

v. Nat’l Wildlife Fed’n., 497 U.S. 871 (1990)). Accordingly, Plaintiff’s section 706(1) claim is

meritless.

CONCLUSION

For the aforementioned reasons and consistent with the Court’s Memorandum Opinion

denying Plaintiff’s Motion for a Preliminary Injunction, the Court should dismiss Plaintiff’s

complaint in its entirety.

Dated: March 11, 2019

Respectfully submitted,

JOSEPH H. HUNT Assistant Attorney General

CARLOTTA P. WELLS Assistant Branch Director

/s/ Kristina A. Wolfe KRISTINA A. WOLFE JOSEPH E. BORSON (Va. Bar No. 85519) Trial Attorney, U. S. Dept. of Justice Civil Division, Federal Programs Branch 1100 L St., NW Washington, D.C. 20005 Tel. (202) 353-4519 Email: kristina.wolfe@usdoj.gov

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Case 1:18-cv-02711-DLF Document 20-2 Filed 03/11/19 Page 1 of 1
IN THE UNITED STATES DISTRICT COURT FOR THE DISTRICT OF COLUMBIA

ELECTRONIC PRIVACY INFORMATION CENTER,
Plaintiff,
v.
UNITED STATES DEPARTMENT OF COMMERCE, et al.,
Defendants.

Civil Action No. 1:18-cv-02711 (DLF)

[PROPOSED] ORDER
Upon consideration of Defendants’ Motion to Dismiss, it is hereby ORDERED that Defendants’ Motion to Dismiss is GRANTED.

IT IS SO ORDERED, this

day of

, 2019.

__________________________________ DABNEY L. FRIEDRICH UNITED STATES DISTRICT JUDGE

 
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United States Court of Appeals
FOR THE DISTRICT OF COLUMBIA CIRCUIT

Argued May 8, 2019

Decided June 28, 2019

No. 19-5031

ELECTRONIC PRIVACY INFORMATION CENTER, APPELLANT

v.

UNITED STATES DEPARTMENT OF COMMERCE AND BUREAU OF THE CENSUS, APPELLEES

Appeal from the United States District Court for the District of Columbia (No. 1:18-cv-02711)
John Davisson argued the cause for appellant. With him on the briefs were Alan Butler and Marc Rotenberg.
Sarah Carroll, Attorney, U.S. Department of Justice, argued the cause for appellees. With her on the brief was Mark B. Stern, Attorney.
Before: HENDERSON and MILLETT, Circuit Judges, and SENTELLE, Senior Circuit Judge.

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Opinion for the Court filed by Senior Circuit Judge SENTELLE.
SENTELLE, Senior Circuit Judge: On March 26, 2018, the Department of Commerce announced that a citizenship question would be added to the 2020 Census. The Electronic Privacy Information Center (EPIC) contends that, before this announcement was made, its members were entitled to a Privacy Impact Assessment by law. EPIC sued to enjoin the addition of the question on this basis, and now appeals the district court’s denial of its motion for a preliminary injunction. Because EPIC lacks standing, we remand to the district court with instructions to dismiss.
I. Background
A. The E-Government Act
In 2002, Congress passed the E-Government Act to modernize and regulate the government’s use of information technology. Pub. L. No. 107-347, 116 Stat. 2899 (codified at 44 U.S.C. § 3501 note) (hereinafter “E-Government Act”). The Act outlines eleven purposes. Nine involve improving government efficiency, organization, and decision-making. EGovernment Act § 2(b). In addition to these predominantly agency-centric goals, however, the Act also aims to “provide increased opportunities for citizen participation in Government,” and “[t]o make the Federal Government more transparent and accountable.” §§ 2(b)(2), (9).
Section 208 of the Act contains privacy provisions. Its stated purpose is to “ensure sufficient protections for the privacy of personal information as agencies implement citizen-centered electronic Government.” E-Government Act § 208(a). To effectuate this purpose, § 208 requires federal

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agencies to conduct, review, and, “if practicable,” publish, a Privacy Impact Assessment (PIA) before “initiating a new collection of information” that involves personally identifiable information that will be “collected, maintained, or disseminated using information technology.” § 208(b)(1)(A)– (B). A “collection of information” is defined as “obtaining, causing to be obtained, soliciting, or requiring the disclosure . . . of facts or opinions” through “identical questions posed to . . . ten or more persons.” 44 U.S.C. § 3502(3)(A). The word “initiating” is not defined by statute.
A PIA required by a new collection of information must address, at a minimum: what information will be collected, why it is being collected, how it will be used, how it will be secured, with whom it will be shared, whether a system of records is being created under the Privacy Act, and what “notice or opportunities for consent” will be provided to those impacted. E-Government Act § 208(b)(2)(B)(ii).
B. The Census
To apportion representatives among the several States, the Census Clause of the United States Constitution requires an “actual Enumeration” of the United States population. U.S. Const. art. I, § 2, cl. 3. The census occurs every ten years, “in such Manner as [Congress] shall by Law direct.” Id. Pursuant to this command, Congress passed a series of census laws directing the Secretary of Commerce to conduct a decennial census and establishing the Census Bureau as an agency within the Department of Commerce. 13 U.S.C. §§ 2, 141(a). These laws give the Secretary broad authority to “obtain such other census information as necessary.” Id. § 141(a). The census has historically included a wide variety of demographic questions, often including questions about citizenship status. With few exceptions, a refusal to answer

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“any of the questions” on the census is a violation of law. 13 U.S.C. § 221.
The Census Bureau operates at least six information technology (IT) systems that process, store, and disseminate personally identifiable information from census responses. The primary system used for the census is called “CEN08.” This system shares information with five other systems: “CEN21,” “CEN05,” “CEN11,” “CEN13,” and “CEN18.” The Bureau maintains a PIA for each system on a publiclyavailable website. Because the use of the systems changes regularly, the Bureau reviews and updates each assessment at least once per year.
C. The Challenge
On March 26, 2018, the Secretary of Commerce, Wilbur Ross, announced that a citizenship question would be added to the 2020 Census. A variety of legal challenges to the merits of that decision followed.
This case presents a narrow question: when does the addition of the citizenship question need to be addressed in a PIA? The parties agree that the E-Government Act requires the government to complete a PIA before “initiating a new collection of information.” E-Government Act § 208(b)(1)(A)(ii). Their disagreement involves the meaning of the word “initiating.” The Census Bureau believes that it does not initiate a collection of information until it solicits information from the public. If this is correct, then the Bureau is not required to produce PIAs until questionnaires are mailed out in 2020. The Government has consistently provided assurances, both before the district court and here on appeal, that the assessments will be completed “before it distributes any 2020 Decennial Census questionnaires.” See,

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e.g., Gov. Br. at 30. Indeed, the PIA updates have been in progress as this litigation proceeded, and an updated PIA addressing the citizenship question was published for one of the six relevant IT systems (CEN08) a few days before this Court heard oral argument. Notwithstanding these assurances and evidence of progress, EPIC, a public interest research center focused on privacy and civil liberties, challenges the Government’s interpretation. In EPIC’s view, the decision to add the question was the initiation of information collection. If this interpretation is correct, the completed PIAs were required before the decision to add the question was announced on March 26, 2018.
Eight months after Secretary Ross’s announcement, EPIC filed a complaint in the district court. It alleged three counts against the Department of Commerce and the Bureau of the Census—two under the Administrative Procedure Act and one under the Declaratory Judgment Act. Count One alleges that the Secretary committed an unlawful act under 5 U.S.C. § 706(2)(a) and (c) when he announced the decision to add the citizenship question before completing the PIAs. Similarly, Count Two alleges that the government unlawfully withheld agency action, in violation of 5 U.S.C. § 706(1), by failing to timely complete and publish the PIAs. Count Three seeks a declaration of rights under 28 U.S.C. § 2201(a). Among other requested relief, EPIC asks the court to: (1) set aside the decision to add the citizenship question; (2) order that the decision be revoked until the PIAs are completed and published; and (3) order the completion and publication of the PIAs.
On January 18, 2019, EPIC moved for a preliminary injunction. In the text of the proposed order submitted with its motion, EPIC asked that the Census Bureau be “enjoined from initiating any collection of citizenship status

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information.” Pl.’s Mot. Prelim. Inj. Attach. 2 at 1 (emphasis added). This is curious, since EPIC’s entire argument is that such collection has already been initiated. Nevertheless, the district court denied the motion because EPIC failed to show a likelihood of success on the merits or a likelihood of irreparable harm. EPIC v. U.S. Dep’t of Commerce, 356 F. Supp. 3d 85, 89, 95–97 (D.D.C. 2019). The district court held that EPIC was not likely to succeed on the merits because “initiating a new collection of information” requires more than a decision to collect information at some point in the future. Id. at 89–91. The court agreed with the Government that collection did not begin until the first set of census questions was mailed out. Id. at 90. The district court also concluded that EPIC was not likely to suffer irreparable harm since the collection of citizenship information—set to occur in 2020—was not imminent. Id. at 95–97. EPIC timely appealed the denial of its motion.
II. Jurisdiction
We have the statutory jurisdiction to review the denial of a preliminary injunction under 28 U.S.C. § 1292(a)(1). Before we review the merits of this appeal, however, we must consider whether federal courts have the constitutional power to decide this case in the first place. “Every federal appellate court has a special obligation to satisfy itself not only of its own jurisdiction, but also that of the lower courts in a cause under review . . . .” Arizonans for Official English v. Arizona, 520 U.S. 43, 73 (1997) (internal quotations omitted). “When the lower federal court lacks jurisdiction, we have jurisdiction on appeal, not of the merits but merely for the purpose of correcting the error of the lower court in entertaining the suit.” Steel Co. v. Citizens for a Better Env’t, 523 U.S. 83, 95 (1998) (internal quotations omitted).

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“The Constitution limits our ‘judicial Power’ to ‘Cases’ and ‘Controversies,’ U.S. Const. art. III, § 2, cl. 1.” West v. Lynch, 845 F.3d 1228, 1230 (D.C. Cir. 2017) (citing Steel Co., 523 U.S. at 102). “[T]here is no justiciable case or controversy unless the plaintiff has standing.” Id. “To establish standing, the plaintiff must show (1) it has suffered a concrete and particularized injury (2) that is fairly traceable to the challenged action of the defendant and (3) that is likely to be redressed by a favorable decision, i.e., a decision granting the plaintiff the relief it seeks.” EPIC v. Presidential Advisory Comm’n on Election Integrity (PACEI), 878 F.3d 371, 376– 77 (D.C. Cir. 2017) (internal quotations omitted). EPIC is required to establish standing as to each claim, and each form of requested relief. See id. at 377. Since the three counts in EPIC’s complaint involve a repackaging of the same underlying grievance, we need not undertake a separate standing analysis as to each claim.
As an organization, EPIC can assert standing in one of two ways. It can assert standing on its own behalf, as an organization, or on behalf of its members, as associational standing. See Am. Soc. for Prevention of Cruelty to Animals v. Feld Entm’t, Inc., 659 F.3d 13, 24 (D.C. Cir. 2011). As we will explain, EPIC’s assertion of organizational standing is plainly foreclosed by precedent. Its assertion of associational standing also fails, because it has not identified a concrete injury suffered by one of its members.
A. Organizational Standing
“[A]n organization may establish Article III standing if it can show that the defendant’s actions cause a concrete and demonstrable injury to the organization’s activities that is more than simply a setback to the organization’s abstract social interests.” Feld Entm’t, 659 F.3d at 25 (internal

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quotations omitted). This Court has previously considered and rejected EPIC’s assertion of organizational standing with respect to § 208 of the E-Government Act. PACEI, 878 F.3d 371. In PACEI, EPIC challenged the authority of the Presidential Advisory Commission on Election Integrity to collect voter information from each state without first publishing a PIA as required by § 208. 878 F.3d at 374. The requested relief included: (1) an order requiring the PACEI to “promptly” publish a PIA and (2) an order enjoining its collection of voter data. Id. at 377, 380. We held that EPIC did not have organizational standing to compel the publication of a PIA or to seek an injunction barring the collection of information. Id. at 378, 380. On both counts, EPIC was unable to show how the failure to publish a PIA concretely injured its organizational interest. Id. at 379. We held that § 208 did not confer an informational interest on EPIC as an organization, and any resources spent obtaining information that would otherwise have been in a PIA was a “self-inflicted budgetary choice that cannot qualify as an injury in fact.” Id. The same reasoning applies to the present complaint. Thus, any assertion of organizational standing by EPIC under § 208 is foreclosed by our prior precedent.
B. Associational Standing
With organizational standing out of the question, we turn to EPIC’s assertion of associational standing. An organization can assert associational standing on behalf of its members if: “(1) at least one of their members has standing to sue in her or his own right, (2) the interests the association seeks to protect are germane to its purpose, and (3) neither the claim asserted nor the relief requested requires the participation of an individual member in the lawsuit.” Am. Library Ass’n v. FCC, 401 F.3d 489, 492 (D.C. Cir. 2005).

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We begin our analysis by observing that EPIC is a membership organization. Respondent contends that our precedent determines that EPIC is not, citing PACEI. It is true that when we issued our decision in PACEI, we noted that “as far as the record shows, [EPIC] has no traditional membership[.]” 878 F.3d at 380. Since that decision issued, however, the nature of the organization has changed. In January 2018, EPIC amended its bylaws. The new bylaws require the organization to designate “members” who must be “distinguished experts in law, technology, and public policy.” Members are eligible to sit on the Board of Directors. They also provide leadership to the organization and pay dues. We implicitly recognized that these changes were enough to turn EPIC into a membership organization when we conducted an associational standing analysis in EPIC v. FAA, 892 F.3d 1249, 1253-55 (D.C. Cir. 2018). We expressly recognize it here.
Having established that EPIC is a membership organization, we can examine the first prong of the associational standing analysis. At this step, EPIC must show, for each of its claims, that at least one of its members has standing. See Am. Library Ass’n, 401 F.3d at 492. By necessity, this requires at least one of EPIC’s members to have suffered a “concrete and particularized” injury. See Lujan v. Defs. of Wildlife, 504 U.S. 555, 560 (1992). EPIC avers that its members have suffered, or will suffer, both informational and privacy injuries. However, they have made no such showing.

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1. Privacy Injury
EPIC asserts that its members will suffer a privacy injury if their citizenship status information is “unlawfully collected.” EPIC argues that the act of collecting information without a PIA, by itself, constitutes an imminent, concrete, and particularized privacy injury. But “a bare procedural violation, divorced from any concrete harm, [does not] satisfy the injury-in-fact requirement of Article III.” Spokeo, Inc. v. Robins, 136 S. Ct. 1540, 1549 (2016). Therefore, to plausibly show a privacy injury, EPIC must allege harm that is distinct from a simple failure to comply with the procedural requirements of § 208. In the privacy context, such harm would ordinarily stem from the disclosure of private information. Since EPIC has not shown how a delayed PIA would lead to a harmful disclosure, its privacy injury theory fails.
Disclosure of individual census responses to third parties is prohibited by law. 13 U.S.C. § 9. A census response may not be used for “any purpose other than the statistical purposes for which it is supplied” and only “sworn officers and employees of the Department [of Commerce] or [Census] [B]ureau” may examine individual reports. Id. § 9(a)(1), (3). Responses are not even admissible as evidence in court in most circumstances. Id. § 9(a). We agree with the Southern District of New York that “it is pure speculation to suggest that the Census Bureau will not comply with its legal obligations to ensure the privacy of respondents’ data or that those legal obligations will be amended.” New York v. U.S. Dep’t of Commerce, 351 F. Supp. 3d 502, 619 (S.D.N.Y. 2019). More specifically, EPIC has not convinced us that a delay in receiving a PIA will make the Census Bureau any less likely to comply with these laws. Speculation, we have said before, “is ordinarily fatal to standing.” PACEI, 878 F.3d

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at 379 (citing DaimlerChrysler Corp. v. Cuno, 547 U.S. 332, 344 (2006)). Therefore, to the extent that EPIC relies on the potential disclosure of their citizenship status to third parties as the source of injury, we reject the theory as a “speculative chain of possibilities” that cannot establish an injury. Accord Clapper v. Amnesty Int’l USA, 568 U.S. 398, 414 (2013).
For the first time on appeal, EPIC also suggests that its members have a constitutional privacy interest in keeping their citizenship status private from the government itself. EPIC cites Whalen v. Roe and Nixon v. Administrator of General Services for the proposition that its members have an interest in “avoiding disclosure of personal matters” and that “informational privacy is ‘implicit in the concept of ordered liberty.’” Appellant Reply Br. at 10 (citing Whalen, 429 U.S. 589, 599 n.23 (1977); Nixon, 433 U.S. 425, 455 (1977)). We have previously expressed “grave doubts as to the existence of a constitutional right of privacy in the nondisclosure of personal information,” at least “where the information is collected by the government but not disseminated publicly.” Am. Fed’n of Gov’t Employees v. HUD, 118 F.3d 786, 791, 794 (D.C. Cir. 1997). These doubts are particularly acute where the information in question is as deeply entwined with national sovereignty and governance as citizenship status.
We need not resolve this issue today, however, because EPIC has not squarely challenged the merits or constitutionality of the citizenship question in this case. Rather, they challenge the procedural propriety of the government’s collection of this information in the absence of a timely PIA. The narrow question before the Court—a question about the timing of PIAs—is completely “[dis]connected” from the broader question of whether a citizenship question on the census is constitutionally permissible. Accord Sugar Cane Growers Co-op. of Fla. v.

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Veneman, 289 F.3d 89, 94–95 (D.C. Cir. 2002). Therefore, for the purposes of this litigation, the existence or scope of a right to informational privacy with respect to citizenship status is not relevant. EPIC has not shown that the timing for publishing PIAs is plausibly connected to the government’s collection of private information that it would not otherwise collect. Especially because, as previously noted (page 2, supra), the principal purpose of the impact assessment is not to deter collection in the first place, but instead to improve upon an agency’s storage and sharing practices.
In short, EPIC has failed to show that its members have suffered, or imminently will suffer, a privacy injury as a result of a delayed PIA.
2. Informational Injury
Having concluded that EPIC’s members have not suffered a privacy injury, we turn to the contention that they have suffered an informational injury. To show an informational injury, a plaintiff must show: “(1) it has been deprived of information that, on its interpretation, a statute requires the government or a third party to disclose to it, and (2) it suffers, by being denied access to that information, the type of harm Congress sought to prevent by requiring disclosure.” Friends of Animals v. Jewell, 828 F.3d 989, 992 (D.C. Cir. 2016). Mirroring our analysis in PACEI, we do not consider whether EPIC satisfies the first prong of the analysis, because EPIC’s members cannot satisfy the second. See PACEI, 878 F.3d at 378.
Even if § 208 requires the disclosure of PIAs to EPIC’s members, the organization cannot show that those members have suffered the “type of harm Congress sought to prevent by requiring disclosure.” See Jewell, 828 F.3d at 992. In

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PACEI, this Court considered what type of harm § 208 of the E-Government Act was designed to prevent. We held that § 208 “is directed at individual privacy” and protects individuals “by requiring an agency to fully consider their privacy before collecting their personal information.” PACEI, 878 F.3d at 378 (emphasis in original). We read this holding to reject the possibility that § 208 can support an informational injury theory, at least in the absence of a colorable privacy harm of the type that Congress sought to prevent through the E-Government Act.
Section 208 was not designed to vest a general right to information in the public. Rather, the statute was designed to protect individual privacy by focusing agency analysis and improving internal agency decision-making. In this respect, § 208 is fundamentally different from statutes like the Freedom of Information Act (FOIA) where the harm Congress sought to prevent was a lack of information itself. Unlike § 208, FOIA was designed to grant enforceable rights to information in the general public. The “broad mandate of the FOIA is to provide for open disclosure of public information” and to allow citizens “to be informed about what their government is up to.” Baldrige v. Shapiro, 455 U.S. 345, 352 (1982); DOJ v. Reporters Comm. for Freedom of Press, 489 U.S. 749, 773 (1989) (internal quotations omitted). These purposes stand in contrast with the stated agency-centric purpose of § 208 to “ensure sufficient protections for the privacy of personal information as agencies implement citizen-centered electronic Government.” E-Government Act § 208(a) (emphasis added).
Because the lack of information itself is not the harm that Congress sought to prevent through § 208, EPIC must show how the lack of a timely PIA caused its members to suffer the kind of harm that Congress did intend to prevent: harm to

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individual privacy. See PACEI, 878 F.3d at 378. As discussed in Part II.B.1, however, EPIC cannot allege an imminent privacy harm without assuming the independent violation of other laws by the Census Bureau. This is too speculative to support standing. For this reason, we hold that EPIC cannot satisfy the second step of the Jewell analysis, and cannot show an informational injury, just as it cannot show a privacy injury.
C. Disposition
Because we conclude that EPIC has failed, as a matter of law, to show that any of its members have suffered a concrete privacy or informational injury, we lack jurisdiction to proceed and must remand the case for dismissal. Indeed, we retain jurisdiction only “for the purpose of correcting the error of the lower court in entertaining the suit.” Steel Co., 523 U.S. at 95.
We take a moment to explain why we have sometimes affirmed the denial of a preliminary injunction based on a standing-related defect, but do not do so here. One showing a plaintiff must make to obtain a preliminary injunction is “a substantial likelihood of success on the merits.” Food & Water Watch, Inc. v. Vilsack, 808 F.3d 905, 913 (D.C. Cir. 2015). “[T]he ‘merits’ on which plaintiff must show a likelihood of success encompass not only substantive theories but also establishment of jurisdiction.” Id. (quoting Obama v. Klayman, 800 F.3d 559, 565 (D.C. Cir. 2015) (Williams, J., concurring)). In determining whether the plaintiff has “a substantial likelihood of success on the merits,” then, we have considered whether the plaintiff has a “substantial likelihood of standing”—that is, whether the plaintiff is likely to be able to demonstrate standing at the summary judgment stage. See id. at 912 (standing must be evaluated “under the heightened

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standard for evaluating a motion for summary judgment” in “determining whether or not to grant the motion for preliminary injunction”); see also Bennett v. Spear, 520 U.S. 154, 167–68 (1997) (“[E]ach element of Article III standing ‘must be supported in the same way as any other matter on which the plaintiff bears the burden of proof, i.e., with the same manner and degree of evidence required at the successive stages of litigation.’. . . [A] plaintiff must ‘set forth’ by affidavit or other evidence ‘specific facts’ to survive a motion for summary judgment.” (first quoting Lujan v. Defenders of Wildlife, 504 U.S. 555, 561 (1992), and then quoting Fed. R. Civ. P. 56(e) (1987))). “[A]n inability to establish a substantial likelihood of standing requires denial of the motion for preliminary injunction, not dismissal of the case.” Food & Water Watch, 808 F.3d at 913. Thus, in cases where we have found that a plaintiff had not established a “substantial likelihood of standing,” we have affirmed the denial of a preliminary injunction. See, e.g., PACEI, 878 F.3d at 377, 380.
Notwithstanding these cases, if, in reviewing the denial of a preliminary injunction, we determine that a litigant cannot establish standing as a matter of law, the proper course is to remand the case for dismissal. See Crow Creek Sioux Tribe v. Brownlee, 331 F.3d 912, 918 (D.C. Cir. 2003). Here, we find that EPIC lacks standing as a matter of law. As a result, our only remaining constitutional duty is to “correct[] the error of the lower court in entertaining the suit.” See Steel Co., 523 U.S. at 95.
III. Conclusion
Because EPIC lacks standing, we vacate the district court’s denial of the preliminary injunction and remand for the purpose of dismissal.
So ordered.