1 

RECOMMENDED FOR FULL-TEXT PUBLICATION 

Pursuant to Sixth Circuit I.O.P. 32.1(b) 

File Name: 14a0071p.06 

UNITED STATES COURT OF APPEALS

FOR THE SIXTH CIRCUIT 

_________________ 

EQUAL EMPLOYMENT OPPORTUNITY COMMISSION, 

Plaintiff-Appellant, 

v. 

KAPLAN HIGHER EDUCATION CORPORATION, 

KAPLAN, INC., and IOWA COLLEGE ACQUISITION 

CORPORATION, d/b/a Kaplan University, 

Defendants-Appellees. 

┐

│

│

│

│

│

│

│

│

│

┘

No. 13-3408 

Appeal from the United States District Court 

for the Northern District of Ohio at Cleveland 

No. 1:10-cv-02882—Patricia A. Gaughan, District Judge. 

Argued: March 20, 2014 

Decided and Filed: April 9, 2014 

Before: KEITH, COOK, and KETHLEDGE, Circuit Judges. 

_________________ 

COUNSEL 

ARGUED: Kate Northrup, UNITED STATES EQUAL EMPLOYMENT OPPORTUNITY 

COMMISSION, Washington, D.C., for Appellant. Gerald L. Maatman, Jr., SEYFARTH SHAW 

LLP, Chicago, Illinois, for Appellees. ON BRIEF: Kate Northrup, UNITED STATES EQUAL 

EMPLOYMENT OPPORTUNITY COMMISSION, Washington, D.C., for Appellant. Gerald L. 

Maatman, Jr., David J. Rowland, Pamela Q. Devata, Jennifer A. Riley, Matthew J. Gagnon, 

SEYFARTH SHAW LLP, Chicago, Illinois, for Appellees. Anastasia P. Boden, PACIFIC 

LEGAL FOUNDATION, Sacramento, California, for Amicus Curiae. 

 

>
No. 13-3408 EEOC v. Kaplan, et al. Page 2 

_________________ 

OPINION

_________________ 

KETHLEDGE, Circuit Judge. In this case the EEOC sued the defendants for using the 

same type of background check that the EEOC itself uses. The EEOC’s personnel handbook 

recites that “[o]verdue just debts increase temptation to commit illegal or unethical acts as a 

means of gaining funds to meet financial obligations.” Because of that concern, the EEOC runs 

credit checks on applicants for 84 of the agency’s 97 positions. The defendants (collectively, 

“Kaplan”) have the same concern; and thus Kaplan runs credit checks on applicants for positions 

that provide access to students’ financial-loan information, among other positions. For that 

practice, the EEOC sued Kaplan. 

Specifically, the EEOC alleges that Kaplan’s use of credit checks causes it to screen out 

more African-American applicants than white applicants, creating a disparate impact in violation 

of Title VII of the federal Civil Rights Act. See 42 U.S.C. § 2000e-2(a)(1), (a)(2), (k). Proof of 

disparate impact is usually statistical proof in the form of expert testimony; and here the EEOC 

relied solely on statistical data compiled by Kevin Murphy, who holds a doctorate in industrial 

and organizational psychology. For two reasons, however, the district court excluded Murphy’s 

testimony on grounds that it was unreliable. First, the EEOC presented “no evidence” that 

Murphy’s methodology satisfied any of the factors that courts typically consider in determining 

reliability under Federal Rule of Evidence 702; and second, as Murphy himself admitted, his 

sample was not representative of Kaplan’s applicant pool as a whole. The district court therefore 

granted summary judgment to Kaplan. The EEOC now argues that the district court “erred”—a 

telling, oft-repeated, and mistaken choice of word here—when it excluded Murphy’s testimony. 

We reject the EEOC’s arguments and affirm. 

Kaplan offers undergraduate and graduate degrees to students across the country. Some 

of Kaplan’s students obtain financial aid through programs operated by the United States 

Department of Education; and consequently, some of Kaplan’s employees have access to those 

students’ financial information. The Department has regulations that circumscribe the manner in 
No. 13-3408 EEOC v. Kaplan, et al. Page 3 

which Kaplan can access and use students’ information. Violations of those regulations can 

bring severe penalties. 

Kaplan’s concerns became reality about a decade ago, when it discovered that some of its 

financial-aid officers had stolen payments that belonged to students. Kaplan also learned that 

some of its executives had engaged in self-dealing, by hiring relatives as vendors. In response, 

Kaplan implemented a number of measures to prevent these abuses. One of those measures was 

to run credit checks on applicants for senior-executive positions, accounting and other positions 

with access to company financials or cash, and positions with access to student financial-aid 

information. The credit checks are performed by a third-party vendor, which reports, among 

other things, whether the applicant has ever filed for bankruptcy, is delinquent on child-support 

payments, has any garnishments on earnings, has outstanding civil judgments exceeding $2,000, 

or has a social-security number that does not match the number the credit bureau has on file. If 

an applicant’s credit history includes any of the enumerated items, the vendor flags the 

applicant’s file for “review.” At that point, Kaplan typically reviews the file and makes an ad 

hoc decision as to whether to move forward with the application. The credit-check process is 

racially blind: the vendor does not report the applicant’s race with her other information. 

Kaplan has used several vendors for its credit checks, but Murphy focused upon 

applications screened by one vendor, General Information Services (“GIS”). Murphy obtained 

GIS data for 4,670 applicants. That data, as discussed above, did not include the applicant’s 

race, so the EEOC subpoenaed records from the departments of motor vehicles. Eleven states 

provided records that identified an applicant’s race. Thirty-six states and the District of 

Columbia provided color copies of drivers’ license photos for approximately 900 applicants. 

The dispute in this case concerns the reliability, or lack thereof, of the process—which 

the EEOC calls “race rating”—by which Murphy purported to identify the race of each person in 

those drivers’ license photos. The process was crafted by Murphy himself, specifically for 

purposes of litigation—though the record contains no indication that Murphy has any particular 

expertise in constructing methodologies to identify race by visual means. In any event, Murphy 

assembled a team of five “race raters,” each of whom has experience in what the EEOC calls 

“multicultural, multiracial, treatment outcome research”—a term undefined by the EEOC here. 
No. 13-3408 EEOC v. Kaplan, et al. Page 4 

But that term assuredly does not refer to the raters’ experience with methodologies to identify 

race by visual means—since, undisputedly, they have none. Murphy directed each rater 

separately to review each applicant’s drivers’ license photograph and then classify the person’s 

race in one of five ways: “African-American,” “Asian,” “Hispanic,” “White,” or “Other.” If 

four of five raters agreed upon a particular applicant’s race, the applicant was so classified for 

purposes of Murphy’s statistics. For 11.7% of the photographs, the raters failed to reach that 

consensus. For some reason Murphy also provided the raters with each applicant’s name—

which, the EEOC concedes, the raters were supposed to disregard when classifying an 

applicant’s race. 

Murphy filed his expert report on May 1, 2012 and then a revised report on August 17, 

2012, both per the district court’s scheduling order. The revised report included the putative race 

and credit-check results for a total of 1,090 applicants, of whom 803 had been racially classified 

per Murphy’s “rating” process. In that sample of 1,090 applicants (out of a total of 4,670 

applicants for whom GIS provided data), the percentage of black applicants who were flagged 

for review, based upon their credit histories, was higher than the percentage of white applicants 

who were flagged. (That is essentially the basis upon which the EEOC claims disparate impact 

here.) But Murphy’s sample overrepresented “fails” generally: 23.8% of the applicants in his 

sample of 1,090 were rejected because of their credit history, whereas only 13.3% of the total 

GIS pool of 4,670 were. 

Murphy then proceeded to file additional reports, contrary to the terms of the district 

court’s scheduling order. On September 5, 2012—in response to a critical analysis of his work 

by Kaplan’s expert—Murphy submitted a third report, which Kaplan moved to strike, but which 

the district court reluctantly permitted in an October 5 order, with the admonition that “[n]o 

further expert reports are allowed.” Yet Murphy filed another report on November 8, 2012, two 

weeks before summary-judgment briefing was due. In that report, Murphy provided what the 

EEOC describes as “anecdotal corroboration” of the reliability of his race-rating process. 

Murphy filed yet another report on December 21, 2012, this time in response to Kaplan’s motion 

specifically to exclude his testimony as unreliable under Rule 702. 
No. 13-3408 EEOC v. Kaplan, et al. Page 5 

The district court thereafter excluded Murphy’s testimony in a meticulously reasoned 

opinion. We review that exclusion deferentially, for an abuse of discretion. Gen. Elec. Co. v. 

Joiner, 522 U.S. 136, 139 (1997). 

Rule 702 provides that “[a] witness who is qualified as an expert by knowledge, skill, 

experience, training, or education may testify in the form of an opinion or otherwise if[,]” among 

other requirements, the testimony “is based on sufficient facts and data” and “is the product of 

reliable principles and methods[.]” Fed. R. Evid. 702(b), (c). As the proponent of expert 

testimony, the EEOC bears the burden of proving its admissibility. Nelson v. Tenn. Gas Pipeline 

Co., 243 F.3d 244, 251 (6th Cir. 2001). 

In determining whether an expert’s methodology is reliable, courts frequently consider 

the factors set forth by the Supreme Court in Daubert v. Merrell Dow Pharmaceuticals, Inc., 

509 U.S. 579 (1993). But the district court has “broad latitude” as to which factors to consider in 

a particular case. Kumho Tire Co. v. Carmichael, 526 U.S. 137, 142 (1999). 

Here, the district court considered every one of the Daubert factors—and found that 

Murphy’s methodology flunked them all. Two factors we consider together. “Ordinarily, a key 

question to be answered” in determining whether a technique is reliable is “whether it can be 

(and has been) tested.” Daubert, 509 U.S. at 593. Similarly, “in the case of a particular 

scientific technique, the court ordinarily should consider the known or potential rate of error.” 

Id. at 594. The district court found that the EEOC “wholly fail[ed]” to provide evidence in 

support of either of these factors. Op. at 13. In response, the EEOC argues that we can find that 

support in Murphy’s “anecdotal corroboration”—set forth in his November 8 report, submitted a 

month after the district court said there would be no more reports. We consider it now only 

because the district court did. Murphy says that, as to 47 applicants, he cross-checked his raters’ 

classifications with racial identifications provided by a DMV, finding 95.7% agreement between 

the two. Murphy also says that, for another 10 applicants, he cross-checked his raters’ 

classifications with racial information provided by PeopleSoft, a personnel-software program 

used internally by Kaplan. That cross-check yielded an 80% match—an unimpressive 

correlation in case where a few percentage points (in credit-check fail rates for blacks and 

whites) might make the difference between significant liability and none. But more to the point, 
No. 13-3408 EEOC v. Kaplan, et al. Page 6 

as Murphy himself candidly conceded, a mere 57 instances of anecdotal corroboration is not 

enough “to establish the reliability of my photo rating methodology.” The district court was well 

within its “broad latitude[,]” Kumho, 526 U.S. at 142, to find these factors unmet. 

The EEOC’s case goes downhill from there. In determining reliability, “[a]nother 

pertinent consideration is whether the theory or technique has been subjected to peer review and 

publication.” Daubert, 509 U.S. at 593. Again the district court found no evidence in support of 

this factor, and undisputedly there is none. Before us, the EEOC simply argues that the district 

court should not have considered the factor. The argument is meritless: “submission to the 

scrutiny of the scientific community is a component of ‘good science,’ in part because it 

increases the likelihood that substantive flaws in methodology will be detected[,]” id.; and the 

district court had good reason to think that such scrutiny might have detected flaws here. 

The district court also found that Murphy’s methodology lacked “standards controlling 

the technique’s operation.” Id. at 594. The EEOC responds that the relevant standard was 

Murphy’s requirement that four of five raters agree on an applicant’s race. But that response 

overlooks Murphy’s own concession that the raters themselves had no particular standard in 

classifying each applicant; instead, they just eyeballed the DMV photos. The district court was 

also troubled by an affirmative breakdown in Murphy’s controls: “the ‘race raters’ were provided 

the names of the applicants,” which—for a methodology purportedly based exclusively on visual 

identification of race—might “create an unintended bias on the part of the panel.” Op. at 16. 

The EEOC countered at oral argument that there is “no evidence” that the raters considered any 

of the applicants’ names in classifying them by race. But that argument merely illustrates a 

fallacy that pervades the agency’s entire argument on appeal, to wit: that it was Kaplan’s (or the 

district court’s) burden to show that Murphy’s testimony was inadmissible, rather than the 

EEOC’s burden to show that his testimony was admissible. The law says the contrary. See 

Nelson, 243 F.3d at 251; Fed. R. Evid. 702 Advisory Comm. Notes, 2000 Amendments (“the 

proponent has the burden of establishing that the pertinent admissibility requirements are met a 

by preponderance of the evidence”). 

The district court also found that the EEOC “present[ed] no evidence” that Murphy’s 

race-rating methodology “is generally accepted in the scientific community.” Op. at 16; see 
No. 13-3408 EEOC v. Kaplan, et al. Page 7 

generally Daubert, 509 U.S. at 593. On this point the EEOC offers no response—perhaps 

because, as the district court observed, “the EEOC itself discourages employers from visually 

identifying an individual by race and indicates that visual identification is appropriate ‘only if an 

employee refuses to self identify.’” Op. at 16. 

Finally, as an independent ground for excluding Murphy’s testimony, the district court 

found that “[t]here is no indication” that Murphy’s group of 1,090 applicants is in any “way 

‘representative’ of the applicant pool as a whole.” Op. at 18. Instead there is a strong indication 

to the contrary: Murphy’s group had a fail rate of 23.8%, whereas the GIS applicant pool had a 

fail rate of only 13.3%. On this point, suffice it to say that an unrepresentative sample by 

definition might not be representative of the respective fail rates of black and white applicants in 

the larger pool—and thus is not a reliable means to demonstrate disparate impact. 

We need not belabor the issue further. The EEOC brought this case on the basis of a 

homemade methodology, crafted by a witness with no particular expertise to craft it, 

administered by persons with no particular expertise to administer it, tested by no one, and 

accepted only by the witness himself. The district court did not abuse its discretion in excluding 

Murphy’s testimony. 

The district court’s judgment is affirmed.