US Department of Justice
Office of Community Oriented Policing Services
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How to Correctly Collect and Analyze Racial Profiling Data:
Your Reputation Depends On It!
Authors:
Joyce McMahon, Ph.D.
Joel Garner, Ph.D.
Captain Ronald Davis
Amanda Kraus, Ph.D.
Prepared by:
The CNA Corporation

How to Correctly Collect and Analyze
Racial Profiling Data::
Your Reputation Depends On It!
Authors:
Joyce McMahon, Ph.D.
Joel Garner, Ph.D.
Captain Ronald Davis
Amanda Kraus, Ph.D.
Prepared by:
The CNA Corporation

Suggested Citation
McMahon, Joyce, Garner, Joel, Davis, Ronald and Kraus, Amanda, How to Correctly
Collect and Analyze Racial Profiling Data: Your Reputation Depends On It!, Final
Project Report for Racial Profiling Data Collection and Analysis. (Washington, DC:
Government Printing Office, 2002).
This project was supported by Contract Number GS-23F-8096H by the U.S. Department
of Justice Office of Community Oriented Policing Services. Points of view or
opinions contained in this document are those of the author and do not
necessarily represent the official position or policies of the U.S. Department
of Justice.

TABLE OF CONTENTS
Letter From the Director. . . . . . . . . . . . . . . . . . . . . . .iii
About the Authors  . . . . . . . . . . . . . . . . . . . . . . . . . . v
Executive Summary  . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.0 Overview and Recommendations.......................................5
1.1 Overview and Scope.................................................5
1.2 Approach and Conclusions...........................................6
1.3 Recommendations ...................................................9
2.0 Introduction......................................................13
2.1 Background........................................................13
2.2 Specific Tasking..................................................13
2.3 Study Approach ...................................................14
2.4 Project Scope and Limitations.....................................14
3.0 Methodology.......................................................17
3.1 Overview of Issues................................................17
3.2 Selection of Participating Cities.................................17
3.3 Literature Review of Data Collection/Analysis Efforts.............18
3.4 Conferences With Subject Matter Experts and City Representatives  19
3.5 Site Visits/Technical Assistance .................................20
3.6 Subject Matter Expertise: Perspectives From NOBLE ................20
4.0 Literature Review of Data Collection and Analysis Approaches......23
4.1 Classification of Approaches and Findings.........................23
4.2 Beyond Comparison Groups: Bivariate Versus
Multivariate Methodologies........................................... 32
4.3 Recommended Analytical Approaches ................................43
4.4 Maximizing the Utility of Future Research ........................51
5.0 Findings From the Conferences.....................................53
5.1 City Representation...............................................53
5.2 Composition of Participating City Groups..........................53
5.3 Areas of Agreement................................................61
5.4 Sources of Disagreement...........................................62
5.5 Recommendations from Conference Participants......................63
6.0 Report on Site Visits.............................................69
6.1 Technical Assistance Visits ......................................69
6.2 Status of Data Collection Efforts.................................71
6.3 Overall Recommendations for Technical Assistance..................79

7.0 Subject Matter Expertise: Viewpoints From NOBLE...................81
7.1 Positives and Negatives of Data Collection .......................83
7.2 Interactions: Mayor, Police Chief, Media, Community ..............95
7.3 Recommendations: How to Eliminate Biased Policing.................97
7.4 Advice for Departments Accused of Racial Profiling................98
7.5 Why Some Chiefs Decline to Collect Data..........................100
7.6 Overall Recommendations..........................................102
8.0 Discussion and Conclusions.......................................105
8.1 Data Collection: Costs and Benefits .............................106
8.2 Technical Expertise Issues for Local Departments ................107
8.3 Leveraging Resources Via Outside Partnerships (e.g., Academic) . 108
8.4 Value of Objective Information Versus Anecdotal Information . .  109
8.5 Importance of Communication and Community Interactions ..........109
8.6 Recommendations for Further Study................................110
Appendices
A. Tables for Chapter 4..............................................113
B. Conference Agenda, August.........................................125
C. Conference Agenda, October .......................................127
D. Bibliography for CD of References.................................129
E. Recommendations: How to Eliminate Biased Policing
(Blindfolds for Justice) ............................................135
Bibliography ........................................................145

LETTER FROM THE DIRECTOR
Racial profiling is one of the most highly visible and important issues
facing law enforcement today. Recent surveys show that more than
60 percent of Americans believe that racial profiling exists. Because
of this widespread consensus among the public at large, the law
enforcement community is working directly and proactively to address
this issue. The mere perception of the existence of racial profiling can
have a profound negative impact on the level of public trust afforded
to the police.
One such negative impact is to compromise the mutual respect
between law enforcement and community members. This mutual
respect often represents significant efforts of both groups. The
public's perceptions of a law enforcement agency's commitment to
ethical policing and respect for those it serves can help keep honest
mistakes from becoming high-profile incidents. A reputation for
ethical and equitable enforcement of the law can go a long way
towards earning an agency the benefit of the doubt in difficult
situations.
Law enforcement agencies should work objectively to determine if
racial profiling exists within their departments to be able to take steps
to deal with the problem if it is found to be present and to address
the public perception of its existence. Through funding from the
Office of Community Oriented Policing Services (COPS Office), the
CNA Corporation developed this resource to help law enforcement
address racial profiling data collection and analysis. This publication
provides a summary of the many important methodological issues
surrounding this topic. In addition, it provides advice to law
enforcement practitioners on how to more accurately collect and
analyze racial profiling data in an easy-to-read and usable format.
The COPS Office has a tradition of supporting efforts to increase
public trust and police integrity. Reducing racial profiling and the
public's perception of it is a way to further not only that goal, but also
COPS' broader goal to advance community policing. This publication
is an important part of that tradition.
Sincerely,
Carl R. Peed
Director, Office of Community Oriented Policing Services

ABOUT THE AUTHORS
Joyce S. McMahon
Dr. Joyce McMahon is a Deputy for the Resource Analysis Division
with 14 years of experience at The CNA Corporation. Dr. McMahon
has been active in the field of economic analysis and evaluation for
over 25 years, and is an expert in applied econometric techniques.
She is widely experienced in program evaluation and has directed
a number of analytical evaluation studies for various government
agencies, including the Department of Justice, Veterans Affairs,
the Commission on National and Community Service, the Federal
Aviation Administration, and numerous DoD and Navy agencies. Dr.
McMahon earned her Ph.D. in Economics from Harvard University.
Before coming to CNAC, she taught at the University of Texas
-Arlington, Southern Methodist University, and the University of
MissouriColumbia, and consulted for the Department of Labor,
Office of the Inspector General.
Joel H. Garner
Dr. Joel Garner is the Director of Research at the Joint Centers
for Justice Studies, Inc. Between 1974 and 1990, he was a research
program manager at the National Institute of Justice. Dr. Garner
has published several reports and articles on the role of officer and
suspect race in the use of force by law enforcement officers. This
research has emphasized the importance of measuring police and
suspect use of force and the use of multivariate statistical approaches
to assessing the impact of arrest situations, officer characteristics and
suspect characteristics on the amount of force used. Dr. Garner was
also a research consultant to the New York State Attorney General's
report concerning the role of race in the stop and frisk practices of
the New York Police department and has advised the U.S. Department
of Justice's Bureau of Justice Statistics on the design of their national
survey of policepublic contacts.
Ronald L. Davis
Ronald Davis is a Captain with the Oakland Police Department
with more than 17 years of experience in most aspects of police
management. He is the former Region VI Vice President of the
National Organization of Black Law Enforcement Executives
(NOBLE) and the current chair of the NOBLE National Task Force
on Racial Profiling. He is also a member of the Race Relations
Committee of the National Commission on Police Integrity. Capt.
Davis has advised members of Congress on bias-based policing

and testified as an expert at the U.S. Senate Judiciary Subcommittee
hearings on racial profiling and the Congressional Black Caucus
hearings on police misconduct. He developed the first Bias-Based
Policing training course in the country and has advised numerous cities
and law enforcement agencies across the country on racial profiling
policy development and traffic stop data collection methodology and
analysis. Capt. Davis is the author of the article "Bias-based Policing,"
the NOBLE Report on Racial Profiling and the article, "Racial
Profiling: What Does the Data Mean?" He has been cited in hundreds
of news articles and appeared on Black Entertainment Television
(BET), Court TV, C-SPAN, CNN and ABC Nightline.
Amanda Kraus
Ms. Kraus is a research analyst and project director at CNAC. She is
a labor economist with expertise in conducting applied econometric
analyses in various contexts, and in support of both government
and corporate decision-makers. She also has research experience in
the economics of education. Ms. Kraus's field of expertise is the
role of education level and educational curricula on determining
an individual's occupational attainment and earnings. Ms. Kraus'
current projects include using survey and administrative data to
analyze the relative importance of different factors contributing
to the reenlistment decisions of Navy Sailors, and providing on-
going technical assistance to the US Navy's Recruiting Command.
Before coming to CNAC, Ms. Kraus was a market forecaster at a
large telecommunications company. Ms. Kraus holds an M.A. in
Economics from Cornell University, and will be awarded a Ph.D. in
May 2003.

EXECUTIVE SUMMARY
Project Summary
This project, conducted by the CNA Corporation (CNAC), focuses
on key issues regarding the collection of racial profiling data. The
specific objectives of this project were to select and provide technical
assistance to four police agenciesBaltimore, Phoenix, Chattanooga,
and St. Paulconduct a literature review and provide an assessment of
existing and planned data collection and analysis of techniques being
employed by police agencies.
Overview
More than 400 United States law enforcement agencies have
instituted traffic-stop data-collection measures and 14 states have
passed legislation mandating racial profiling policies. Polls indicate
that a majority of citizens believe that police departments engage in
racial profiling, while most police chiefs do not believe their officers
engage in racial profiling. This difference of perception, at times,
is a reflection of a fractured relationship between the police and
the community. Citizens who do not trust the police are less likely
to invest their time in understanding police policies, procedures, or
efforts to collect data. Police, on the other hand, feel they are likely
to be unfairly accused of racial profiling, and may be less enthusiastic
about pursuing their duties. Many departments have swiftly
implemented mechanisms to collect data to investigate allegations of
racial profiling, but too often base their conclusions on comparing
preliminary data on traffic stops to aggregate city demographics
without establishing credible benchmarks for comparison purposes.
These superficial evaluations are dangerous, in that they may foster
incorrect conclusions and generate inappropriate corrective measures.
CNAC conducted a literature review in which they discovered more
than 20 published reports that analyze more than three million records
of police stops from more than 700 law enforcement agencies.
Most of the analyses reported show that police traffic stops are not
proportional to the racial distribution of that jurisdiction's resident
population, but most studies do not conclude that the police are
engaged in racial profiling. No two studies used the same exact
design or comparison group. As a result, it was difficult for CNAC to
determine the extent to which the reported findings stemmed from
real differences in behavior or from differences in study measures
and methods. Thus, they concluded that more could be learned about
the nature and extent of racial profiling if future analyses were more
attentive, not simply to the comparison group issue, but to a series
of analytical issues that have either not been identified or addressed

adequately in prior research. CNAC identified five analytical issues that
would enhance future research: 1) base rates, 2) measuring race,
3) geographical and functional allocations of police operations,
4) multiple predictors of stops and searches, and 5) criteria for the
existence and extent of racial profiling.
CNAC Findings/Recommendations
 It does not matter how accurate data collection and analysis is
if the community does not feel engaged in the process. The
collection and evaluation of data, in and of itself, will not address
or defuse community frustrations.
 Data collection and evaluation is an appropriate way to address
the concerns of racial profiling. Anecdotal evidence is an
unreliable tool with which to make policy decisions.
 Data collection and evaluation should be carefully planned and
based on pre-determined questions. The data collection plan
should facilitate finding answers to those questions while also
recognizing the limitations of data collection and analysis.
 The data collection and evaluation plan should blend police
operational expertise with external research methods. Subject
matter experts from either side are likely to over-generalize the
questions and answers if working in isolation. Combining the
expertise of operational and research experts, working together, is
the best way to accomplish an accurate evaluation of the data.
 The partnership between operational police expertise and external
researchers should be established before the data collection begins.
This will allow police to have input on operational constraints, and
researchers to have input on what data will be required to reach
conclusions. If the wrong data are collected, the best analysis in
the world will be unable to reach useful or valid conclusions.
 Analytical methods should focus on accounting for the
complexities of police procedures and operational methods as
well as the characteristics of the city. Most cities have distinct
neighborhoods, and it is likely that a thorough evaluation will need
to reflect analysis at the neighborhood, area, region, or precinct
level.
 Analytical methods must consider multiple influences. In
research terms, this means using a multivariate analysis. A less
technical way to express this is to say that the impact of many

different influences must be jointly taken into consideration
before conclusions are reached. These might include, for
example, characteristics of the driving population, presence of
nearby cities/states/countries (transient populations), day-time
versus night-time stops, stops that are description-based (be on
the lookout for), stops of those on probation and parole, and
special programs such as seat-belt violations. Depending on
circumstances, these or other factors might merit consideration in
the determination of what can be learned from the data.
 All parties should understand that examining traffic stops is
unlikely to address the finer nuances of defining racial profiling.
We do not as yet have an accepted, official definition of racial
profiling, much less an operational definition that describes exactly
what data should be collected, how they should be collected,
and what type of analytical results would definitively identify
racial profiling. Until a basic overall definition is specified, the
examination of data to determine the existence or extent of racial
profiling will, of necessity, be open to interpretation by various
stakeholders. Our participants felt that the lack of a uniform
definition of racial profiling fosters alternative interpretations of
data, and suggested that a clear operational definition should be
sought.
 There should be clear guidelines on how information on racial
profiling should be usedwho will own it, who will be responsible
for using it, how confidentiality can be maintained, and how
frequently reports should be generated and released.
 If data collection is a job appropriate for a task force, then there
should be specific information about how to put together a task
force and make it work.
 Police departments need guidelines on how to establish
partnerships with university researchers, and guidance on the
appropriate roles for academic or public research groups to play.
 Police departments need guidelines on how to educate the
community regarding interpretations of the data and how data
should be released and presented to the community.
 Data collection and analysis can be costly, so if data collection is
mandated, it should also be funded. Without funding, competing
needs that are more directly related to traditional law enforcement
will almost always have higher priority.

1.0 OVERVIEW AND RECOMMENDATIONS
1.1 Overview and Scope
The Office of Community Oriented Policing Services (the COPS
Office) at the Justice Department tasked the CNA Corporation to
investigate technical data concerns with respect to the general issue of
racial profiling. Polls indicate that the majority of citizens believe that
police departments engage in racial profiling, while most police chiefs
do not believe their officers engage in racial profiling. Public media
sources have directed considerable attention to news coverage of
charges of racial profiling. Officers, on the other hand, feel that they
are doing good police work, and are not engaging in racial profiling.
These discrepancies raise a number of concerns. Specifically, if the
trust between police and the communities they serve is frayed, it
will become more difficult for the police to protect and serve their
communities. Citizens who view the police with distrust are less likely
to work together with officers to help establish safe neighborhoods
and control or prevent crime. In addition, if officers feel they are likely
to be unfairly accused of racial profiling, they may be less enthusiastic
about pursuing their duties.
Concerns about the use of race as a significant factor in police
decision-making (racial profiling or bias-based profiling) have caused
numerous police agencies to propose collecting data to investigate
the validity of the allegations. However, many people have jumped
to conclusions based on comparing preliminary data on stops to
aggregate city demographic data. These superficial evaluations are
dangerous, in that they may foster incorrect conclusions and generate
inappropriate corrective measures.
These issues are too important to be assessed based on anecdotal
evidence or incomplete analysis. Decisions about appropriate police
tactics and training are among the crucial considerations that will be
affected by the evaluation of the extent and nature of police profiling
patterns. It is vital that such evaluations be based on appropriate
methodological approaches, using objectively obtained data, and
comparing the data to appropriate benchmarks or comparison
guidelines. It is also important that the various stakeholder groups
agree on the basic concept of what they are trying to investigate. Until
there is agreement on an operational definition of racial profiling, it
will be very difficult to proceed with investigations that are designed
to look for and measure it.

It is also very important to protect and preserve trust between police
officers and the community members they serve. In this sense,
it is crucial that the dialogue between all parties be broadened to
encompass a full understanding of the scope of issues involved.
Community leaders, politicians, citizens, media representatives,
and police officers need to be talking to each other, not talking at
cross-purposes. All parties need to focus on the importance of the
issues being considered and make sure that they are using the same
descriptors to define racial profiling.
1.2 Approach and Conclusions
The COPS Office asked CNAC to investigate racial profiling
concerns, focusing on technical issues in assessing the existence and
scope of racial profiling. The following tasks were included in the
scope of work:
 Select a sample of police agencies to participate in a study of
profiling and data issues.
 Conduct a preliminary analysis of ongoing or proposed data
collection efforts.
 Hold two working conferences involving the selected agencies and
subject matter experts.
 Summarize the findings, methodological issues, and lessons
learned.
 Prepare a final report to COPS and the participating agencies.
This final report is primarily targeted toward police department
executives and operational data analysts, city officials, and potential
research partners. It is not intended to provide a primer in statistical
methods, although it offers broad operational guidelines. Rather than
provide an overly technical document (aimed primarily at professional
researchers), it seeks to provide a broad overview of information that
will prove helpful to a variety of users. Its intent is to allow readers
to understand the key points that confront communities and their
local law enforcement agencies with regards to racial profiling and
the collection of stop data. This report should offer guidance to law
enforcement and justice personnel, as well as government leaders who
generally oversee police agencies. Finally, this report may also be a
useful reference for community leaders and media representatives who
are addressing issues regarding the use of data collection and analysis
to examine racial profiling.
CNAC developed a list of cities that expressed interest in engaging in
this effort to examine racial profiling, data collection, and evaluation
efforts. It used a number of criteria to ensure that an appropriately
balanced mix of cities would be included, and that the cities would be

interested in, and able to consider using, technical assistance in further
developing their data collection and evaluation efforts. In conjunction
with the COPS Office, it selected Baltimore, Maryland; Chattanooga,
Tennessee; Phoenix, Arizona; and St. Paul, Minnesota.
CNAC also completed a literature review of racial profiling in the
context of data collection and evaluation findings. This review details
relevant studies that have been completed, but does not address
ongoing data collection or analytical efforts or studies that have not
been released in final form. It concluded from this review that many
different methodological approaches have been used to investigate
racial profiling. Most of the studies follow a single-variable design,
meaning that they investigate the influence of one variable on another
variable. The most common pattern is to collect data on traffic stops
in a city, and to compare the percentage of minority stops to the
percentage of minorities in the entire city. This type of approach is
far too simplistic, and it fails to incorporate information on police
operational procedures.
Specifically, most cities are characterized by distinct neighborhoods,
with different amounts of minority representation, crime rates, and
police presence. If minority neighborhoods are characterized by
below-average incomes and above-average crime rates, as is often
observed in urban areas, then police presence will be augmented in
these neighborhoods. This will lead to a bias in observed stops of
minority members, not necessarily due to racial profiling, but based on
disproportionate police presence in minority neighborhoods. Studies
that do not consider these and other police operational procedures,
along with additional specific city characteristics, will fail to accurately
assess the existence or extent of racial profiling or bias-based policing.
Four participant cities sent representatives to two conferences, each
held in Alexandria, Virginia at CNAC. Each city was represented
by three people who reflected alternative points of view within the
overall communitya senior member of the police department, a
union representative, and a community representative. CNAC also
arranged to have technical assistance provided by subject matter
experts, drawing from criminal justice experts and operational
expertise provided by the National Organization of Black Law
Enforcement Executives (NOBLE). The experts who attended
included Captain Ronald Davis of the Oakland (California) Police
Department, a Vice President of NOBLE; Chief of Police Jerry
Oliver of the Richmond (Virginia) Police Department; and Chief
of Police Leonard G. Cooke of the Portsmouth (Virginia) Police
Department, President of NOBLE. CNAC also conducted site visits
to talk to more of the police department representatives and data
evaluators in their respective cities.

The conferences revealed that, as expected, there are sharp differences
of opinion among and between the police, union, and community
representatives, and the operational experts. First and foremost, the
participants struggled with an operational definition of racial profiling.
It seems clear that racial profiling means different things to different
people, and that all parties must agree on a definition if meaningful
discussions are to occur. However, participants could not agree on a
definition that was mutually acceptable. Community representatives
could not agree regarding the merit of various definitions offered by
subject matter experts, including definitions proposed by Ramirez,
PERF, IACP, and NOBLE. Their recommendation was that
addressing the issue of a standard operational definition of racial
profiling is of critical importance, so that all parties can use this
definition as a starting point for discussion.
Although sharp differences were voiced, several themes emerged from
the overall discussion. In addition to a need for an external definition
of racial profiling, CNAC observed definite tensions between police,
union, and community representatives. In particular, it found that the
police rank and file feel that they are being asked to do good police
work, protect the citizens, arrest criminals, and prevent crime, but
are then being criticized for doing their jobs. It is very difficult to
disentangle the requirements to do thorough police work and at the
same time make certain that there is no activity that can take on the
appearance of racial profiling.
There is also general agreement that simply collecting data is
insufficient. Data that are collected must then be analyzed, and there
is a growing concern that many evaluation methods being applied are
neither systematic nor are they held to accepted analytical standards. In
addition, as the operational experts are quick to point out, collection
and evaluation of data in and of itself will not be enough. It is very
important that lines of communication and cooperation be opened
between police departments and community leaders and members.
Only with frequent and open interactions will there come movement
toward a common understanding of community frustrations and
police operational constraints.
CNAC found that the status of data collection and evaluation of racial
profiling can be characterized as incomplete at this point. Cities in
general appear to be working in two directions. First, they are working
to set up lines of communications and structures that foster ongoing
dialogues with community groups. These efforts will be very useful
to defuse tensions, restore trust, and sharpen the focus on profiling
issues. Second, many cities are engaging in data collection efforts

followed by data analyses. For this effort, the picture is still somewhat
unfocused. Most police departments do not have personnel who are
trained in analytical methods, and are unequipped to launch technical
evaluations of the data. It is important that all parties understand
that incomplete or superficial analyses will be counterproductive to
establishing a cooperative partnership between police agencies and the
community.
At the present time, CNAC found that the body of racial profiling
research provides an inadequate basis for setting public policy. Despite
the growing number of larger and more sophisticated studies, this
assessment is that there are too few studies, over too short a period
of time, with too diverse a set of findings, and with too many
methodological limitations.
This report investigates these and other issues in more detail. Chapters
two through eight review the background, discuss the conference
findings, and address the current status of investigations into racial
profiling using data collection and analytical methods. It offers
overall guidance on technical assistance for future data collection and
evaluation efforts, and make recommendations for various stakeholder
groups involving their future participation in, and responsibilities for,
evaluating racial profiling issues.
1.3 Recommendations
Based on CNACs findings and conclusions, the following is
recommended:
 It is very important that police agencies set up routine structures to
establish linkages between themselves and community members,
as well as other stakeholders. Open communications are extremely
critical. It does not matter how accurate data collection and
analysis are, if the community does not feel engaged in the
process. It is not enough to tell community members that their
concerns are not valid (if indeed that is the conclusion reached);
rather, the community must be brought into the picture and
allowed to have input into the overall process. The collection and
evaluation of data, in and of itself, will not address or defuse
community frustrations.
 Data collection and evaluation is an appropriate way to address
the concerns of racial profiling. Anecdotal evidence is an
unreliable tool upon which to make policy decisions. However,
in the absence of systematic and carefully crafted data collection
and analysis, policies will be driven by anecdotal evidence. The
resulting policy decisions may be inefficient at best, and at worst
may, in the end, prove counterproductive.

 Data collection and evaluation efforts should be carefully planned.
Participants should decide what questions they are trying to
answer, and then craft a data collection plan that will facilitate
finding answers to those questions. It is important to recognize
the limitations of data collection and analysis, and not expect that
it can address all possible questions and resolve all possible issues.
 The data collection and evaluation plan should, as much as
possible, blend police operational expertise with external research
methods. Police personnel are unlikely to have a background in
analytical research methods, whereas professional researchers are
likely to lack knowledge of operational police procedures. Either
party is likely to over-generalize the questions and answers if
working in isolation. Combining the expertise of operational and
research experts, working together, is the best way to accomplish
an accurate evaluation of the data.
 The partnership between operational police expertise and external
researchers should be established before the data collection begins.
This will allow police to have input on operational constraints,
and researchers to have input on what data will be required in
order to reach conclusions. If the wrong data are collected, the
best analysis in the world will be unable to reach useful or valid
conclusions.
 Analytical methods should focus on accounting for the
complexities of police procedures and operational methods, as
well as city characteristics. Most cities have distinct neighborhoods,
and it is likely that a thorough evaluation will need to reflect
analysis at the neighborhood, area, region, or precinct level. The
proper level will, of course, depend on specific city characteristics.
Because cities differ, analytical approaches may need to differ as
well.
 In addition, the analytical methods must consider multiple
influences. In research terms, this means using a multivariate
analysis. A less technical way to express this is to say that the
impact of many different influences must be jointly taken into
consideration before conclusions are reached. These might
include, for example, characteristics of the driving population,
presence of nearby cities/states/countries (transient populations),
day-time versus night-time stops, stops that are description-based
(be on the lookout for), stops of those on probation and parole,
and special programs such as seat-belt violations. Depending on
circumstances, these or other factors might merit consideration in
the determination of what can be learned from the data.

 Finally, all parties should understand that examining traffic stops
is unlikely to address the finer nuances of defining racial profiling.
There is not as yet have an accepted, official definition of racial
profiling, much less an operational definition that describes exactly
what data should be collected, how they should be collected,
and what type of analytical results would definitively identify
racial profiling. Until a basic overall definition is specified, the
examination of data to determine the existence or extent of racial
profiling will, of necessity, be open to interpretation by various
stakeholders. Participants felt that it was critically important for
all parties to reach an agreement on an official definition of racial
profiling.

2.0 INTRODUCTION
2.1 Background
The Office of Community Oriented Policing Services (the COPS
Office) at the Justice Department asked the CNA Corporation
(CNAC) to investigate technical data concerns with respect to the
general issue of profiling. Concerns about the use of race as a
significant factor in police decision-making (racial profiling, or bias-
based profiling) have caused numerous police agencies to propose
collecting data to investigate the validity of the allegations. Decisions
about appropriate police tactics and training are among the crucial
considerations that will be affected by the evaluation of the extent
and nature of police profiling patterns. It is important that such
evaluations be based on appropriate methodological approaches,
using objectively obtained data and comparing the data to appropriate
benchmarks or comparison guidelines.
The difficulties facing those investigating the existence of racial
profiling are compounded by a lack of agreement as to how to define
racial profiling. This extends beyond agreement on a formal, technical
definition. Even if there was an accepted standard definition of
racial profiling, there would still be the problem of determining how
to translate this definition into evaluating operational police tactics
and methods. In general, data collection efforts to investigate racial
profiling have focused on collecting, categorizing, and then analyzing
information, but they have not linked the evaluation of information to
a clear operational definition of racial profiling. This may help explain
the variety of conclusions that different research efforts find regarding
the issues of racial profiling or bias-based profiling.
2.2 Specific Tasking
To investigate racial profiling issues, COPS asked CNAC to:
1) Select a sample of police agencies to participate in a study of
profiling and data issues.
2) Conduct a preliminary analysis of ongoing or proposed data
collection efforts.
3) Hold two working conferences involving the selected agencies and
subject matter experts.
4) Summarize the findings, methodological issues, and lessons
learned.
5) Prepare a final report to COPS and the participating agencies.

2.3 Study Approach
In the first part of the study, CNAC developed a list of cities that
would be interested in engaging in this effort to examine racial
profiling, data collection, and evaluation efforts. A number of criteria
were used to ensure that an appropriately balanced mix of cities
would be included.1 It also needed to determine that the cities would
be interested in, and able to consider using, technical assistance in
developing their data collection and evaluation efforts. This list of
cities was submitted to the COPS Office for consideration before
being narrowed down to a final four.
1 The COPS Office established certain requirements, including not selecting
any city under investigation or judicial proceedings, or cities with data
projects previously concluded. In addition, these cities do not provide a
representative sampling; they merely offer a range of different viewpoints
and problems for consideration.
In the second part of the study, CNAC conducted a literature review
of racial profiling in the context of data collection and evaluation
issues. This review detailed the relevant studies that have been
completed, but did not generally address ongoing data collection or
analytical efforts, and also did not address studies that have not been
released in final form. A number of analytical efforts are underway
where results have been announced in the media. It did not evaluate
efforts that are incomplete, or have not yet been published, and did
not evaluate media discussions of pending reports. Those mostly
interested in operational issues can scan this literature review.
CNAC then conducted two conferences in Alexandria, Virginia. Each
city was represented by three people who reflected alternative points
of view within the overall community. The points of view are those
of the police department, union representatives, and people in the
community. CNAC also arranged to conduct site visits to talk to more
of the police department representatives and data evaluators in their
respective cities.
Finally, it synthesized the findings from the above steps into a final
report. This report addresses the current status of investigations into
racial profiling using data collection and analytical methods, and offers
overall guidance on technical assistance for future data collection and
evaluation efforts.
2.4 Project Scope and Limitations
In this project, CNAC considered only city police departments and
focused primarily on traffic stops. Although the literature search
covers other topics in racial profiling, touching on state police studies
for example, the primary focus in this effort is city police departments
and community interactions. It did not evaluate drug or weapons
smuggling interdiction efforts. It is important to note that for other
environments and tasks, such as state police responsibilities, there

may be other analytical problems and tools that will be appropriate
to consider, as well as other issues and alternative concerns and
constraints.
In addition, studies of racial profiling generally evaluate data that
are available for collectionnot data that would result from designed
experiments. In other words, researchers may want to observe the
characteristics of those segments of the population who break laws
and violate regulations. However, they are often constrained to readily
observable data, because they lack the resources to design experiments
or collect specific data to establish more precise comparison
populations.
Finally, the cities that are investigating racial profiling have to work
with many limitationsfunding, time to devote to additional data
collection and investigation, computer and manpower constraints,
practical and political constraints, and media and community
perceptions. These and other constraints will limit the scope of
effort that cities can mount, and the scope of effort that individual
communities demand.

3.0 METHODOLOGY
3.1 Overview of Issues
Based on a Washington Post survey,2 52 percent of African-American
males believe they have been victims of racial profiling, while a
Gallop poll indicates that about 60 percent of Americans believe
racial profiling exists.3 Over the past few years, there has been intense
national debate on whether racial profiling is real or perceived, and
initial data collection and evaluation efforts have provided fuel for
this debate. More than 400 United States law enforcement agencies
have instituted traffic-stop data-collection measures, and 14 states
have passed legislation mandating racial profiling policies. In 2001,
Congressman John Conyers introduced the End Racial Profiling Act,
to mandate data collection on racial profiling for agencies receiving
federal funds. Similar bills have also been introduced in both the
House and Senate.
Many people feel that data collection provides critical input to putting
an end to racial profiling, while others view the role of data collection
as largely symbolic, indicating a commitment to addressing community
needs and concerns. Others cite the lack of credible benchmarks,
or comparison data, as reasons to avoid engaging in data collection.
As a result, data collection and analysis have become somewhat
controversial concerns in the overall issue of racial profiling. This
overall tasking involves providing technical guidance regarding these
matters in order to assist agencies that are trying to collect and analyze
data, as well as assist agencies considering whether to undertake data
collection and evaluation projects.
3.2 Selection of Participating Cities
The first task from COPS directed CNAC to "select a sample of
police agencies to participate in a study of profiling and data issues."
It worked with personnel from the National Organization of Black
Law Enforcement Executives (NOBLE) to develop a list of cities
that would meet the criteria identified by the COPS Office and who
expressed an interest in participating. Although about 10 cities passed
the initial screening, the COPS available funding line supported
involvement with only four cities. Therefore, CNAC worked with
the COPS Office to validate each proposed city and select the final
candidates for inclusion.
2. Washington Post article dated June 21, 2001.
3. 1999 Gallup Poll.

The initial evaluation criteria included:
 Geographic diversity
 Potential for union and community involvement
 Having a data collection process getting underway or in progress
(but not yet completed)
 Not being under a court order mandating data collection
 Willingness to commit to sending department, union, and
community representatives to two national conferences.
CNAC and the COPS Office jointly selected the final list of cities,
which included Baltimore, Maryland; Phoenix, Arizona; St. Paul,
Minnesota; and Chattanooga, Tennessee. Among the criteria used
to help make the final selection were geographic diversity as well as
diversity in city size and composition. It wanted to include cities facing
a variety of challenges rather than engage very similar cities.
3.3 Literature Review of Data Collection and Analysis
Efforts
The second part of the study focuses on a literature review of racial
profiling, in the context of data collection and evaluation issues and
findings. This review also focused on determining the relevant issues
in setting up data collection efforts, as well as assessing the competing
merits of various evaluation approaches. An overall review of the
state-of-the-art profiling research efforts and findings is an appropriate
first step to making recommendations as to future study designs and
evaluating the relative merits of alternative investigative approaches.
There are presently more than 20 published reports that analyze more
than three million records of police stops from more than 700 law
enforcement agencies. Even more studies are in progress and should
be completed in the near future. In Chapter 4, it summarizes the
completed studies and compare and contrast the characteristics of the
nature of the data collected, the analyses conducted, and the findings
reported. Specific details and comparisons between the studies are
provided in an appendix as referenced in Chapter 4. Full citations of
the studies are referenced in the Bibliography. This chapter is most
useful for those interested in data analysis considerations and may be
skimmed by those more interested in operational issues and lessons
learned.

3.4 Conferences with Subject Matter Experts and City
Representatives
CNAC held two conferences to bring together the city representatives
and various subject matter experts. The National Organization of
Black Law Enforcement Executives (NOBLE) provided subject
matter experts for the conferences, including Captain Ronald Davis
of the Oakland (California) Police Department (a Vice President of
NOBLE), Chief of Police Jerry Oliver of the Richmond (Virginia)
Police Department, and Chief of Police Leonard G. Cooke of the
Portsmouth (Virginia) Police Department (President of NOBLE).
In addition, Maurice Foster, Executive Director of NOBLE and
Program Coordinator Torian Lee, also attended and participated
in part of the meetings. Finally, Dr. Joel Garner, Director of the
Joint Centers for Justice Studies, Inc., provided expertise from his
extensive experience with the Department of Justice and analytical
investigations in justice studies.
In structuring the conferences, CNAC asked the police department
representatives to take the lead in presenting and leading discussion
about the current situation in each city. This status included details
on what each city is doing with respect to addressing profiling issues
and gathering data to investigate concerns. It is important to discuss
what event or issue has led each city to become involved in this
process. Finally, it is important to learn what outcomes are being
sought from the profiling investigation and data gathering processin
other words, what specific questions are being asked, and how are the
cities planning to gather and process data to answer these questions?
The first conference focus targeted developing an understanding of
the underlying issues and concerns across the four cities, looking for
commonalities and critical differences.
The second focus of the conferences addressed investigation of
technical issues in data-gathering, evaluation, and interpretation.
This entailed a concentration on analytical methods and evaluation
techniques, with respect to setting up some guidelines for appropriate
ways to investigate. For example, one issue is the mapping of types of
questions to appropriate data to investigate those questions. In other
words, there are different approaches to gathering different types of
data. It is important to set up the framework of data collection on the
basis of what types of data willand what will nottend to support
specific types of investigations. In this context, all of the participants
served in the role of operational experts, sharing information on
lessons learned and operational constraints observed based on current
and prior experiences in this area.

The third focus of the conferences allowed the participants to work
together with each other and with outside subject matter experts to
refine their analysis plans. Each city has a current plan for gathering
and evaluating data. Based on the shared experiences and analytical
discussions ranging across the group of participants and analysts,
the city representatives learned things that will foster refining and
refocusing investigations, modification of data-gathering plans, and/or
altered expectations with respect to the best use of the data being
collected or planned to collect. Investigation into profiling issues is an
ongoing effort, and the interaction of operational and subject matter
experts should yield additional information that will help planners
better design and guide current and future inquiries into profiling
concerns.
The findings and recommendations from the conferences are
discussed in Chapter 5. The structure of the conferences and the small
size of the overall participant group allowed for very rich interactions
among the participants and invited subject matter experts.
3.5 Site Visits/Technical Assistance
CNAC also conducted site visits to talk to more police department
representatives and data evaluators in their respective cities. This
allowed it to develop more insights into local conditions and issues
relevant to specific locations as well as to learn more about local
reactions to issues of racial profiling, data collection, and evaluation
approaches. It assessed more of the technical assistance needs by
talking to department representatives tasked with developing data
collection plans and evaluation approaches. These visits were not
designed to help set up and execute a data collection plan, but were
geared toward giving technical advice for plans that were already
under way or being considered. The site visits served as an extension
of the conference participation, providing opportunities to talk about
technical aspects with representatives who had not attended the
conferences.
3.6 Subject Matter Expertise: Perspectives from NOBLE
CNAC relies on subject matter experts provided by NOBLE to
provide background and context for the operational issues of police
tactics and behavior. This allows it to blend the NOBLE perspective
on racial profiling issues with the operational point of view of
police officers actively working in the field, thus bringing a unique
perspective to this evaluation. As excerpted from an article by Captain
Ronald Davis:4
4. Racial Profiling: "What Does the Data Mean?" A Practitioner's Guide
to Understanding Data Collection & Analysis, by Captain Ronald Davis,
written for NOBLE.

On May 3, 2001, NOBLE issued its national report5 on racial
profiling. The NOBLE report identified racial profiling as a
symptom of Bias-Based Policing, which is defined as:
The act (intentional or unintentional) of applying or incorporating personal,
societal or organizational biases and/or stereotypes in decision-making, police
actions or the administration of justice.
NOBLE believes bias-based policing is a systemic problem in
the industry, requiring strategic and comprehensive strategies to
affect systematic reform. Effective data collection and credible
data analysis is a necessary "tool" in reform. The NOBLE report
supports racial profiling legislation that requires data collection
and analysis, training, and the implementation of racial profiling
policies.
By relying on the expertise of NOBLE operational officers, primarily
Captain Ronald Davis, the NOBLE racial profiling point of view
is linked with the practical operational issues as observed by active
officers in the field.
Captain Davis brings another aspect to this report. By offering an
example of how the Oakland Police Department has approached
collecting and analyzing data, it articulates some of the pitfalls of
overly simplified analysis using actual data rather than hypothetical
examples. In addition to providing a powerful example of real-world
analytical issues, Captain Davis offers a police department operational
approach to multivariate analytical methodsessentially a linear
stepwise approach via nested pairwise comparisons. Although this
approach does not achieve the power of simultaneously examining
and disentangling multiple influences, it does provide a logical and
systematic approach in lieu of multivariate research expertise. The
operational stepwise approach approximates more conventional
multivariate research methods and may be more readily understood by
police department personnel, community, and media representatives.
5. Racial Profiling: A Symptom of Bias-Based Policing.

4.0 LITERATURE REVIEW OF DATA
COLLECTION AND ANALYSIS APPROACHES
Following the calls for increased data collection on how and when
the police make traffic stops, a number of reports on racial profiling
have been made public. CNAC identified two dozen published reports
that analyze more than three million records of police stops from
more than 700 federal, state, and local law enforcement agencies.6 (See
Table 4.1 in Appendix A for a bibliographic listing of these reports.)
These reports can be brief accounts or lengthy discussions that
involve complex statistical analyses and interpretations of findings.
There are important differences in how the report authors designed,
implemented, and interpreted these studies, and these differences
can have subtle (and sometimes not so subtle) implications for the
appropriate contribution of these studies to the public discussion of
bias-based policing.
6. This listing does not include secondary sources, such as press accounts
of reports that have not been made public.
In this chapter, the nature of the published reports and substantive
findings that have been reported are summarized. It compares and
contrasts the characteristics of the data collected, analyses conducted,
and the findings reported. Based on the review of the existing studies,
it offers recommendations for guiding analytical efforts to use data
collection to assess racial profiling.
4.1 Classification of Approaches and Findings
The substantive findings from the available reports on racial
profiling are diverse. Their assessments of the average annual risk
of being stopped by the police while driving a vehicle vary greatly
by jurisdiction, law enforcement agency, and methodology used.
Most of the analyses reported show that police traffic stops are not
proportional to the racial distribution of that jurisdiction's resident
population, but most studies do not conclude that the police are
engaged in racial profiling. In addition, every study that examined
police searches found some racial disproportionality, at least in
certain types of police searches, but the majority of the report
authors concluded that police search behavior does not indicate racial
profiling.
Methodological Strengths and Weaknesses
Some reports assert that the nature of the methods used and the
findings generated provide definitive proof that the law enforcement
agencies studied do (and do not) engage in racial profiling. Other
studies express considerable skepticism that the data, methods, and
analyses used adequately capture the nature of police behavior. This
report is not designed to resolve either the substantive debate about

racial profiling or the questions about the reliability of prior research
methods. The goal is to illuminate the nature of these studies so that
the general public, the law enforcement community, and the research
community can better appreciate the strengths and weaknesses of this
body of research and improve the value and utility of future studies
of the nature of police public contacts.
The assessment is that all of these reports have strengths and
weaknesses and that no one study or study design is likely to provide
satisfactory answers to the central questions raised in the public
discussion over bias-based policing. Each of the existing studies
contributes something to understanding the day-to-day interaction
between citizens and their law enforcement officials. Comparing and
contrasting these studies is designed to increase an appreciation for
the extent to which data collection and analysis can and cannot:
 Establish the existence and amount of racial profiling.
 Diagnose those aspects of policing that appear to be the most and
the least problematic.
 Indicate the appropriate strategies for improving police public
contacts, stops, and searches in the future.
At the present time, this body of research provides an inadequate
basis for setting public policy. Despite the growing number of larger
and more sophisticated studies, the assessment is that there are too
few studies, over too short a period of time, with too diverse a set of
findings, and with too many methodological limitations. Because all
studies have some methodological limitations, CNAC recommends
caution in using the findings of the available research. Future research
reports are likely to be more valid and reliable and to be of greater
use to the public, especially if they more consistently apply established
standards of social research and analysis.
4.1.1 Study Characteristics
The completed studies on racial profiling display many similarities (see
Tables 4.14.4).7 Of the 24 reports reviewed here, most use official
police records (23) of a single municipal (10) or statewide police
agency (11) to compare the racial characteristics of motorists stopped
(19) or searched (17) by the police with the racial characteristics of
residents as reported in the U.S. Census (14). Among these reports,
however, there is great variability in the scope and depth of the
analyses conducted. Two reports (Cox et al., 2001; Missouri Attorney
General, 2001) present information from most law enforcement
agencies within a single state and one study (Langan et al., 2001) uses
a representative sample of households to examine all police public

contacts in the U.S. Lamberth's 1994 study of the New Jersey State
Patrol covers 25 days and includes information about fewer than 3,000
traffic stops on one part of one roadway.
7 The data tables for Chapter 4 are included in Appendix A. Some summary
tables are included in the text.
The report by the California Highway Patrol covers 10 months and
more than 2.5 million traffic stops. Eleven reports employ data on
more than 100,000 traffic stops. The smallest study (Lamberth, 1996)
involves 823 traffic searches along the I-95 corridor by the Maryland
State Police during a 21-month period in 1995 and 1996. Twelve
reports are based on data compiled over a period less than 12 months,
six reports use exactly 12 months worth of data, and six reports cover
more than 12 months of police activity. Four studies include police
public contacts not involving vehicles; one of those studies (Spitzer,
1999) investigates pedestrian stops exclusively.
Sixteen studies address both traffic stops and searches. Four studies
collect and analyze data about traffic stops but do not analyze data
about traffic searches. Three studies investigate searches conducted
during traffic stops but not the traffic stops. The California Highway
Patrol report (California Highway Patrol, 2000) includes a wide
variety of police public contactsarrests, citations, written notice of
correction, warnings, motorist services, and collisions. The report by
the Baltimore Police Department includes information on traffic and
non-traffic stops.
Perhaps the most distinctive study is the nationally representative
survey of households conducted by the U.S. Census Bureau for the
Bureau of Justice Statistics (BJS) (Langan et al., 2001). It does not rely
on official records of any law enforcement agency. During six months
of 1999, a special set of questions about police public contacts was
added to the National Crime Victimization Survey. This survey was
completed by 80,543 residents, more than 20,000 of whom had some
sort of face-to-face contact with the police in the previous 12 months.
Because of its design, the BJS survey is based on reports by the
public, not by police officers or police agencies. Another unique aspect
of the BJS design is that it produces direct measures of the racial and
other characteristics of individuals who did not have contact with the
police. The BJS survey data records the nature of the police contact
and can distinguish between contacts initiated by the public or by the
police, contacts made by victims of crimes and contacts made when
the police consider the individual a suspect in a crime or a traffic
offense. All of the other studies of racial profiling use official records
of police stops (or police searches) but do not record any information
about specific individuals who could have been stopped but were not.

This is an important limitation of all the studies using official records
of police stops.
The nature of the BJS survey also captures a wide variety of
information about the nature of the contacts between law
enforcement officers and suspects. This survey asks whether the
individual was searched, whether any contrabandtypically illegal drugs
or weaponswere found, whether the individual was arrested and
whether the police used force. Six of the studies using official police
records report if contraband was found, and seven studies report if
the suspect was or was not arrested. Only the BJS study reports if the
police used force.
Not surprisingly, every study uses the race of the suspect in its
analysis, though the nature of the race categories varied from one
study to another. The Florida Highway Patrol reports a separate
analysis based on suspect Hispanic ethnicity, whereas other studies
use Hispanic as a racial category. None of the studies employ all
the racial categories used by the U.S. Census or consider individuals
who self-identify as belonging to more than one racial group. Ten
studies compare the proportion of male and female suspects who are
stopped, and seven of those ten also report the proportion of stops
by various age categories. Four of the studies incorporate information
about the characteristics of individuals with driver's licenses or how
much the amount of driving varies by age, race, and sex. Five of
the racial profiling analyses record whether the person stopped is a
resident of the jurisdiction being studied, but none of these reports
conducts separate analyses for residents and non-residents.
Another important characteristic is the nature of the collaboration
between the agency being studied, other government agencies,
and independent researchers. Local police departments studied
issued ten of the reports, but two of these reports (San Diego
Police Department, 2001; Carter et al., 2000) have clear indications
that academic researchers played a major role in the analysis and
presentation of the data analysis. In eight other studies, independent
researchers appear to be the sole authors of the report. State-level
officials produced the reports about state and local law enforcement
agencies in Connecticut, Missouri, New Jersey, and New York, but all
but the New Jersey report identify academic researchers as the primary
authors or consultants. Litigants in suits against law enforcement
agencies originally prepared reports in Maryland and New Jersey
(Lamberth, 1994, 1996). At least one report (Knowles and Persico,
2001) was produced by social scientists without any apparent contact
with the studied department.

Four studies (Missouri Attorney General, 2000; Institute on Race and
Poverty, 2000; Langan et al., 2001; Washington State Patrol, 2001) used
estimates of the racial composition of the driving-age population,
and four studies (Lamberth, 1994, 1996; Greenwald, 2001) produced
independent surveys of the racial composition of drivers at certain
locations and times. Greenwald also observed the race of drivers at
driving while intoxicated (DWI) stops and conducted a telephone
survey to check the officially recorded race and sex of the driver. The
BJS survey did not ask its respondents about driving behavior but
used an independent survey of driving behavior generated by the U.S.
Department of Transportation to construct estimates of the racial
composition of the driving population.
The authors of these reports chose to employ a variety of study
designs; in fact, no two studies used the same exact design. CNAC
suspects that future research will also display similar innovation
in study designs depending upon the specific concerns of local
jurisdictions, the nature of the available data, and the time and
resources available to conduct the research. The designs chosen have
implications for the types of data analyses that can be conducted and
the meaning of the substantive findings of the individual reports.
4.1.2 Reported Findings
This section summarizes how the reports address two central
questions in the public debate over racial profiling: Is there evidence
of racial profiling in making traffic stops or in conducting searches?
These reports provide a wide range of answers to these questions
(see Tables 4.5-4.6). In three jurisdictions (New Jersey: Lamberth,
Richmond, St. Paul), there are findings of racial profiling in traffic
stops, and one (New York City) finds racial profiling in non-traffic
stops. In two jurisdictions (Missouri and North Carolina), there is
mixed evidence regarding the existence of racial profiling in traffic
stops. In nine jurisdictions (California, Connecticut, Florida, Lansing,
Oakland, Sacramento, San Jose, Texas, and Washington State),
analyses do not find evidence of racial profiling in traffic stops. In
three jurisdictions (New Jersey Attorney General, San Diego, and the
United States), there are reports that the evidence is insufficient to
determine whether there is racial profiling or not. Reports from three
other jurisdictions (Baltimore, Chattanooga, and Michigan) make
no statements about what their data analyses mean, and the three
reports about Maryland do not address the issue of traffic stops.
Summary Table 4A categorizes the results of these and the following
comparisons.

Summary Table 4A
Summary Statement of Reported Finding for Stops and Searches by
Jurisdiction (and Author)
Type of Finding
Stops
Searches
Racial Profiling
Stops:
New Jersey (Lamberth: I-95)
New York City
Richmond
St. Paul
Searches:
Maryland (Lamberth: I-95)
New Jersey (NJAG)
St. Paul
Washington State
No Racial Profiling
Stops:
California
Connecticut
Florida
Lansing
Oakland
Sacramento
San Jose
Texas
Washington State
Searches:
Connecticut
Lansing
Richmond
Sacramento
Mixed Evidence
Stops:
Missouri
North Carolina
Searches:
Maryland (Knowles and
Persico)
Missouri
North Carolina
Cannot Determine
Stops:
New Jersey (NJAG)
San Diego
United States
Searches:
Oakland
San Diego
United States
No Statement
Stops:
Baltimore
Chattanooga
Michigan
Searches:
Baltimore
Maryland (Lamberth: Not
I-95)
Michigan
Texas
Issue Not Addressed
Stops:
Maryland (Knowles and Persico)
Maryland (Lamberth: Not I-95)
Maryland (Lamberth: I-95)
Searches:
California
Chattanooga
Florida
New Jersey (Lamberth: I-95)
New York City
San Jose

There is similar diversity in the findings about the existence of racial
profiling in searches. In the reports on four jurisdictions (Maryland:
Lamberth, New Jersey Attorney General, St. Paul, and Washington
State), the authors say that there is evidence of racial profiling in
traffic searches. In four other jurisdictions (Connecticut, Lansing,
Richmond, and Sacramento) the analyses did not find evidence
of racial profiling in searches. Mixed evidence for and against the
existence of racial profiling in search behavior was found in three
jurisdictions (Maryland: Knowles and Persico; Missouri; and North
Carolina). Three analyses (San Diego, Oakland, and the United
States) find insufficient evidence to make a determination. Six studies
(California, Chattanooga, Florida, New Jersey: Lamberth: I-95, New
York City, and San Jose) do not address the issue of searches at all.8
In summary, by a margin of nine to four, more studies report that
their data collection and analysis lead them to conclude that they have
not found racial profiling with respect to traffic stops, with two studies
reporting mixed support for this hypothesis. On the issue of racial
profiling in traffic searches, the study count is a little more evenly
matched. Four studies report racial profiling, four report no racial
profiling, and three indicate mixed findings.
Strengths and Weaknesses of Counting Reports
Counting studies is a common approach to summarizing prior
research. The basic value of a study count is that it produces a
simple, easily understood summary of the literature. Each publication
is counted equally, and the general nature of what can become a
large number of reports is easily and accurately conveyed. By itself,
however, this approach has been found to be unsatisfactory (Cooper
and Hedges, 1994). As in the literature on racial profiling, study
findings rarely provide a clear and consistent answer to the most
important questions. In addition, simple counts provide limited
information about the relative value of individual studies or the body
of published research, and offer little guidance on what has been
learned by the prior studies that might enhance the value of future
research. Moreover, there are several technical reasons that limit the
value of simple counts, even when the findings are more consistent.
For instance, as in this body of research, a large proportion of the
studies do not reach a conclusion. Six of the reports either do not
state a conclusion or explicitly say that their study design is unable to
support a conclusion. Seven studies reach no conclusions about racial
profiling in traffic searches.
8 This categorization of the substantive findings of these reports is
presented in tabular form in Table 4.54.6. The exact text of the
narrative in each report used to determine the conclusion reached
about the existence of racial profiling in traffic stops and in
traffic searches is also presented in these tables.

Study Designs and Research Methods
Had all or most of these studies reached similar conclusions regarding
racial profiling, the methodological details of these studies would be
of less concern to public policy-makers, police professionals, and
concerned members of the community. However, the mixed findings
and the hesitance of some authors to draw conclusions means that
the nature of the samples obtained, the measures used, the analyses
conducted, and the study interpretations take on more importance.
The studies on racial profiling vary greatly in the level of detail and
methodological rigor of the analyses conducted. Some texts on how
to summarize research go so far as to advise excluding reports that
do not meet certain methodological standards (Sherman et al., 1998).
Although there are no universal or absolute standards for research
methodologies, there are a variety of generally accepted conventions
about the relative strengths and weaknesses of alternative research
designs. For instance, studies with larger and more representative
samples drawn from several jurisdictions using a variety of common
measures and testing a number of competing hypotheses are generally
preferred over studies that use small or unrepresentative samples from
one jurisdiction (or part of one jurisdiction) and are limited to testing
a single hypothesis.
The studies reviewed here vary greatly in the size and representative
nature of their samples, in the number and commonality of the
measures used, and in the methods for testing competing hypotheses
about how and why the police make traffic stops and traffic searches
(Tables 4.7-4.8). For example, one study of racial profiling by the
State Police in two townships in New Jersey analyzes 823 searches
conducted over a 21-month period; the BJS representative sample
of U.S. households provides the basis for estimating the racial
characteristics of more than 1.2 million searches by the police. A
research summary that did not address such vast differences in sample
sizes would not properly reflect the nature of police behavior.
In addition to the differences in the size and scope of the research,
the substantive conclusions of these reports stem from comparing
the racial distribution of traffic stops and searches with a variety
of comparison groups, such as the resident population, the driving
age population, the population that owns motor vehicles, the
population that is violating traffic laws, the population involved in
traffic accidents, and the population identified as criminal suspects
or arrested for crimes. As displayed in Table 4.9, most studies use
just one comparison group and that tends to be the total resident
population of the jurisdiction under study. Some studies use several

comparison groups and, on occasion, they report different conclusions
depending upon which comparison group is used. For instance, the
BJS national survey of police public contacts compares traffic stops
with both the resident population and with the population that owns
automobiles. These comparisons can generate divergent results. For
example, in the BJS report, resident Whites above driving age have a
higher rate of being subjected to a traffic stop than resident driving
age Blacks, but Blacks with a driver's license have a higher rate of
being stopped by the police than Whites with a driver's license.9
No single comparison group is used consistently across all the
available studies, and the lack of commonality limits our ability to
summarize this body of research. Because of the dissimilarities
in comparison groups and other measurement and analytical
considerations, CNAC cannot determine the extent to which the
reported findings in Tables 4.5-4.6 stem from real differences in
behavior in these jurisdictions or from differences in study measures
and methods.
The studies also vary in how information about a comparison group is
compared to traffic stop data. Twelve of these reports relied on simple
bivariate comparison of the racial distribution of police stops to the
racial distribution of the resident population. Another five reports also
make bivariate comparisons but substituted the racial distribution of
the population of driving age or the population of individuals with
driver's licenses for the racial distribution of residents. Eleven of the
reports also produced bivariate comparisons of the age and sex of
the persons stopped but generally do not address the meaning of age
or sex differences or the implications of age or sex differences for
reported race differences. For three jurisdictions (Maryland: Knowles
and Persico, New York City, and Richmond), analyses used suspect,
officer, and encounter-level measures to produce multivariate statistical
tests of the effects of race when the effects of other encounter
characteristics are included in the analysis.
Many of the prior studies have recognized some of the difficulties in
obtaining proper comparison groups and in conducting appropriate
statistical tests of the effect of race on stops and searches. Some of
these studies determined that, since their comparison groups were not
very good, no conclusions at all could be drawn from their analyses.
A second group of studies did not appear to recognize the nature and
extent of these analytical difficulties and reached conclusions in spite
of the potential limitations of their data or their analyses.
9 Table 4.9 also reveals that several studies (Baltimore, Cranbury and
Moorestown, New Jersey, and the Knowles and Persico analysis of traffic
searches in Maryland) do not use comparison groups at all. They either
draw no conclusion, draw a conclusion from a simple count of traffic stops,
or conduct analyses limited to the information that is available about
the nature of the traffic stop.

A third group of studies attempted to address the problem of
identifying appropriate comparisons by using a number of different
comparisons. This third group frequently reports the extent to which
the results obtained are consistent, regardless of the comparison
group used. CNAC recommends the third approachusing multiple
comparison groupsas more likely to be informative about the actual
relationship between alternative measures and methods. It does not
recommend that studies be undertaken whose designs are so weak
that the authors assert that the findings are not sufficiently strong
to support even a tentative conclusion. Similarly, readers should be
skeptical of studies where the authors state firm conclusions but do
not identify the likely strengths and potential weaknesses of their own
or alternative designs.
4.2 Beyond Comparison Groups: Bivariate versus
Multivariate Methodologies
Several reports (Zingraff et al., 2000; Walker et al., 2001) refer to
the comparison group issue as the "denominator" problem, as if
the primary analytical issue in this research was one of long division
or finding just the right measure for the denominator. Although
the concern over the appropriate set of comparisons is warranted,
this focus is, we think, too narrow. Even if every prior study had
used a universally agreed upon comparison group, there would still
be substantial uncertainty about the meaning of the data analyses
conducted.
It is more likely to improve the understanding of the nature and
extent of racial profiling if future analyses are more attentive, not
simply to the comparison group issue, but to a series of analytical
issues that have either not been identified or have not been addressed
well in prior research. This report identifies the most important issues
and suggest ways in which future analyses might produce a better
understanding of the nature and extent of racial profiling. These
issues fall into five general categories:
 Base Rates
 Measuring Race
 Geographical and Functional Allocations of Police Operations
 Multiple Predictors of Stops and Searches
 Criteria for the Existence and Extent of Racial Profiling.
Attention to these analytical issues will enhance the value of future
research to the participating police agencies and to the communities
they serve.

Standardized Base Rates
Most of the prior research has focused considerable attention upon
identifying differences in the rates at which Blacks, Whites, and
other races are stopped and searched by the police. This focus has
obscured an important aspect of police public contactsthe base rate
at which all individuals are stopped or searched by the police in that
jurisdiction. Tables 4.7-4.8 construct three base rates for police stops
and for police searchesthe number of stops per year, the number of
stops per day, and the number of stops per resident in a year.
These rates vary greatly from one study to another and by the type of
rate used. For instance, the data collected in Baltimore during the first
six months of 2001 can be used to estimate that the police department
makes approximately 179,778 stops in a year, or 492 stops every day.
Using 2000 census figures, the total number of stops is equivalent to
27.6 percent of the population of Baltimore. Because the Baltimore
data distinguish between stops of Baltimore residents and stops of
other persons, it is easy to construct the base rate for residents being
stopped in Baltimore of 24.3 percent. In most jurisdictions, however,
it is not possible from the published data to separate out stops of
residents from stops of non-residents. Therefore, the stop rate figures
for other jurisdictions in Table 4.7 are constructed by dividing all the
stops of both residents and non-residents by the population figures
for residents.
In addition to base rates for stops, several base rates can be
constructed for police searches. Table 4.8 displays this information
for the 19 jurisdictions for which search information is available. The
base rate for searches in Baltimore is only 4.2 a day, and the number
of searches in one year is equivalent to 0.2 percent of the population
of Baltimore.10 In addition, according to official police records, less
than one percent of all stops in Baltimore result in a search. Other
studies report higher and lower base rates of stops and searches. The
early reports about racial profiling in Maryland, for instance, have base
rates of less than 1.5 searches per day, a relatively low rate among
the studies summarized here, and one that is not consistent with the
anecdotal accounts of minority drivers being stopped "every day."
10 This base rate is technically not a person's risk of being stopped,
because during the study period some people were stopped more than once.
Lansing, Michigan appears to have a relatively high base rate of two
searches for every 100 residents. The Lansing base rate for police
stops is also high. This may reflect something about the nature of
policing in Lansing or that the home of the state capital and Michigan
State University may have a large proportion of drivers not counted

by the census as residents of Lansing. On the other hand, both
Richmond and Sacramento are state capitals, and their base rates
for stops (at 10.8 and 9.1 percent, respectively) are relatively low.
Conversely, their base rates for searches (at 0.9 and 1.6 percent) are
relatively high. In Sacramento, almost one in six stops results in a
search.
The value of base rates reporting is threefold. First, it provides a
simple basis for comparing the likelihood of being stopped and of
being searched. In Baltimore, the likelihood of being stopped by
the Baltimore police is about one in four every year. Police searches,
however, are quite rare, less than one time for each 100 residents in a
year. These radically different rates of behavior for stops and searches
suggest that the reasons involved in making stops are different from
the reasons involved in making searches and that different types of
analyses may be appropriate.
Second, these base rates reveal certain similarities and differences
among jurisdictions in the rates at which their law enforcement
agencies make traffic stops and search drivers. Baltimore and other
large urban police agencies tend to fall in the 20 to 25 percent range
whereas State Police agencies tend to make larger numbers of stops
but fewer stops per resident. The Connecticut and Missouri reports
compile data from a large variety of agencies and jurisdictions. Their
base rate for stops is lower than the rate for urban police agencies, but
it is above the rate for the State Police.
Lastly, base rates are easily derived from the number of stops and
searches, the length of the data collection period, and the number of
residents in a jurisdiction. The calculations reported in Tables 4.7 and
4.8 are imprecise in part because some individuals are stopped more
than once during the study period, but they are sufficiently accurate
to convey the broad notion that base rates vary by the type of police
activity (stops versus searches), by jurisdiction studied, and by certain
methodological characteristics of a particular report. Variations in
base rates have implications for understanding differences in rates
between Blacks and Whites, young and old, male and female and other
characteristics of suspects, officers, encounters, districts, etc. Studies
about racial profiling often report the relative risk of being stopped
or searched, but the substantive meaning of such findings depends in
part on whether the base rate is 25 percent, one percent, or one-tenth
of one percent.

Measuring Race
Despite the central place that the race of the person stopped or
searched plays in this literature, there is little agreement on how
to measure race or ethnicity and what to do with incidents where
the race or ethnicity is unknown or not recorded. Within these
reports, there are sometimes differences in how race is measured in
population statistics from the census bureau and in stop and search
data from police records. One major difference is whether Hispanics
are considered a racial group mutually exclusive from other races or
whether Hispanic is a separate measure of ethnicity. Both approaches
are used in these reports.
There are additional problems with the measurement of race. In some
instances, the race of the person stopped or searched is not known
or not recorded. In the most dramatic examplesthe New Jersey
AG's report and the Lamberth report on New Jerseythe race of the
suspect is missing in more than two-thirds of the known searches.
Worse, in some reports, there is no clear indication whether stops and
searches with missing information about race were excluded from the
analysis. Some reports, however, do include all known stops and use a
category of "unknown race" in their presentation of findings.
Missing data is a problem that has long plagued social science
research, but it is one for which many analytical solutions have been
developed. One of the least recommended approaches is to simply
exclude cases with missing or incomplete data, but that appears to be
the most common approach in this literature. Although this problem
occurs frequently in official records, it is unusual for even the best-
designed and implemented study to not have problems with missing
data.
The problem with missing or incomplete data is not just a problem for
traffic stop data; it is also a problem for population data from the U.S.
Census. There are some concerns that the undercount of minority
populations in urban areas is large enough to affect congressional
redistricting and the distribution of federal funds. In addition, the
Census Bureau determined that a growing number of residents
identify themselves as belonging to more than one race. Alone or in
combination, the categorization of Hispanics as a race or an ethnicity,
the existence of missing data, and the multiracial classifications limit
the certainty of the racial proportions of any baseline comparison
group.

Most data collection efforts record the race of the person after the
stop is made. It is interesting to consider that for some (unknown)
proportion of stops, officers may not know the race of the person
until after the stop has been made. Some studies have attempted to
conduct independent traffic surveys to record the race of drivers at
certain times (day and night) and places (intersections, streets), but
the results have been varied. When officers are unable to determine
race prior to the stop, it is more difficult to determine that the stop is
based on the racial biases of the individual officer.
Geographical and Functional Allocations of Police Operations
Most research about traffic stops has not utilized a working knowledge
of police operations. Law enforcement agencies allocate their
personnel in response to perceived public preferences for services.
In general, police officers are assigned on the basis of crimes called
in by the public. These allocations influence how many officers are
assigned to specific neighborhoods and which particular aspects of
law enforcement and maintaining ordersuch as drug enforcement,
violent crime, property theft, problem-solving, or traffic lawswill be
given priority.
Studies of racial profiling in traffic stops and searches have generally
not incorporated this type of information into their data analyses
in any explicit way. Therefore, they cannot rule out the possibility
that jurisdiction-wide racial disparities in traffic stops stem not from
inequitable behavior of officers but from equitable behavior by
officers assigned in greater numbers to areas with a larger proportion
of minorities. Assignment of a high proportion of officers to
minority neighborhoods can generate disparate numbers of traffic
stops for racial minorities even if officers are acting in a completely
equitable manner.
Data analyses on racial profiling that have not incorporated
information about the allocation of police resources could easily be
in error about the existence and nature of racial profiling. If future
analyses substantiated that many of the observed disparities were due
to the nature of patrol allocations, the focus of attention would shift
from a discussion of individual officer training and behavior to a more
thorough assessment about what factors determine patrol allocations.
Specialized Police Operations
Existing research reports have also not considered the fact that traffic
enforcement is, in many departments, concentrated in a relatively small
unit of officers. For instance, in the Phoenix Police Department, a

traffic unit of just over 100 officers makes about the same number of
stops for moving violations as the nearly 1,000 officers in the patrol
division. These officers are assigned to specific locations based on
citizen complaints about traffic problems, not the drug, property, or
violent crime problems that drive the geographic and time allocation
of patrol officers. Even within patrol allocations, individual district
commanders may from time to time direct some officers to emphasize
traffic enforcement or domestic violence or open-air drug markets. As
these policies change in different neighborhoods and at different times
of the day, week, or year, they may affect the number of traffic stops
and searches in different communities within a single jurisdiction.
The allocation of police resources and the role of units with
specialized functions are central issues in any discussion about
racial profiling. In some of the earliest studies of drug enforcement
efforts along Interstate 95 in Maryland and New Jersey, patrol
officers were using traffic violations as a pretext to stop vehicles in
which the drivers were suspected of transporting illegal drugs. After
constitutional objections to the use of traffic stops as a pretext for
investigating other illegal behavior were rejected by the U.S. Supreme
Court in Whren and Brown v. United States,11 the practice of pretextual
stops was attacked in the courts on the grounds that the police
were using the race of the driver as at least one basis for the stop.
Part of the argument made by the litigants in New Jersey was that
police stops made by radar units involved less discretion than other
police stops, and that separate analyses of radar and other units
were needed to discern the nature and extent of racial bias. Similarly,
separate analyses seem appropriate for police officers or units assigned
drug enforcement responsibilities or whose assignments emphasize
removing illegal weapons during street stops.
Relatively simple approaches to data collection and analysis can help
assess the impact of differing police assignments, responsibilities, and
current priorities, and theseand not officer attitudesmay be greater
determinants of the racial distribution of traffic stops or searches.
However, most research on racial profiling has failed to address
whether differences in the proportion of traffic stops by race are
due to these factors or are a result of the discretionary judgments
of individual officers. For these reasons, prior studies provide little
guidance concerning which types of remedial efforts are likely to be
effective, where a problem exists, and which are unneeded or unlikely
to affect the most severe problem behavior.
11 Supreme Court Case No. 95-5841, Michael A. Whren and James L Brown,
petitioners v. United States on writ of certiorari to the United States
Court of Appeals for the District
of Columbia Circuit, June 10, 1996.

Multiple Predictors of Stops and Searches
Most (21 out of 24) of the studies reviewed for this paper considered
race in isolation from all other factors which might be influencing
decisions to make a stop or conduct a search. These analyses are
essentially single-variable models such as the one portrayed below.
Single-Variable Model Connecting Race to Stops
The underlying assumption of this analytical model is that no
other characteristic of the suspect, the officer, or the nature of the
encounter independently influences stop and search decisions. This
one-variable model is grossly unrepresentative of the motivational
factors behind police stops and searches. Many of the published
reports implicitly reflect the notion that there are multiple
considerations in determining why police stop or search an individual
because they include information about the rate at which males and
females are stopped, or younger or older drivers are searched. The
more useful of the available reports include a couple of simple,
one-variable modelsone for race, one for sex, one for age, etc. The
reporting of various single-variable models suggests the report authors
believe there are actually multiple influences on police behavior or
on driving behavior. For instance, the Zingraff et al. (2000) report
on North Carolina develops models and conducts analyses that
incorporate more than one variable at a time. However, the analysis
considers only drivers' ages, races, and sexes.12
Three reports incorporate a richer variety of factors that might
influence the nature of traffic stops and traffic searches. The analysis
of New York City pedestrian stops considers the extent to which the
racial distribution of neighborhoods and race of specific suspects
combine to explain higher or lower rates of police stops. Smith and
Petrocelli's analysis of traffic stops in Richmond uses multivariate
methods that include the age, race, and sex of officers and suspects,
as well as the amount of crime in the area where the traffic stop
occurred to explain traffic stops, searches, and arrests that occur from
traffic stops. Knowles et al. incorporate considerations such as the
time of day, kind of vehicle, and seriousness of the offender violation,
as well as the race of the person searched into their multivariate
analysis of traffic searches on I-95 in Maryland.
12 More extensive analyses of North Carolina data by Zingraff and his
associates are expected in 2002.

Most contemporary thinking about police stops and police searches
incorporates the idea that traffic stops and searches are linked, but
the data analyses conducted to date do not. The incorporation of
multivariate thinking into data analysis is one of the major challenges
for future research on racial profiling. Continued use of the kinds
of simple bivariate analyses that dominate the currently available
reports is likely to lead to a larger number of reports with inconclusive
findings. Progress in understanding the role of race requires statistical
analyses that conform more closely to our multivariate way of
thinking about police behavior, as depicted below. Section 4.3 suggests
a number of approaches to advance future analyses.
Multivariate analysis ties many observable characteristics to stops:
Multivariate analysis tying characteristics to stops. Characteristics:
Race, Age, Sex, Time of Stop, Location of Stop, Police Assignment, and
Suspect Behavior
Criteria for the Existence and Extent of Racial Profiling
Current research has failed to establish a consistent set of criteria
to determine the nature and extent of racial profiling. Some of
the studies adopt a criterion that as long as the percentage of the
stopped population that is Black is not more than five percent points
larger than the percentage of the resident population (or some other
comparison group), there is no racial profiling. For example, Summary
Table 4B displays stop data from the Connecticut report.
The data indicate that 12.1 percent of traffic stops were of Black
drivers, and the proportion of Blacks in the state population is 8.4
percent. Since the difference in these two percentages is less than
five, the report authors conclude that there is no racial profiling in
Connecticut.

Summary Table 4B
Summary of Connecticut State Population and the Statewide Traffic
Stops
Race
State Population
Number    Percent
Traffic Stops
Number    Percent
White
2,859,353 87.0%
264,747   83.7%
Black
274,269   8.4%
38,272    12.1%
American Indian
6,654     0.2%
665       0.2%
Asian/Pacific
Islander
50,698    1.5%
5,421     1.8%
Other/Unknown
96,142    2.9%
7,053     2.2%
Totals
3,287,116 100.0%
316,158   100.0%
Other studies use different criteria. For instance, the analysis of traffic
stop data in St. Paul reports the following stop data and comparison
groups in Summary Table 4C.
This report's conclusions are based on whether or not the differences
in the over-18 population and the population of traffic stops is
statistically significant. The use of this criteria led the report author
to conclude that the St. Paul police racially profile both Black and Hispanic drivers.
In the latter case, the difference between 6.3 percent in the over-18 population and
6.71 percent in traffic stops met their criteria for being statistically significant.
Summary Table 4C
Summary Information of Traffic Stop Data for St. Paul
Race
City Population
Count    Percent
Over Age 18 Population
Count    Percent
Traffic Stops
Count    Percent
Non-Hispanic White
186,583   65.6%
152,542   73.2%
23,788    57.67%
Black
34,861    12.3%
21,302    10.2%
10,828    26.25%
Asian
10,828    26.25%
18,731    9.0%
3,659     8.87%
Hispanic
20,756    7.3%
13,076    6.3%
2,768     6.71%
Native American
4,542     1.6%
2,808     1.3%
206       0.50%
Totals
284,526 100.0%
208,459 100.0%
41,249 100.00%

Other criteria are also used to interpret the data analyses reported
in racial profiling studies. The Bureau of Justice Statistics reports
its findings in a format more familiar to police agencies, as a rate
per 1,000 population over age 16 (see Summary Table 4D). These
survey results, however, rely on estimates of stops projected from
the nationally representative sample of households participating in
the National Crime Victimization Survey, corrected for survey non-
response rates.
Summary Table 4D
Police Contacted Respondents
Reasons for Contact
Total
White
Black
Hispanic
Other Race
Motor Vehicle Stop
109
113
107
90
83
Involved in Accident
16
18
12
10
10
Witness to Accident
4
4
2
2
1
Victim of Crime
4
4
5
5
3
Witness to Crime
7
7
6
6
4
Suspect in Crime
6
6
8
8
5
Serve Warrant
2
1
5
1
2
Crime Prevention
3
3
3
2
1
Other
25
27
25
19
17

Zingraff et al.'s (2000) analysis in North Carolina, on the other hand,
reports a variety of criteria. For instance, in their analysis of traffic
searches they report the actual numbers, the percent differences,
and the ratio of African-American search rates to White search rates
(see Summary Table 4E). The third row reports the odds or chances
that each racial group will be searched, given that they were cited or
warned.
Summary Table 4E
North Carolina Search Rates
African-Americans
Whites
Searches
281
545
Citations/Warnings
223,241
683,517
Proportion of
Citations/Warnings
That Were Searched
.00126
.00080
Incident Rate of
Searches (Per 100,000)
13
8
Difference in Incident Rate 5
African American/White Ratio 1.63
The calculation in the last row is called the odds ratio and is
commonly used in a wide variety of statistical analyses. The standard
interpretation of these findings is that the odds that African-
Americans will be searched are 63 percent higher than those of White
drivers. The Missouri Attorney General's report uses a similar ratio,
but in neither report is there an explicit statement about the cutting
point for determining that racial profiling does and does not exist.
However, in both of these reports, the authors assert that the findings
indicate the presence of some racial profiling.
It is important to note that had the North Carolina report applied
the five percent rule used in Connecticut, the North Carolina report
would not have found racial profiling in traffic searches. Had the
Connecticut report constructed the odds ratio used in the North
Carolina report, the Connecticut report would have reported an odds
ratio of 1.51, that is, Blacks in Connecticut have 51-percent greater
odds of being stopped than Whites.

In some reports, the authors reach a conclusion without identifying
how they went from the reported data analysis to the report's finding.
The New Jersey Attorney General's report, for instance, reports
number and percent of traffic stops and searches but reports no
information on any comparison group. Still, the report concludes that
there is no racial bias in traffic stops but there is racial bias in traffic
searches.
4.3 Recommended Analytical Approaches
This review has highlighted a number of problems with the research
on police stops and searches. The existing body of research displays
great diversity in methods and in findings, but it has not generated
an understanding of the nature and extent of racial profiling, or
of the circumstances and types of police activities where profiling
is more prominent or absent. It also lacks evidence on approaches
to policymaking, training, supervision, or leadership that have been
demonstrated to reduce racial profiling or community concerns about
it. At present it does not know the extent to which the allegations
of racial profiling can be substantiated by social research, or if
any of the proposed solutions to this problem will be effective (or
counterproductive).
Social science research is an approach that can contribute to an
assessment of the nature of police stops and searches, but the
promise of that approach has not yet been fulfilled. Improvements
can be made in how data are collected and analyzed and in how the
analysis is reported. For the most part, the improvements suggested
are intended to incrementally advance the analysis of official police
records, but the use of other data collection methods, such as public
surveys of contacts with the police is encouraged. The use of
multivariate statistical methods is also recommended.
Although many suggestions such as capturing and using information
about the residence of drivers stopped can be implemented by
analysts working for law enforcement agencies, the skills and
experience needed to conduct multivariate statistical methods are
not typically resident in law enforcement agencies. However, not all
researchers trained in statistical methods are sufficiently knowledgeable
about the day-to-day operations of law enforcement agencies. Also,
not all police department officials or statisticians are sufficiently
attuned to the aspects of police public contacts that are most relevant
to the communities they serve and which issues warrant more in-depth
analyses. The extent to which studies benefited from the analytical
training of local researchers, the experience of police professionals, or
the concerns of community leaders is unclear.

Five strategic suggestions that will increase the value of collecting
and analyzing data on police stops and searches are described below.
CNAC recommends some general activities, such as having a research
plan, as well as some specific data analysis methods such as employing
multivariate analysis. Some suggestions will be more relevant to
jurisdictions that have not yet initiated a research project on traffic
stops; other suggestions may be more suited to organizations and
individuals currently implementing a study. The suggestions are
designed to encourage incremental and general improvements in
future studies. It does not recommend a specific model, because no
single research design will fit the purposes, schedules, or resources
available to all jurisdictions.
1. Have a Plan
CNAC recommends creating an analysis plan before the data are
collected and analyzed. This will focus the research, and facilitate a
final report that indicates how the results achieved compare to the
plan's intentions or expectations. Analysis plans do not need to be
long, but they should address the following concerns:
 Identify the issues you, your organization and your community
think are important enough to warrant a formal study.
 Consider the strengths and weaknesses of previous studies.
 Determine what aspects of police behavior will and will not be
studied.
 List data items that will be collected.
 Identify exactly how each data item will used in the proposed
analysis.
 Determine which types of informationofficial records, citizen
surveys, independent observationsbest address the issues you
care about most.
 Estimate how long the data collection should last and how big a
sample will be needed.
 List the planned analysis approaches.
 Establish criteria for reaching conclusions prior to collecting data.
 Determine the internal and external resources are available.
 Clarify who should do each part of the data collection, analysis,
and report writing.
Many research plans and reports are overly ambitious. They take on
a large number of issues and many details. Frequently, this results in
insufficient attention to central issues and a lack of in-depth analysis
of any issue. Thus, perhaps the most difficult part of a plan is limiting
the issues to be studied to the time and resources available.

2. Plan to Iterate
Elements of a research plan will change as new information becomes
available. Plans require certain assumptions (e.g., the nature of police
stops, which units or individuals will collect or code data, how many
stops will occur over a given period of time), and experience shows
that preliminary assumptions often do not hold up. Original plans
are frequently revised, and final reports will be stronger if they
indicate not only what the research did but the research designs and
approaches that were attempted unsuccessfully.
There are benefits to starting small and expanding the size of the
study or the nature of the issues addressed. Data analysis should begin
almost simultaneously with data collection. In many projects, analysts
wait for a large batch of data before they begin to analyze the data
and then discover that important data items were not collected or that
certain items, such as the race of the suspect, are missing in a large
proportion of cases. Conducting these sorts of diagnostics early can
eliminate some unforeseen problems in the implementation of the
data collection effort.
Stopping and restarting data collection or revising approved data
forms are not easy actions in bureaucracies. However, pilot studies
are usually preferable to conducting lengthy and resource consuming
studies whose implementation problems cause their authors to
determine that no conclusion is warranted from their efforts.
3. Benefit from Professional ResearchOperational Linkages
Although many of the existing studies of traffic stops and searches
were issued by law enforcement agencies or conducted with their
cooperation, most of the reports were authored by or involved
substantial assistance from individuals trained in conducting statistical
analyses. Given the kinds of enhanced data analyses needed to
improve the utility of future research on racial profiling, CNAC
recommends increased initial involvement of professional researchers.
The design, implementation, analysis and interpretation of data
on traffic stops require professional research skills. In turn, the
professional researcher will benefit from a close collaboration with
police professionals, and by being attentive to the concerns of local
communities.

There are many models of how researchers, police professionals
and community members can collaborate. Researchers can work
completely independent of police agencies and the community.
They can work as contractors to departments or to litigants against
departments. Although there are potential strengths and weaknesses
to different models, there is not much evidence about which model
increases the scientific reliability of the research, is of greater utility
to law enforcement agencies, or better addresses the concerns and
complaints of residents.
CNAC recommends that researchers be considered analogous to
medical doctors whose training and experience help them diagnose
particular illnesses and prescribe particular treatments based on a
variety of symptoms. In the matter of diagnosing symptoms about
what might be wrong with the nature of police public contacts, law
enforcement agencies might want to obtain second opinions about
how to measure police behavior, analyze traffic data, and interpret
the findings. A professional and open discussion by independent
researchers of the alternative strengths and weakness of a proposed
analyses will assist law enforcement and the communities they serve to
better understand the nature of the analyses conducted and the proper
interpretation of those analyses for improving future police public
contacts. Such a discussion is more likely to be fruitful if it occurs
before the type of sample, nature of the data, and data analysis are
determined.
4. Describe Police Operations
Future research on traffic stops and searches would be improved
if it described the nature of police operations in general, and
traffic enforcement in particular. This information, while familiar
to experienced personnel in a particular agency, is often not well
understood by the general public. For instance, how many patrol
officers are there and which units or officers are given primary
responsibility for traffic enforcement? Where are they assigned? What
are the departmental policies and legal criteria for making stops and
searches? These narrative accounts of the nature of police operations
should provide a foundation for the particular data analyses conducted
and assist in interpreting the meaning of the research findings.
5. Consider Specific Analytical Issues
There are a number of tightly focused analytical approaches that
can be relevant to a wide variety of research designs. Eight of these
approaches are discussed below.

Controlling for Resident Status: Several reports have noted that their
data on traffic stops includes some unknown proportion of nonresidents,
and that stopped non-residents may include more or fewer
racial minorities. This could be a real problem, depending on the
nature of the jurisdiction, the time of day, or, in some locales, the
time of the year. If the traffic stop data include information about the
residence of the driver, this issue can be addressed by conducting an
analysis that only includes stopped residents.
Allocation of Agency Resources: Virtually no police department
allocates patrol or traffic enforcement resources on a per population
basis. Analyses that understand and incorporate these allocations will
provide stronger tests of the existence of racial profiling. This type of
analysis requires an understanding of how and why police resources
are assigned to specific geographical areas, and how and why they
are assigned to emphasize certain types of police work (e.g., traffic
enforcement, drug interdiction, 911 calls, foot patrol, etc.). A single
analysis of all law enforcement units in a particular jurisdiction could
easily miss or underestimate the nature of racial profiling in certain
neighborhoods or at certain times of day. On the other hand, analyses
of distinct units may focus on a small proportion of a department's
traffic stops and not represent the behavior of the overall agency.
Analysis of neighborhoods and units can help identify whether
remedial training, supervision, or discipline are needed in specific
areas.
Missing Data and Missing Cases: Research on racial profiling needs to
address the issue of missing data, since missing data can bias analytical
results. At a minimum, studies should report how many traffic stops
are known or believed to be missing, or how much data have been
excluded from the analysis because one or more pieces of information
about a stop is missing. This is not a trivial concern, especially in
research that relies on official records. Information about the race of
the suspect was missing in up to two-thirds of known traffic stops
in some prior studies. Analyses need to consider the extent to which
missing data could affect the study's substantive findings about racial
profiling.
The problem of missing data is endemic to social research, and a
variety of approaches have been developed to address it. In addition
to reporting the nature of the missing data problem, we recommend
that studies use at least two different ways to handle missing data and
report whether they generate substantively different results about
racial profiling.

Bivariate and Multivariate Statistics: Bivariate statistical analyses are not
appropriate for testing for the existence of racial profiling, and studies
that rely exclusively on them are unlikely to increase our knowledge
about the nature of police public contacts. The decision to make a
traffic stop or conduct a search involves a large array of legal, policy,
and social considerations. Analyses that include these considerations
will provide stronger tests of the nature and extent of bias-based
policing. Bivariate statistics are useful for descriptive purposes but are
too simplistic to disentangle the role of race or any other single factor
in determining police behavior.
There are a number of plausible considerations, other than the race
of the person stopped, which might explain the nature and extent
of police public contacts. Future research needs to identify which of
these plausible considerations may be consistently associated with
more stops or more searches. Examples include:
 Suspect characteristics
Age, race, sex, driving behavior, nature of violations
 Officer characteristics
Age, race, sex, length of service, training, current assignment
 Encounter characteristics
Time of day, day of week, type of vehicle, volume of traffic
 Jurisdictional characteristics
Legal requirements for stops, departmental policies on stops,
population density, socio- economic disadvantage
Study Samples: In the context of racial profiling, multivariate analyses
are most appropriate when the sample under study includes both
individuals who have been stopped and those who have not been
stopped (or individuals who have been searched and those who have
not been searched). For this reason, samples like those obtained in the
BJS police public contact survey are well suited for multivariate tests
of the role of race. Most racial profiling studies, however, include
only people stopped by the policenot those who could have been
stopped (but were not) because they were observed violating some
law. The following diagram illustrates differences between resident,
available, stopped, and searched populations. Most studies compare
stopped populations versus resident populations, although a stronger
comparison is with violator populations. The problem is that it is
difficult to ascertain the characteristics of populations of violators,
so researchers frequently use the better known, but less appropriate,
resident population.

Alternative Study Samples:
Diagram illustrating the differences between resident, available, stopped,
and searched populationsNon-resident Population
Even if the nature of the violations among the available population
were known, a stronger study would identify the subset of all possible
violations that police departments or police officers regularly enforce.
Some departments and officers emphasize speeding violations,
whereas others focus on equipment violations. Some departments
strictly enforce laws about child safety restraints, whereas others do
not.
Traffic Surveys: Independent surveys of the characteristics of
drivers can provide useful estimates of the available population and
violator populations at certain times and locations. The value of these
surveys would be improved if they were informed by the nature of
enforcement activity, and the legal and operational criteria used by
the police in making traffic stops and searches. For example, in many
U.S. jurisdictions, traffic enforcement laws require that police establish
that drivers not only exceeded the posted speed limit but also that
they were not driving in a "reasonable and prudent" manner. Under
these conditions, studies conducting traffic surveys may benefit from
determining the extent to which officers ticket and judges enforce
violations that exceed the posted limits by 1, 5, 10, or 15 miles an
hour.
If officers never ticket cars driving less than 10 miles over the speed
limit, traffic surveys of cars going over 5 miles an hour are not
particularly helpful. Similarly, if officers are asked to enforce seat belt
laws, especially for children, estimates of traffic violators need to
include these and other types of violations. Traffic surveys would also
provide better estimates of violator behavior if they were obtained
under conditions similar to those used by the police to observe traffic.
If the police being studied are stationary, surveys of traffic from
stationary observers would more closely approximate actual police
operations. Mobile observations can easily misrepresent the population
of violators observed from a stationary location.

Analyzing Stops and Searches: Samples of official police stops often
include persons who were searched and those who were not. These
are better suited for studies of search behavior, including the nature
of the search and the length of time the person is detained. A
multivariate analysis of search behavior needs to consider the different
types of consensual and non-consensual searches and searches that
occur without an arrest, before an arrest, and after an arrest. One
challenge for multivariate analyses of search behavior is that traffic
stops rarely involve searches of any kind. Prior research has addressed
traffic stops and searches as separate analyses. Future research will be
improved by considering these behaviors together and recognizing that
racial biases in police traffic stops will likely affect any analysis of the
traffic searches, often in unexpected ways.
Criteria for Racial Profiling: Future research should be more explicit
about the criteria used to judge whether systematic racial profiling
exists, and if it exists, how frequently it occurs. Racial profiling
undoubtedly occurs in some incidents, but the broader issue is
whether it occurs in a systematic manner rather than as isolated
individual instances. Social science research methods can be used to
evaluate the extent to which racial profiling occurs as a rare event or in
a systematic and measurable fashion. There are a number of statistical
criteria that are commonly used in social science (e.g., percentages,
odds ratios, statistical significance, proportion of explained variance)
to assess whether an effect exists and, if so, how large is the effect.
However, ultimately determinations about racial profiling require value
judgments as well.
CNAC recommends that future research on racial profiling go beyond
the use of various percentages and statistics and that analysts attempt
to report their findings in terms of the number of racial minorities
stopped or searched that would not have been stopped or searched
under racially neutral circumstances. There are various methods to
compare the actual number of stops (or searches) with the expected
number. The importance of this recommendation is to convey the
nature and size of the reported effect in terms of the number of
people affected rather than in the jargon of statistical methods.
Prior to collecting data, explicit criteria should be articulated about
how much of a difference between races, measured with which
statistics, and controlling for which other influences, would indicate
the existence of racial profiling. This procedure would lead to stronger
racial profiling research. Of course, reaching agreement among various
interested parties within an agency or a jurisdiction about what criteria
should be used can be difficult. Social science research often addresses
this problem by adopting, applying and reporting results using several
different criteria. This approach is recommended, especially when time
and resources permit.

4.4 Maximizing the Utility of Future Research
Local jurisdictions should consider a variety of potential uses for any
study on racial profiling. Most reports have focused on determining
if there is a problem, but the research typically provides little or no
diagnoses of the locations, times, circumstances, or enforcement
activities where the problem appears most strongly or does not appear
at all. For example, is there a greater problem with searches or with
stops? Is the problem greater is some neighborhoods but not in
others? Similarly, most reports provide little guidance on what should
be done to alleviate any problems that are identified. Will a new
policy help? Is the issue related to current training, supervision, or law
enforcement management priorities? Is the problem agency wide or
just among certain offices?
Many jurisdictions have already considered and adopted numerous
policies and practices to address concerns about racial profiling.
However, there is little empirical evidence about observed changes
in the nature of police public contacts after these new policies and
practices have been adopted. Social science research may ultimately
be more valuable if it evaluates the strengths and weaknesses of these
new policies instead of offering simple descriptions of the nature and
extent of racial profiling.

5.0 FINDINGS FROM THE CONFERENCES
5.1 City Representation
CNAC developed a list of cities that would meet the criteria identified
by the COPS Office and that expressed an interest in participating.
It then worked with the COPS Office to select four cities: Baltimore,
Maryland; Phoenix, Arizona; St. Paul, Minnesota; and Chattanooga,
Tennessee. Among the criteria used to make the final selection were
geographic diversity as well as diversity in city size and composition.
CNAC wanted to include cities facing a variety of challenges.
The cities were asked to send representatives to two Profiling
Technical Assistance Conferences held at CNAC. The first conference,
held in August 2001, focused on understanding the cities' current data
collection plans and special problems they faced. CNAC brought in
subject matter experts, including research analysts and operational
experts, to work with city representatives to discuss issues in defining
and measuring racial profiling issues. The second conference, held in
October 2001, was a working conference, focused tightly on technical
issues and assistance to the participants. CNAC again brought in
subject matter experts to facilitate in-depth discussions on pertinent
topics. Formal agendas for the two conferences are shown in
Appendices B and C.
5.2 Composition of Participating City Groups
The representation from the cities was specified to elicit points of
view from various stakeholder groups. CNAC asked each city to send
representatives to reflect views from the department, the union, and
the community. Specifically, it asked for:
 A high-ranking police department official, involved in the planning
and process of data collection
 A union representative from the police department, to reflect
points of view held by the rank-and-file police officer
 A representative of the community, to reflect the observations and
beliefs of citizens and members of minority groups.
CNAC combined these attendees with outside subject matter experts
from other jurisdictions, to obtain a wide cross-section of opinions. In
particular, it invited members of the National Organization of Black
Law Enforcement Executives (NOBLE) to lead critical discussions
concerning racial profiling and data collection issues. CNAC also
invited members of the research community experienced in analytical
and evaluation issues.

From the city groups, it expected to observe interesting patterns of
commonalities and differences among the cities. Specifically, CNAC
expected to observe common issues pertinent to union members,
community representatives, and police department officials across all
cities. It also wanted to observe any differences the representatives
were able to identify in their particular circumstances and issues.
Another focus was to explore the different viewpoints of police,
union, and community representatives within each city. This structure
was designed to allow us to explore between-city and between-group
variations constructively, with the outside subject matter experts
serving to lead discussions and facilitate debate.
CNAC started the first conference by having each city group present
the pertinent details regarding its city, its problems, and the current
thinking regarding data collection and analysis. It requested that the
police representatives present the status of their city's efforts to the
entire group, and engage in a short question and answer session.
CNACs guidance to each police department representative was as
follows:
As the Police Department representative, you will take the lead
in presenting and leading discussion about the current situation
in your city. Generally speaking, we want you to share details on
what your city is doing with respect to addressing profiling issues
and gathering data to investigate concerns. We want you to discuss
what event or issue has led your city to become involved in this
process. Finally, we want to know what outcomes you seek from
your profiling investigation and data gatheringin other words,
what specific questions are you trying to answer, and how are you
planning to gather and process data to answer those questions.
The first part of our conference is targeted to developing an
understanding of the underlying issues and concerns across the
four cities, looking for commonalities and critical differences.
In addition, CNAC forwarded a list of questions for the city
representatives to consider with respect to describing their data
collection and evaluation efforts. Following are sample questions
it asked the representatives to consider in helping them focus their
discussion:
 Why is your department collecting data/what made you decide to
do this?
 What types of data are you collecting/plan to collect?
 How are you recording the information?/what is the technical
process?
 How much is it costing in terms of money and time?

 Who is responsible for collecting, recording, maintaining the data?
 What group will be responsible for evaluating the data?
 Who will release information derived from the data?
 What specific questions do you want answers for?
 What answers are you expecting to find?
 What are your plans to disseminate the information learned?
 What actions do you foresee resulting from the information/
answers gained?
 What happens if the data shows you completely unexpected
results?
 How important are public medias (television, radio, newspapers)
in terms of focusing attention to profiling issues? Are they fair in
their reporting?
 What problems have you seen so far in your data collection/
analysis effort?
 What lessons learned can you contribute for discussion?
5.2.1 Presentations from Individual Cities
This section presents information from the four cities and their
representatives regarding how the cities came to be involved in data
collection. It also discusses briefly the type of data collection that
is being considered/ongoing. The speakers focused primarily on
introducing the issues that prompted their city's involvement in the
project and their current efforts to address racial profiling issues.
Although the police department representative took the presentation
lead, the other representatives then spoke to present counterpoints
and additional points of view.13
13 Confidentiality concerns generally preclude identifying specific
participants and the interactions observed during the conferences.
Similarly, CNAC did not ask for actual data collected on racial profiling.
Comments and criticisms of these approaches spurred further
discussion on the pros and cons of various data collection efforts.
The culmination of various perspectives on the issue created insights
that should be useful for cities struggling with pinpointing the best
methods and practices. The cities have made various levels of progress
to date in addressing racial profiling. Those who have made greater
strides provided useful insights to those just becoming familiar with
the significance of the issue in their area.
Chattanooga, Tennessee
As described during the conference, Chattanooga is composed of
roughly 155,000 people59 percent Caucasian, 36 percent African-
American, 2 percent Hispanic, 1 percent Asian, and two percent other.
The daytime population, on the other hand, ranges from 230,000 to

240,000 people87 percent Caucasian, 11 percent African American,
1 percent Hispanic, 1 percent Asian, and .5 percent other. The
Chattanooga Police Department is 69 percent Caucasian, 28 percent
African-American, 2 percent Hispanic, 0 percent Asian, and 1 percent
other.
Chattanooga has a relatively new chief, who is identified as bringing a
new philosophy of openness to Chattanooga (Chief Dotson, October
1997). He sees rebuilding community trust as a critical goal for the
police department. The following factors/principles are listed as keys
to the department's success in meeting that goal:
 Department actions and policies should be driven by departmental
values.
 An important value is openness both across the departmental
hierarchy and with the community.
 The chief and his command staff must set the tone and lead by
example.
To promote openness within the department, the command staff
holds regular meetings with, and cooperates with, the union. In
addition, to promote openness with the community, the department
established several community groups that meet regularly. The police
department's mission statement is "to enhance the quality of life
working cooperatively with the public and within the framework
of the Constitution of the United States and State of Tennessee to
enforce the laws, preserve the peace, maintain order, reduce crime and
fear and provide a safe environment."
Chief Dotson is also reported to have brought cultural change within
the department in the form of increased freedom and responsibility
for individual officers to do their jobs more creatively. The chief says
that the State and U.S. constitutions define the parameters of police
behavior and officers are free to function within those parameters.
This new culture may require new recruiting strategies as well.
Under the leadership of Chief Dotson, the Chattanooga Police
Department began directly addressing the issue of racial profiling in
1998. Their effort has had three components:
 Collection of data to track racial profiling
 Provision of in-service professional development to teach officers
about racial profiling and what not to do
 Establishment of a code of ethics regarding criminal profiling.

Chattanooga's data collection effort consists of logging every moving
citation that each officer writes and every field interview that each
officer conducts. The moving citation and field interview summaries
capture the geographic area in which the stop took place and the sex
and race of the person stopped. The moving citation summary also
indicates whether the stop resulted in a citation or a verbal warning. A
command committee reviews the aggregate and officer-level data from
the summaries every month. The data are considered public record
information and are available upon request from any interested party,
including citizens and the media.
There are technological problems associated with collecting the
data. The specific issue that was mentioned was the fact that the
Department's two main databasesthe Computer-Aided Dispatch
System (CADS) and the Records Management System (RMS)are not
integrated. One benefit of integrating these systems is that matching
RMS data, which is provided by officers, with CADS data, which
comes from dispatchers, would help validate the officers' data.
As of January 1, 2001, the Chattanooga Police Department voluntarily
began participating in the State of Tennessee Vehicle Stop Form
program. These forms are completed each time an officer stops
a vehicle. The state Vehicle Stop Forms are sent directly to the
appropriate state office. The individual departments do not review this
data and do not know how the data will be compiled and used by the
state.14
Baltimore, Maryland
Baltimore is a coastal city with a population of 650,000, including
a large minority component. The population of Baltimore is 64
percent African-American, 32 percent white, and four percent other.
In contrast, the composition of the police department is roughly
33 percent African-American. The traffic investigation unit has two
African-Americans and 38 white officers.
The Baltimore Police Department has not been required by any
outside agency to collect data. It decided to do so for three main
reasons. First, in addition to being an important national issue, racial
profiling is an important issue in Maryland. In response to allegations
of racial profiling along Interstate 95, Maryland State Police have been
collecting and reporting data on vehicle stops. At the same time, and
at both the state and local levels, legislation requiring data collection is
being considered. The state did not pass this legislation in 2000, but it
is thought that some type of bill will eventually pass.
14 These forms have considerable overlap, which will be discussed
further in Chapter 6.

Second, public safety and community-police relations were important
issues in the campaign of Baltimore's recently elected mayor. In his
campaign, he promised to require that anyone stopped by a police
officer should receive a receipt showing the reason for the stop and
the officer's name and identification number. Finally, it is felt to be
a smart business practice. In order to maintain public trust, police
practices and procedures should be as transparent as possible.
To initiate the process, a research group was asked to develop stop
receipts and a system for collecting and analyzing data. The research
group developed a citizen/police contact receipt book. Officers carry
the book and make out receipts to all citizens with whom they have
contact. The forms in the book are two-sided, but the citizens' receipt
has information from only one side. The citizen's receipt shows:
the date of the contact; the times the contact began and ended; the
officer's name; the location of the contact; the officer's assignment;
the citizen's name, date of birth, contact information, and race; the
type of stop; and the action taken.15 The second side of the form
(which contains information included on the receipt) shows vehicle
information; whether a search was conducted and what type; and
whether any item was seized.
Baltimore has already collected many stop receipts. The information
collected to date shows 63 percent of those stopped are of African
Americans, 30 percent are Whites and 6.25 percent are other, which
seems to match the overall city demographics. A possible issue
of concern is that 80 percent of pedestrian stops are of African
Americans.
St. Paul, Minnesota
The St. Paul Police Department began collecting data for reasons
similar to those that motivated Baltimore. It is considered to be an
appropriate business practice and will probably eventually be required
anyway. (As in Maryland, a bill requiring data collection was proposed
in the Minnesota legislature, but was not passed.) There have also
been investigations in St. Paul that have prompted further efforts
to investigate racial profiling issues. The total population is about
287,000, and the racial composition of the city is 66 percent White,
12 percent Black, 13 percent Asian, seven percent Hispanic, and two
percent Native American. (Police officers are estimated to be nine
to ten percent Black, five to eight percent SE Asian, and four to five
percent Hispanic.)
15 Arizona representatives asked whether citizens might worry that in
collecting information about the citizens, the police are acting in
cooperation with the INS. Although this isn't really an issue for Baltimore,
the fact that the question came up highlighted the fact that each department
will have its own local issues that must be considered when designing a
data collection system. If these data were collected in Arizona, Immigration
officials, who could use it to find illegal aliens, might request the data.

In making the decision to collect data, the department engaged in
extensive internal discussions, and also solicited significant community
involvement.16 Internally, the discussion revolved around fulfilling the
requirements of both the Fourth and Fourteenth Amendments. The
department representative felt that although officers are well trained
on Fourth Amendment search and seizure issues, they have not
had the same exposure to Fourteenth Amendment equal protection
concerns. An additional issue was the role of training and professional
development.
St. Paul representatives reported that initial findings regarding the
data collected by the department indicated that racial profiling had
been occurring (one type of profiling identified involved Asian
gangs in specific areas). In order to improve community relations
after these indications became public, the department considered
two new policies. First was a plan to give officers personal business
cards to hand out to citizens with whom they come in contact. The
business cards are intended to support an early-warning system that
will identify individual officers who may be problem cases. Second, a
"consent search advisory" was developed. Officers are now required
to read this advisory to citizens when requesting a consensual search.
This advisory is analogous to the Miranda advisory and is intended to
keep officers from casting too broad a net when requesting searches.
The data collected by the St. Paul police come from their CAD
system. The data show race and gender of people who are stopped
and whether or not a person or car was searched (and also the time
of the stop). The data are reported to allow comparisons between the
rate at which people of a given race are stopped with the rate at which
those who are stopped are searched. St. Paul calculates the following
measures:
where the subscript, r, indicates the race so that # stopped is the number of
individuals of race (r) who are stopped.
16 Community discussions focused on how to collect data that would truly identify
biased behavior and would result in real diagnosis and correction of problems.
The community discussions also went beyond data collection to issues of general
community safety.

The St. Paul representatives indicated that various approaches were
used to evaluate the initial data collected. The press stated that the
police department stops a disproportionate number of minorities.17 It
was also reported that the Institute of Race and Poverty looked at the
data and compared them to 2001 U.S. Census data, and concluded that
the St. Paul police stop, frisk, and search more people of color than
the population percentages.18
The current position in St. Paul is that because of the negative
findings, the Department has moved in a significant way toward
defining a solution. Rather than continuing to focus on collecting data,
the Department is now focusing on programs to address perceived
inequities and treat all citizens appropriately.19
Phoenix, Arizona
Phoenix is the sixth largest city in the U.S. with a population of 1.3
million. The population is 57 percent Caucasians, 34 percent Hispanic,
five percent African American, three percent Native American, and
two percent Asian or Other. The racial composition of the 2,810
officers in the Department mirrors that of the city's population,
with Hispanics being slightly under-represented and Caucasians
slightly over-represented. Currently, there is no legislation in the state
regarding racial profiling or data collection. However, the issue is
being discussed.
Phoenix is not currently collecting racial profiling data, although
it does collect standard data to provide traditional crime statistics.
The first reason cited for why data on racial profiling are not being
collected is that the Department doesn't know what data to collect or
how the data should be used. A second issue is Arizona's liberal public
disclosure laws. In most other states, data on individual officers would
be considered part of a department's private personnel data, but in
Arizona, all data collected would be considered part of the public
record. Because the state's public records laws are currently very
open, any information gathered would be immediately open to public
scrutiny.20
17 The police department representative indicated that the press compared its
information to the 2000 Ramsey County dataa county with a higher percentage
of whites than in the city itself.
18 These comparisons may not adequately adjust for geographic disparities and
operational influences.
19 The St. Paul Police Department and the St. Paul chapter of the NAACP signed an
Agreement. The police department agreed to institute certain measures to address
racial profiling, and the NAACP agreed to support the police department and see
how the new measures worked out. The union representative stated that the union
did not sign the agreement, although they want to be a part of the discussion.
20 This is essentially the case for Chattanooga as well. See details in Chapter 6.

A third issue is a technological onecurrently, the computer system
used to store other crime data (the state-mandated traffic system)
forces officers to classify Hispanics as whites (White or Other). If data
are entered as Hispanic, the program will re-classify as White or Other.
This makes it difficult to analyze the information in a meaningful
manner, as Hispanic is the dominant minority group in Phoenix.
The police representative indicated that, at this point, the biggest race
issue for Phoenix policing is the use of force. There were three events
in the city that have brought the issue to the Department's attention,
mostly focused on the use of force by the police. In response to
allegations of too frequent use of undue force, the Department
initiated a citizens' use-of-force forum and special professional
development programs to teach officers about the importance of
racial profiling.
Specific actions taken by the city include:
 Instituting a Citizen's Use of Force Forum
 Report from the Arizona Attorney General and Resolution
 Developing a Model Policy for Arizona
 Training 2,800 officers on bias-based policing
 Creating seven advisory groups with minority communities that
meet monthly.
The Phoenix Police Department is also in the process of
implementing an early-warning system. They are concerned with
knowing what flags they should be looking forin other words, what
signals will clearly identify the existence of racial profiling?
5.3 Areas of Agreement
Among the four cities, CNAC found important areas of agreement
on issues and concerns. First, each city agreed that they were
characterized by having distinct neighborhoods with very different
characteristics and problems. A common comment was that "our city
is really two cities." This mirrors concerns discussed in a previous
section about using aggregate data collected on a city-wide basis
to interpret policing actions for the city, since geographic diversity
interacts with poverty and crime. The cities agreed that neighborhoods
had specific characteristics and problems that required different police
activities and presence.

All of the city representatives expressed concerns about how to
correctly evaluate and interpret data. They were also concerned
about which groups will be allowed, or asked, to make interpretation
decisions. Some of the community representatives expressed concerns
about the accuracy of data, and the honesty with which forms are
filled out. If some officers are knowingly engaged in racial profiling,
which the department forbids, then there is an incentive for officers to
forego filling out the forms or to fill them out incorrectly. This could
lead to biased data.
The department representatives seem certain that no department-
wide policy exists for engaging in racial profiling practices. They also
seem to dismiss the "bad apples" theory.21 The general tone was that
they think that they are doing good police work, and it just "looks
like" they are racial profiling when in fact they are not. Therefore, one
reason to resist doing data collection is that "it will make us look guilty
just for doing good police work and protecting the citizens." This
concern appears to be consistent across departments and is shared by
police management and the rank and file. Officers find it both time
consuming and insulting to be asked to collect data, and they worry
that they are being set up because the press and community opinion
have already convicted them.
5.4 Sources of Disagreement
One of the community members spoke on the general issue of racial
profiling throughout the country. He stated that it has not received as
much attention in his state as in other areas of the U.S. This opened
up a discussion of community/regional values and expectations.
The discussion pointed up the fact that acceptable practices in one
community may not be viewed as acceptable practices in another.
In addition, whether specific practices are viewed as acceptable may
depend on which minority community is being queried, even within a
single city.
Another point of view that was raised questioned the overall value of
data collection. From this point of view, if racial profiling policies are
in place or instituted, this may obviate the need for data collection.
This point of view probably reflects some frustration with a focus
on data collection. It reflects a desire to move past trying to measure
whether the problem exists, and instead put procedures in place to
address the problem.22
21 They also indicate that, if there are bad apples, they will surely be clever
enough to cover their tracks during any data collection effort. The feeling is
that bad apples will have to be found via other metrics.
22 This was not a general view, but more than one person voiced it. This may
simplify racial profiling too muchwhat kind of profiling is going on, and who
is doing it is important to devising proper policies.

5.5 Recommendations from Conference Participants
CNAC also asked its conference participants to break out into
counterpart groups to observe their reactions separately. It asked the
police department representatives to meet alone and discuss some of
their concerns, as well as the community representatives and the union
members. CNAC learned that, as expected, some of the concerns
voiced were more candid when the groups were organized in this
fashion. It then brought the groups back together to talk further about
some of the issues that were raised in the breakout sessions.
5.5.1 Command-Level Police Department Concerns
Public Awareness and Media Involvement
One of the major concerns to surface was how the data being
collected would ultimately be used. Specifically, considerable concern
was expressed over whether the data collected would become public
information. These concerns include:
 Will officials and/or politicians allow the data to be made public
without proper qualifications and explanations of the meaning?
 Will the data be accessible via the Freedom of Information Act?
 If so, data could end up on a website or in print (via the
media), thus allowing citizens or media experts to draw their
own conclusions.
Such concerns may have a chilling effect on the prospect of data
collection and evaluation. If police lack confidence in how the data
will be used and protected, it may seem more reasonable to avoid data
collection. In particular, if the police are asked to collect data, but are
not invited to provide input into analysis of the data collected, and
add their specific operational expertise, it is reasonable for them to
be concerned about the analytical conclusions that may be reached by
outside experts.
In this context, data collection should be viewed as part of an overall
strategy. One of the key elements in the process is for the police to
bring the media into the process and make sure that they understand
the overall strategy and the steps being taken to improve police-
community interactions. In particular, without proper education and
preparation, the media may simply mirror citizen reports, citing stories
from unhappy citizens or people with grudges. Media involvement
can be an educational process. If the media become engaged with
police departments, and learn the processes, stresses, strategies, and
community-relations issues, they can give a more balanced picture and
help resolve tensions rather than exacerbate them.

Stand-alone reports are viewed as dangerous. Conference
representatives felt it is better to engage politicians and media
representatives in an ongoing process, with periodic reports and reevaluations
and assessments. Reports need to set the stage and work to interpret results rather
than just cite a lot of statistics and let people
draw their own conclusions. The public does not understand what
racial profiling really means, and they do not look at the whole picture
(as discussed in Chapter 4).
Involvement with the media should be ongoing. It is unwise to wait
until negative publicity occurs and then expect the media to listen
and understand police processes and constraints. A pre-existing
relationship will generally yield more even-handed media coverage. A
department does not want to be in a position of reacting to bad press
or community outrage; it needs to be proactive in setting up media
and community interactions before misunderstandings develop. It is
also important to have the involvement of City Hall and support of
community leaders. In summary, the police must try to educate the
media and the community, and if possible, local politicians should
also be brought into the picture. Suggestions for police policies in this
regard include:
 Conduct business with openness and transparency
 Create relationships with the media to help foster understanding
of issues, strategies and processes
 Serve as an educator for the community and the media.
The participants agreed that the politicians are seldom at the table
when racial profiling is being discussed. They may drive agendas, but
they don't often meet with the chiefs or line officers to understand the
issues and look at the overall picture. The police see value from trying
to educate politicians along with the media and community. However,
this may be difficult to accomplish, as politicians have their own
interests to consider.23
5.5.2 Community Concerns
Community representatives view data collection as a positive step, but
indicate that all too often there is no real community participation.
Community leaders are often approached after the fact to give
endorsement to ongoing efforts. They recommend that community
representatives be engaged at the very beginning. The community
recognizes that crime is a problem, and it makes sense for community
members and the police to work together to define the biggest crime
problems and develop strategies to deal with them. This would help
the community to better understand police work and help the police
to better understand the community's needs.
23 Once phrase used was "politicians will be politicians." There was wide agreement
with this. Another observation was that other than the mayor's office, the councils
and legislators really do not understand the police department. One city reported
holding numerous community meetings to bring together the media, community, and
political groups. An important and sad fact is that the politicians are usually
absentthey rarely attend and often answer that they are too busy. This observation
was echoed by the other cities.

Collected data need to be analyzed and reported in a way that will help
community members to better understand police practices and to use
this information to help them interpret what they see on the streets.
For example, members of the minority community would like to see
whether Blacks and Whites get pulled over and stopped for different
reasons. In particular, are Blacks more likely to be subject to high-
discretion stops than Whites? Some community members feel that
Blacks are more likely to get pulled over for minor infractions that
serve as a pretext for finding criminal behavior.
Community representatives were also skeptical about whether the
average person can understand and draw implications from the
findings reported from data collection. Also, it is not clear how
much the community cares about data collection. Public relations are
handled at a different level and in different ways: Data collection may
be more appropriate as an internal management issue or tool.
Regular community meetings where citizens can ask questions and
air concerns are important. In addition, citizen members can serve
on review and disciplinary boards and then help field questions
at community meetings. Such practices foster positive levels of
involvement of major stakeholder groups.24
Community input can come via other avenues as well. For example,
community surveys can focus on citizens' attitudes toward police,
and ask citizens to characterize their interactions with police. Such
surveys can supply useful information on community perspectives, and
provide input from those who do not interact with the police.
To summarize, the following points were raised with respect to
community concerns regarding data collection:
 Concern that it will be meaningless
 The data should be relayed to the community in an
understandable way.
 The data should include information on activities other than
traffic stops.
 The data should be relayed to police in a way that is
instructive to the rank and file.
 Concern that data collection should not be allowed to substitute
for actual community contact, improved policies, or other
accountability procedures
 Concern that it will be falsely offered as evidence of good or
improved relations with the community/departments will consider
it enough to ensure good relations
24 One city indicated that citizen participation on review boards and community
meetings was ineffective.

 Concern that the community has been shut out of the
development process
 They should be consulted at the beginning and end of the
process.
 Police data collection should be supplemented by data collected
within the community itself.
5.5.3 Union Concerns
Some union representatives voiced strong opinions about racial
profiling issues and data collection. However, they were generally
more forthcoming in private conversations than during the general
sessions.25 The union representatives also did not form a cohesive
group, probably because the strength and influence of the unions
varied considerably across the cities attending the conferences. It
became very clear that unions serve very different roles in different
regions of the country.
One theme that did emerge, often from sidebar discussions, was
that some union members did not feel that racial profiling occurred
in any substantive fashion. They sometimes did not agree with the
definitions of racial profiling that were discussed, or they felt that
some of the actions defined as racial profiling were really just "good
police work" that should be supported as police officers doing their
job. Resentment was also voiced that investigations into racial profiling
were designed to reach pre-determined conclusions that racial profiling
existed, and that the data collection and analysis are not designed to be
fair to police officers.
In sidebar conversations, some participants seemed to support
instances of racial profiling being observed. This also establishes
a theme: Some police report they have seen or experienced what
appears to be racial profiling, yet they do not view it as a systematic
police practice. This view may be characterized in the following way:
Racial profiling may occur in isolated cases by some officers, but "we
are not trained or encouraged to use racial profiling, and these are
isolated instances." In other cases, the individuals flatly denied that
racial profiling is used. In part, this may be due to a lack of agreement
on the definition of racial profiling. However, even with an official
definition, people would still be likely to judge the existence of racial
profiling based on their own personal definition.
25 Possibly this was due to expectations of strong reactions to their viewpoints
from some of the community representatives and/or police leadership.

Findings from the Conferences
5.5.4 Overall recommendations for Issues That Should be
Addressed
CNAC asked the conference participants to give their
recommendations for issues that should be addressed. The following
issues reflect the top priorities for participants:
 The Department of Justice should address the issue of assisting
relevant parties to discuss and agree on an official definition of
racial profiling that is clear to everyone. It is important that there
be a clear standard to measure against.
 Officers should know how they are supposed to do business.
 Researchers can then know what they are looking for.
 There should be clear guidelines on how information on racial
profiling should be usedwho will own it, who will be responsible
for using it, how confidentiality can be maintained, and how
frequently reports should be generated and released.
 If data collection is a job appropriate for a "task force," then there
should be specific information about how to put together a task
force and make it work.
 Police departments need guidelines on how to establish
partnerships with local university researchers, and guidance on the
appropriate roles for local academic or public research groups to
play.
 Police departments need guidelines on how to interface with the
community regarding interpretations of the data and how data
should be released and presented to the community.
 Data collection and analysis can be costly. If data collection is
mandated, supplemental sources of funding should be identified.
Otherwise, competing needs that are more directly related to
traditional law enforcement activities will tend to be given higher
priority.

6.0 REPORT ON SITE VISITS
6.1 Technical Assistance Visits
Based on interviews and reviews of data provided by the city
police departments, CNAC identified several common issues that
significantly affect the ability to conduct and evaluate data collection
efforts. In most instances, the information provided during site
interviews was anecdotal and based on staff perceptions and hands-on
experience. Because much of the information provided was anecdotal,
and only three sites were visited, its findings are more illustrative than
definitive of issues that may affect data collection and evaluation.
A number of common themes as well as a number of technical
assistance suggestions emerged from the site visits. In addition, a
number of common concerns were identified. Each city also has
special local circumstances to take into consideration when crafting
data collection and evaluation procedures. The intent here is not to
identify the particular technical assistance issues associated with each
cityafter all, the cities may or may not choose to consider CNACs
recommendations. In addition, CNAC is not the operational expert
attached to the cities; it cannot know local circumstances as well as
local experts. Rather, the intent is to cull out general guidance and
concerns that are likely to be important both for the cities and for
other jurisdictions as well.
Theme 1: Some police department leaders, perhaps in conjunction
with local politicians, make decisions on whether and how to collect
data without:
 Discussing the issues with police officers
 Outlining the issues to be investigated
 Defining racial profiling in the context of their city
 Creating a clear study plan
 Allocating additional resources for evaluation
 Indicating what kind of evidence will indicate/not indicate the
presence of racial profiling
 Offering a plan to react to the evidence collected.
In other words, some police rank-and-file officers feel disenfranchised
because data collection decisions are reached without consulting all
those involved.
It appears that the leadership believes police officers are not
engaged in racial profiling, and that therefore it seems simple just
to demonstrate that this must be true. However, if a plan is not

specifically crafted to fit a city's particular circumstances, and internal
expertise is not available to work with and interpret results, the city
may get a measure that does not fit its needs and proves nothing.
Theme 2: Data collection and evaluation can be viewed as unfunded
mandates. The departments report that they lack the resources and
expertise needed to support a robust data collection and analysis
effort. In this context, resources may consist of funding, or of
computer capabilities to record information. Expertise may refer to
lack of computer or analytical expertise. Specific concerns reported
include:
 Inadequate manpower trained in analytical evaluation
 Inadequate computer (hardware) facilities
 Insufficient computer software evaluation capabilities
 Network-based systems that are not user-friendly to individual
analytical efforts
 Lack of expertise and resources to remedy computer/analytical
shortcomings.
Theme 3: An important issue is whether police departments should
conduct the evaluations and analyses or contract them out. First,
few departments have internal personnel with the expertise and
background to perform analytical evaluations. Second, departments
may feel that by contracting out the evaluation and analysis of the data
collected, they will present the image of objectivity. There is a fear
that if they do their own evaluations, community members and the
press will not trust the reported results.
However, contracting out the evaluation and analysis may create
disconnects because contractors may lack the knowledge of police
processes and/or city-specific information necessary to accurately
evaluate the data and reach supportable conclusions. In the discussions
with the cities, CNAC recommended that evaluation and analysis
be done with a mixture of resources. The in-house knowledge is
important because the operational expertise is associated at this level.
It may be difficult for outside experts to understand and interpret
a city's results as fully as city or police personnel can. Yet if a city
partners with outside analysts, it also gains analytical expertise
combined with objectivity.
The choice of blending resources offers other advantages. The police
department should retain some control over what questions are being
addressedthe study design. In addition, the department should work
along with outside researchers. When a report is issued, there should
be no surprises. While the police department may not agree with all
the findings of an outside research group, local or not, it is important
that it be aware of the results before the media see them.

Theme 4: Some officers who go out and do the work resent data
collection and evaluation for a number of reasons:
 They feel that the conclusions are already drawn, and that data
collection is just a set-up to "prove" that they are engaging in
racial profilingwhich is insulting.
 They have to waste time and resources engaging in the effort
which cuts down on their ability to execute their jobs properly.
 Outsiders who don't know what to look for will evaluate the data.
 A superficial evaluation will be likely to "validate" racial profiling,
and make them look bad. It is painful and insulting to be labeled
as racists.
 They fear the media will misrepresent the data and findings.
 They fear that data collected will become available to anyone
who asks for itthe media, politicians, individual citizens, outside
researchers. Specifically they fear:
 What kind of analysis will these people do?
 What kind of personal information may be released in this
way?
 Will it be used to damage careers, or harass individual
officers?
 Profiling is part of the jobthey do the job as they have been
taught, and part of the job is learning to recognize citizens
who have something to hide, who are guilty, who are likely to
have weapons, etc. They look for clues, and those clues may be
correlated with race, but that is not the same as racial profiling.
If primary clues involve non-race indicators, then some officers
do not consider adding race as a secondary clue to constitute
profiling (e.g., the person is out late at night near a drug trafficking
area, and also is of the wrong race to fit in the neighborhood).
6.2 Status of Data Collection Efforts
Data collection efforts in Chattanooga and Baltimore are proceeding
at this time, and present some interesting facets worth consideration.
Data collection in St. Paul is not a primary concern to the Department
at this point, as they feel that they have moved to a follow-on phase
to resolve racial profiling issues through training and officer focus
programs, pending additional evaluation of the data already collected
(by the University of Minnesota). In Phoenix, the data collected have
been focused on use-of-force issues, and there is no current data
collection effort for addressing racial profiling. We will describe the
data collection process for Chattanooga and Baltimore, and then
address briefly some of the pertinent issues present in St. Paul and
Phoenix.

6.2.1 Review of Current Chattanooga Police Department Data
Collection
The Chattanooga Police Department logs every moving citation that
each officer writes and every field interview each officer conducts.
The Field Interview and Vehicle Stops Report (FIVSR) captures
the information shown in Figure 1 on the next page. The form also
permits collection of detailed information on each person involved
in the stop (the primary contact, and three associates) and on the
vehicle. This information includes name, date of birth, social security
number, address, identifying characteristics, demographic information,
and aliases. This additional information is not collected on the State
Vehicle Stop Form.
As of January 1, 2001, the Chattanooga Police Department voluntarily
began participating in the State of Tennessee Vehicle Stop Form
(VSF) program. These forms are completed each time an officer stops
a vehicle. There is no information collected on the VSF that is not
also collected on the FIVSR. The only time filling out the VSF is not
a duplication of effort is when a stop is made but leads to no action at
all. Items collected are shown in Figure 2 on the next page.
The data collected with the FIVSR is currently being summarized on
two, one-page reports, which are given to the Chief on a monthly
basis. The first report is the Moving Citation Log Summary. It
captures the number of citations written overall, plus the number of
citations written by the traffic unit, and in each of seven geographic
zones (Zones A through G). These data are reported by race, by
gender, and for various cross tabulations of geographic zone, gender,
and race.

Figure 1
FIVSR Information
 The case number
 The complaint number
 The date and time of the stop*
 The location of the stop (sector, zone, beat) or interview*
 The officer's name and badge number*
 Race/ethnicity of the person stopped (African-American, Asian, Hispanic,
Caucasian, other/not apparent)*
 Approximate age of the person stopped*
 Gender of the person stopped*
 The reason for the stop (criminal, traffic)*
 Whether the stop was gang related
 Whether the stop was officer initiated
 The result of the stop (citation, written warning, verbal warning, arrest)*
 Whether a search occurred and if so, what type (vehicle, personal effects, driver,
passenger(s))*
 The legal basis for the search (consent,probable cause, incident to arrest, warrant,
inventory, plain view, safety factor)*
 Whether physical evidence was seized*
*-items are also collected with the State Vehicle Stop Form
Figure 2
VSF Information
 The ORI number (city)
 The date and time of the stop
 The location of the stop
 The officer's ID number
 The race/ethnicity of the person stopped (African-American, Asian, Hispanic,
Caucasian, other/not apparent)
 The approximate age of the person stopped
 The gender of the person stopped
 The reason for the stop (moving traffic violation, vehicle equipment violation,
criminal)
 The result of the stop (citation, written warning, verbal warning, arrest)
 Who the action was taken against (passenger, driver)
 Whether a search occurred and if so, what type (vehicle, personal effects, driver,
passenger(s))
 The legal basis for the search (consent, probable cause, incident to arrest, warrant,
inventory, plain view, safety factor)
 If physical evidence was seized
 Type of evidence seized (weapon(s), drugs, other)

The first report also shows the total number of accidents with
citations by zone and the number of warnings by zone. The second
report is the Field Interview Log Summary. It shows the number
of field interviews conducted overall and in each zone by gender
and race. Neither summary captures whether the contact resulted in
searching a car or an individual, although this information is available.
Currently, the Crime Analysis Unit responsible for organizing and
analyzing the data consists of only one person with no support staff.
The resident crime analyst does not have formal expertise in data
analysis, and accordingly feels somewhat unprepared to set up and
analyze the data collected. It seemed clear that the crime analyst would
also need to acquire access to software designed for data manipulation.
At the time of the visit, none of the data from the State's VSF had
been analyzed or reported. The Chattanooga Police Department
and other participating departments send their forms to the State
Comptroller's Office (a state requirement), but reported scanning
difficulties have prevented the State from conducting analysis. At this
point, the Chattanooga Police Department does not know what the
state is planning to do with the data, or how it plans to evaluate the
data. This is causing them some concern.26
Some members of the staff were apprehensive about the data being
collected with the VSF for the State of Tennessee for the following
reasons:
 Some are concerned that the goal of the program is to show that
departments across the state have been engaged in or do engage
in racial profiling, and that they are collecting data to support a
pre-determined conclusion.
 Supporting this notion is the perception that the VSF does not
capture enough detail on stops to portray an accurate picture of
Chattanooga police practices.
 Some also see the VSF program as inefficient and a waste of time
since the form largely duplicates most of the information they
already collect.
Some staff reiterated that they (and other departments in general)
are presumed to be guilty of racial profiling and must now prove
otherwise. This reflects an overall attitude that, in the court of public
opinion, they have already been convicted. However, they agreed
that they would support a "fair" data collection system and a "fair"
analysis.27
26 Other areas of concern are the level of detail captured by the state forms
and the method that will be used for aggregating the data. For example, used in
isolation, data collected with the state's VSF may not be able to take into
account officer deployment patterns across areas that differ demographically.
27 For example, a fair analysis would include data collected and analyzed at a
level of detail that would capture factors such the deployment patterns of officers
into racially diverse neighborhoods and directed stops for specifically described
suspects. The staff felt certain that they do not engage in racial profiling. However,
they agreed that they would abide by the findings of a fairand thoroughevaluation.

A final issue that emerged is the concern that any data that are
collected may become part of the public record. The media has
already had access to the department's personnel files, including the
Internal Affairs files. Therefore, it must be assumed that any data
collected either for the city or the state are likely to be obtained
by outside investigators at some point. This follows from state law
regarding public information.
6.2.2 Review of Current Baltimore Police Department Data
Collection
The Baltimore Police Department's data collection involves providing
citizen receipts after every officer-initiated contact.
Citizen/Police Contact Receipt
The data on the citizen's side of the receipt include:
 Date of stop
 Time of stop and duration
 Location of stop
 Officer's name and ID number
 Officer's assignment (post, assignment, unit)
 Citizen's name
 Citizen's date of birth
 Citizen's address and phone number
 A box to mark if the address is not in the city
 Citizen's gender
 Citizen's race (American Indian, Asian/Pacific Islander, Black, White, Hispanic, other,
unknown)
 Reason for stop (driving related, vehicle equipment, stop and frisk, field interview,
other), plus explanation
 Action taken (traffic citation, repair order, criminal citation, warning, arrest, other), plus
The data on the other side of the receipt include:
 Whether the citizen has a driver's license, an ID card, or another form of ID
 The state where the ID was issued
 The license or ID number
 The license plate number and state of the vehicle stopped
 The year, make model, and color of the vehicle
 Whether a search was made and what type (person, vehicle, property, consensual, other)
 Whether an item was seized (firearm, CDS)
 Receipt numbers of other receipts issued as part of the same stop.

Prior to issuing the Citizen/Police Contact Receipt, the Department
collected data from Field Interview reports. Officers entered
information in this database voluntarily if they thought that the
information would be useful for continuing or later investigations.28
28 The Department expects that the collection of racial profiling data will soon
be mandated by the state. They say that they are already collecting most of what
they expect the state to require. They believe the state's plan for data evaluation
is to give the data collected to the University of Maryland for analysis.
Baltimore Police Department Data Collection Analysis
The Baltimore Police Department data are currently being analyzed at
the city level, and there are plans to do future analysis at the precinct
level. Data are presented to the mayor at bi-weekly meetings. In
addition to the bi-weekly reports, the Baltimore Police Department
has also done 3 and 6-month interim reports that have more detail and
were used for internal purposes only. At the time of the visit, results
from a six-month collection period were discussed, involving about
89,000 records.
The Baltimore Police Department has a multi-person staff to address
analytical questions, but as they have a large amount of data to
analyze, they consider themselves under-staffed. The officers CNAC
spoke with seem somewhat comfortable with data analysis, but they
do not have a formal background in research methods. Another
consideration is that the data are stored in a Lotus Notes database,
which is apparently better for handling documents than data. In
particular, Lotus Notes doesn't offer enough flexibility for officers to
generate anything other than canned reports set up by a consultant
programmer who is only on site two days a week. In addition, there
are issues with hardware. The data and the software live on the
Baltimore Police Department network, which is very slow. This means
that generating reports is time consuming from a data processing
standpoint.29
29 As part of CNACs technical assistance, it spoke to the data analysts about doing
initial analysis on samples of their data, reserving full data runs for final reporting.
89,000 observations yield almost too much data.
The staff CNAC spoke with accept that they are going to collect racial
profiling data, and would like to get additional information from the
data if possible. In particular, they were very interested in using data
to inform management decisions. As for police-community relations,
the general feeling seemed to be that tensions had diminished once the
receipt program began. The view is that people are happy with some
attention being given to the problemthey feel that their complaints
have been heard and addressed to some extent.
Maryland does not have "public access to records" laws similar to
those in Tennessee and Arizona. However, it is not clear whether
information from the receipts will eventually become part of

the public record. The current thinking is that raw data can be
disseminated so long as neither police officers nor citizens can be
identified.
6.2.3 Review of Current Phoenix Police Department Data Collection
Because Phoenix is not currently collecting data on racial profiling, the
goal of this trip was to understand the city's traffic stop procedures
and develop some ideas about how data collection could be
implemented in the future. CNAC also spent several hours talking in
detail with some of the officers and data analysts. Among the things
learned are:
 Since about 100 traffic officers issue most of Phoenix's traffic
tickets, using patrol officer deployment data will not capture the
allocation of traffic officers.
 These officers are sent to specific locations based on a formal
system of recorded traffic complaints. There is also a formal
system for recording how each complaint is addressed by the
traffic units and where each unit is assigned.
 Arizona's "reasonable and prudent" traffic laws require officers to
establish clear violations of traffic laws. Speeders must be going
about 15 miles over the speed limit to be stopped.
 Officers need to use radar or laser and observe the car visually.
This often means tracking them as they approach and after they
pass the traffic officer (and it also means that the officer has a
better chance of determining the driver's race and sex). However,
even under daylight conditions, it is difficult to determine some
drivers' race or sex until they are pulled over.
 Phoenix addresses are very confusing. Some post offices with a
Phoenix street address are not in Phoenix; some post offices with
Scottsdale or Mesa addresses are within the Phoenix city limits.
This might prove to be a minor complication in using Phoenix
demographic data.
 There are additional problems with using traffic accident data as a
measure of available or violator populations since the ticket for a
traffic accident is often indistinguishable from a speeding ticket.
The data analysts in Phoenix are currently considering three future
approaches:
 Conducting a citizens' survey based in part on the BJS police
public contact survey, but also measuring citizen's general
assessments of the police.
 Conducting some systematic police observations as a way to get a
handle on what actually goes on in police stops.

 Using existing police traffic data supplemented with improvements
in recording race and ethnic data (Hispanic currently recodes as
Caucasian).
There are difficulties in implementing these approaches, since they
require obtaining representative samples of data from citizens in
general, and from citizens stopped by police. It might be possible
to link citizen assessment of stops with officer records of stops at
the individual stop level. This type of information may be more
appropriate to use for identifying issues in police practices rather then
for quantitative analysis.
Another issue explored was "be on the look out" BOLO stops and
how their effectiveness might be measured. One consideration is
whether or not BOLO stops are effective in actually catching someone
(how low/high are the hit rates). It is clear that citizens expect police
to look for suspects that get away and that such stops are legal.
However, it is not known what proportion of police stops were of the
BOLO type. In addition, the effectiveness of BOLO stops also has to
do with the amount of discriminating detail in the descriptions of the
suspect, and the time and distance from the precipitating event. Some
Bolo stops may actually happen months or years after the notice.
6.2.4 Summary Review of Current St. Paul Police Department Data
Collection
Initially, officers in the St. Paul Police Department collected data
using their CADS system. They evaluated their data and issued a
report at the request of the city council. They also turned the data
over to researchers at the University of Minnesota for a more formal
analysis. They are still waiting for final results from the University of
Minnesota. In the meantime, they have been caught up in the issue
of whether to have officers issue business cards whenever they stop
someone.
The community representative, who represents the NAACP, said
the NAACP is willing to wait for the results of the University of
Minnesota study now that the initial data collection effort is over. The
police department feels that the data collection process has helped to
improve the relationship between the department and the community.
The community representative indicated that initially members of the
NAACP resisted data collection efforts because they considered it
insulting that racial profiling would have to be proven. However, they
now consider that it is appropriate to demonstrate proof that there

is a problem. Data collection also can serve to delineate appropriate
corrective measures. For example, it is crucial to know if these are
the consequences of bad apples or biased training. In the first case,
the officers need to be identified and stopped. However, if the fault
lies with police department initiatives, then procedures will need to be
changed.
Other issues that were raised involve identifying "reason for the stop"
as important for determining and uncovering bias. For example, if
Blacks are subject to high discretion stops, while Whites are subject to
low discretion stops, a pattern emerges which needs to be investigated.
In addition, the union representative raised a concern with whether
the data collected has enough detail to give an accurate representation
of police practices.
6.3 Overall Recommendations for Technical Assistance
It is important to establish linkages with the professional research
community. Police departments can benefit substantially from
consulting with analytical experts. Ideally, the departments can
approach local analytical groups to establish a mutually beneficial
partnership. The word partnership is an important recommendation:
An ongoing shared dialogue should characterize the relationship. The
police department and professional analysts should work together, not
as separate entities.
Computer issues are also important. However, the needs of
hardware and software depend critically on the size of the database
being collected, and the scope of the analysis under consideration.
Depending on how the police department network is set up, it may
be inefficient to use a shared police network. If that is the case, it is
best to extract the data being collected to investigate racial profiling
and move the data to a stand-alone system. Stand-alone systems
may provide superior processing with respect to speed as well as
specialized software not generally available on police computer
networks. Most departmental requirements for data analysis can be
met by a reasonably sophisticated Pentium PC, and do not require
a major financial investment for hardware and/or software. On the
other hand, internal processing and evaluation may require training of
personnel, which would be more costly and time-consuming.

It is also time-consuming for individual department representatives to
become knowledgeable about the existing literature on racial profiling.
As part of providing technical assistance to the participating cities,
a CD was created containing electronic versions of selected papers
and presentations collected from various sources. This included 22
U.S. single-site studies, 11 general studies, and 10 British studies.
CNAC provided a copy of this CD to each participating city. This
is not intended to be a comprehensive source of information, but
to provide each city with a good starting point in its evaluation of
external studies of racial profiling issues. The details of the papers and
presentation information included in the CD are found in
Appendix D.

Subject Matter Expertise: Viewpoints from NOBLE
7.0 SUBJECT MATTER EXPERTISE:
VIEWPOINTS FROM NOBLE
In the course of this study, CNAC sought operational perspectives
to go along with consideration of the analytical issues involved. This
section presents viewpoints associated with members of the National
Organization of Black Law Enforcement Executives (NOBLE).
Note that this is not a single point of view. Since racial profiling and
data collection issues are complex matters, it is unlikely that a single
viewpoint will capture the outlook of all an organization's members.
The primary source for this section is Ronald Davis, a captain with the
Oakland Police Department.30 He is also a vice-president of NOBLE,
and has written and presented widely on the subject of racial profiling.
He served as a subject matter expert at both of the conferences.
By articulating an example of how the Oakland Police Department
has approached collecting and analyzing data, Captain Davis
demonstrates some of the potential pitfalls of overly simplified
analysis using actual data instead of hypothetical cases. In addition to
providing a powerful example of real world analytical issues, Captain
Davis also outlines a template for a police department approach
to multivariate analytical methods by sequentially examining and
comparing selected data.31
Although this approach falls short of yielding the power of
simultaneously examining and disentangling multiple influences, it
provides a logical, systematic, and comprehensible approach which can
be used in lieu of true multivariate research expertise. The Oakland
methodology approximates more conventional multivariate research
methods and may be more easily understood by police department
personnel, community, and media representatives.32
In his opening comments for the conference participants, Captain
Davis began by drawing a distinction between racial profiling and
bias-based policing, by asserting that the former is a symptom of the
latter. He also noted that by addressing the issue of racial profiling
without understanding that it is the symptom of a larger problem,
responsibility for social and departmental bias is put on the shoulders
of the rank and file. He feels that systemic reform is required, and
data collection is only a first step in the process. Data collection and
analysis can be used to identify specific problems and to measure
improvement.
30 In this section of the report, CNAC is primarily using material collected and
prepared by Davis in his capacity as a law enforcement practitioner and in his
position in NOBLE. Davis has used some of these examples in previous presentations
and at our conferences. CNAC also include some material from other NOBLE members.
Unless otherwise noted, the material in this section is derived from Davis.
31 In more technical terms, this approach is essentially a linear stepwise approach
via nested pairwise comparisons.
32 The Oakland Police Department is now partnering with RAND to use multivariate
research methods.

Points About Collecting and Using Data
Most data that are being collected relate to traffic stopse.g., what are
the characteristics of the individual who is stopped and of the officer
who made the stop, why was the stop made, what happened during
the stop, and what was the result of the stop? However, little thought
is given to an important issue: the deterrent effect of these traffic
stops.
At least three important questions should be addressed before a data
collection effort is undertaken: 1) What is racial profiling? 2) Why
are we collecting data and what do we hope to learn? 3) How will we
judge the effectiveness of policies enacted based on data analysis?
Also embedded in the current debate is whether or not data should be
collected which identifies individual officers.
Definition of Racial Profilingthe 60/60 Dichotomy
Captain Davis, speaking during our conferences, said that to properly
analyze racial profiling, it needs to be carefully defined. Once defined,
it can be determined whether it exists, to what extent it exists, and
how to fix it. Devising a common definition of racial profiling is
important because if the community and the police department don't
agree on the definition, then a perceived problem can't be fixed. It's
likely that disagreement over the definition of racial profiling is what
has led to the "60/60" dichotomy in which 60 percent of police chiefs
(in a PERF survey) say that racial profiling is not occurring in their
departments, while 60 percent of the people say that it is occurring.
For example, if racial profiling is defined using race as the sole
determinant for a stop, then chiefs will say that their officers are
not profiling based on race. Or, consider the definitions offered by
Ramirez (Ramirez et al. 2000) and Harris (Harris 2002), which indicate
that race can be used as a descriptor (i.e., if it is part of a suspect's
description), but should not be used as a predictor of criminal
activity. In addition, it is important to know what definition of racial
profiling was used in a study that you read or in a survey whose results
are being considered. In general, although few studies use surveys, it is
important to know how survey questions were worded.

7.1 Positives and Negatives of Data Collection
(This material was provided by Captain Davis based on a report he prepared
for NOBLE, Racial Profiling: "What Does the Data Mean?" The report is a
practitioner's guide to understanding data collection and analysis.)
Many people believe data collection is necessary to end racial profiling.
Others believe data collection offers no practical value and simply
validates what we already know. Is data collection practicala critical
step to ending racial profilingor is it merely symbolicnecessary to
appease the minority community in hopes of instilling public trust?
On one hand, data collection is practical as a management tool.
Statistics facilitate making intelligence inferences from data. Proper
data collection and utilization of credible benchmarks not only
provides an organizational "snap shot"a look at the organization
at a specific point in timeit assists administrators in identifying
institutional and systemic problems. Data collection is also symbolic
because it is a gesture of openness to the community and a
commitment to equality. It translates into "we have nothing to
hide" and represents the willingness of law enforcement to take an
introspective look to prevent disparate treatment. It also demonstrates
law enforcement's true commitment towards community needs and
concerns.
On the other hand, improper data collection and inaccurate data
analysis contribute to negative perceptions in the community and
negative perceptions of law enforcement, and they result in an overall
lack of confidence in the process. False expectations of data analysis
can also contribute to negative perceptions in both the community
and the agency. Most people agree that data collection is not a panacea
for racial profiling, but good data collection and analysis can be a
critical first step in developing solutions to ending racial profiling.
7.1.1 Data Collection and Analysis
Data collection alone will not solve the issue of racial profiling. It
should, however, serve as a tool to illuminate the issues and identify
operational systems and programs that may be influenced by bias or
result in disparate treatment. It is important to remember that data
collection must be done in the appropriate manner, and that analysis
must be done in an accurate, thorough, and fair manner in order for
positive outcomes to be observed. If any of these steps are done in
such a way as to cast doubts upon the conclusions, participants may
conclude that the entire project is invalid.

It is critical to define the purpose of data collection before deciding
what data to collect, so that the goals will be reachable. In other
words, know what questions are asked and have in mind what steps
must be taken depending on the answers found. In the context
of racial profiling, the purpose of data collection is analysis and
applications to illuminate the answers to questions. Analyzing the data
properly allows the information to be used to benefit law enforcement
and the community.
An Early Benchmarking Example
Many people consider San Jose Police Chief William Lansdowne to
be the "father of data collection" with respect to racial profiling. The
San Jose Police Department was one of the first law enforcement
agencies in the country to voluntarily collect traffic stop data. Chief
Lansdowne's decision was based on concerns of the minority
community. He led the San Jose Police Department in developing and
implementing a data collection program and was applauded by the
ACLU, the NAACP, and many other civil-rights and community-based
organizations for his courage and commitment.
When Chief Lansdowne released his first data-collection report, it
showed a disparity (less than 10 percentage points), between traffic
stops of Hispanics compared to the percentage of Hispanics residing
in the city. The department came under immediate criticism from a
few civil-rights and community-based organizations because the stop
statistics did not exactly match the demographics of the city.
This type of comparisonvehicle stop data against citywide census
databecame the national trend. The 1990 Census and aggregate
citywide demographics became the sole benchmark for many people
and organizations. Racial profiling and discrimination accusations
were launched against police agencies based on this comparison. Not
only is this practice inaccurateit is outright irresponsible, and actually
contributes to negative perceptions in the community. As a result,
many police administrators are apprehensive about data collection
for fear they too will be accused of racial profiling and racism based
on statistical disparities. Effective benchmarking must incorporate
the complexities of effective policing, as well as societal and cultural
disparities.
Baseline Comparison Data (BCD)
Census data often fail to provide an effective data analysis benchmark
or baseline. The census shows the percentage of citizens residing
in a city; it does not provide the number or demographics of the

actual drivers or traffic violators, which by most accounts yield the
most effective baseline. The census does not provide the number of
people that visit or drive through a jurisdictioncommonly referred
to the "daytime" population. To the extent possible, police agencies
should utilize professional researchers to conduct statistical samplings
and surveys to determine violator-demographics and the daytime
population. In the absence of statistical sampling, agencies that use
census data must narrow the data to persons of driving age and
incorporate all relevant local variables, as will be discussed later.
In addition, aggregate percentages do not reflect racial or ethnic
population density. Many neighborhoods are predominately one race
or ethnicity. Consequently, the number of officers assigned to and
stops conducted in these neighborhoods may skew the aggregate
data. Most police agencies deploy staff based on population density,
reported crimes, and calls for service and then divide the city into
beats, districts, precincts, or areas. High-crime areas generally have
more officers assigned to them. If higher percentages of officers are
assigned to areas that are predominately one race or ethnicity, the
number of stops will be higher for that race or ethnicity.
These disparities are not a result of the police tactics. These disparities
are societal, based on many factors ranging from historic racism and
discrimination to education and socio-economic conditions. The
police should not be held accountable for societal-based disparities,
unless these disparities are used to form biases and stereotypes that
are then applied in policing.
Case StudyOakland, California
Oakland can be used as a case example of how data collection
can be both improperly and properly applied. By working through
consecutive applications of data collection and analysis, it is possible
to highlight an appropriate approach to investigating racial profiling
issues. It demonstrates how hasty conclusions can lead to incorrect
assessments of the situation.
Oakland is approximately 36 percent African-American, 23 percent
Caucasian and 26 percent Hispanic. It is divided geographically
along historic racial-geographic linesareas in which the majority
of the population is of one race or ethnicity. In Oakland, about 85
percent of the Black population resides in an area referred to as the
"flatlands," and about 85 percent of the White population resides
in an area known as the "hills." The flatlands area is a high-crime,
low-income area. The hills area has lower crime and more affluent
neighborhoods.

Oakland is also divided into three police areas. The demographics
differ in each police area and in addition differ from the aggregate
census demographics. The flatlands and hills are not police
designations or official police precincts. They are historic racial-
geographic boundaries (named by the community) that encompass
parts of all three precincts. Although 85 percent of Oakland's black
population resides in the flatlands, it represents only 50 percent of
the aggregate flatland demographics. And although, 85 percent of the
white population lives in the hills, it too represents only 65 percent of
the hill demographics.
Approximately 85 percent of crime reported in Oakland is committed
in the flatlands. Of approximately 100 officers assigned to each watch,
85 are assigned to the flatlands and 15 in the hills.
Establishing Benchmarks for Oakland
Before compiling and comparing data, it is important to first establish
a benchmark. One method is to identify the "perfect" data set and
statistical match. In other words, what would the statistics reflect
if all of the stops the officers conducted matched perfectly with
the demographics of the areas to which they were assigned? The
key to this method is to delineate each area because this determines
what baseline data will be used. The next decision is whether to
use the aggregate census data, the precinct demographics, or the
racial-geographic statistics. As discussed above, the best baseline for
Oakland is racial-geographic.
The next step is to identify staffing deployments relative to the
racial-geographic boundaries. As part of the "perfect" data model,
each officer stops the same number of people, whose demographics
match perfectly with the areas assigned. The chart below establishes
a "perfect data model" racial-geographic baseline for the City of
Oakland.
Location (Area)
No. of officers (100)
No. of stops (10,000)
No. of blacks in area
Total no. of blacks stopped
Hills
15
1,500
19%
285
Flatlands
85
8,500
50%
4,250
Total
100
10,000
100%
4,535
The perfect model results are based on the assumption that each
officer conducts 1,000 stops that perfectly match the demographics of
assigned areas. Using the racial-geographic percentages, 4,535 out of
10,000 stops should be black (45 percent of stops). Aggregate 2000

Census data say that Oakland is 36 percent Black, therefore, there is
a nine percentage point disparity between the model prediction and
simple city-wide Census demographics.
If data collection revealed that 45 percent of stops were of Blacks,
many observers would see a disparity and immediately accuse the
police of racial profiling. This is inaccurate. The 45 percent figure
actually represents a reasonable stop-benchmark for the City of
Oakland, by taking into account population density and staffing
deployments.
The apparent disparity would be the result of a majority of reported
crime being committed in an area that is predominantly Black.
Consequently, a majority of officers are deployed in this area. It is
only reasonable to expect that where there are more officers, there will
be more stops. The apparent disparity would represent societal-based
disparities, not police-based disparities.33 In addition, data collection
findings of stop-percentages for blacks of greater than 45 percent
might or might not indicate police disparities or racial profiling,
depending on circumstances. In actuality, the data collected in 2000
show that 48 percent of stops were of Blacks.
Extending the Perfect Model Approach to Consider Searches
When reviewing search and post-stop data, it is important to recall the
distinction between traffic stops and crime compared to searches and
crime. Many argue that the crime rate and the suspect or perpetrator
demographics determine the demographics of the stops, not traffic-
violator or population demographics. Many chiefs and managers state:
"If minorities are committing more crime, I expect my officers to stop
and search more minorities."
Most law enforcement officers believe traffic stops are effective in
"catching bad guys," thereby reducing and preventing crime. However,
some evaluations raise questions about this premise. Recent traffic
stop data reveal that only 3 to 10 percent of traffic stops result in
arrests; over 65 percent of those arrests are traffic-related violations
or warrants, not the crime offenses used to justify making traffic stops
based on perpetrator demographics.34
33 It is important to note that although 85 percent of reported crime is committed in
an area that is 50 percent black, this does not mean that the majority of blacks commit
crime. Law enforcement should not use this information to create biases and stereotypes
to target minorities, but to effectively deploy staff in areas where they are most
needed and to develop strategies to improve the quality of life in high-crime
neighborhoods. Even if it is true that minorities commit the majority of reported
crimes in certain areas, it is most likely that the percentage of people committing
crimes represent less than 10 percent of that minority group. It is unreasonable to
cast suspicion on an entire group or class of people, based on the actions of a few.
34 These traffic stop data provided by Captain Davis are from several cities, including
Oakland.

If empirical data do not suggest that traffic stops reduce or prevent
crime, it is not reasonable to expect officers to conduct stops based
on the demographics or profiles of criminals. It results in race and/or
ethnicity being used as a predictor of crime, versus as a descriptor
of a suspect. It constitutes racial profiling and is a violation of the
Fourteenth Amendment of the Constitution.
However, although there is not necessarily a nexus between car stops
and crime reduction, there is a direct nexus between searches, post-
stop activities, and crime. A search should not be conducted unless
there is probable cause to believe a person has committed a crime.
Therefore, search statistics and post-stop activities must be analyzed
using different benchmarks and baseline comparison data.
The most effective baseline data for searches and post-stop activities
are data on "reported crime," but this does not mean suspect
demographics. It means agencies should plot reported crime by police-
geographic or race-geographic lines. The searches should match the
percentage of crime in an area relative to the demographics of that
area. As discussed earlier, in Oakland 85 percent of reported crime
occurs in the flatlands, so it is reasonable for 85 percent of vehicle
searches to be conducted in the flatlands area, which is 50 percent
black. This evaluation may also be subdivided to smaller geographic
areas based on search density and police geographic demographics.
Agencies should plot where the searches are conducted and compare
search density to reported crime density and local demographics.
Applying the Search Patterns to the Case Study of Oakland
Examining data collection for Oakland reveals that 65 percent of
searches conducted were on African-Americans. This appears to
be a 29 percentage point disparity, based on simple population
demographics that show Oakland is 36 percent black. The next step is
to identify whether the disparity is police or societal-based, or both.
Once again, the baseline data and benchmark must be identified
before comparing search data. The "perfect" data set is once again an
effective method of establishing benchmarks. In post-stop categories,
such as searches, the census, precinct and/or racial-geographic
demographics are not effective as the sole benchmark(s). Reported
crime relative to the stop-benchmark is the most effective benchmark.
In other words, the number of searches conducted by officers should
be proportionate with the percentages of crime committed in each
area. Racial-geographic boundaries is used as the search-benchmark to
overlay reported crime and searches.

The actual Oakland search data indicate that there were 2,229 searches,
with 90 percent (2,006) of the searches conducted in the flatlands, and
10 percent (223) of the searches conducted in the hills. The net effect
was that 65 percent of searches were conducted on blacks. Using
the percentages of blacks in the hills and flatlands, multiplied by the
number of searches in the hills and flatlands, yields an expectation
of 47 percent of searches on blacks. It is important to note that this
observed disparity (65 percent versus 47 percent) does not necessarily
constitute police-based disparities or racial profiling. Other variables,
such as probation and parole considerations and local factors, should
be examined before reaching that conclusion.
Additional Factors to Consider
There are approximately 11,000 people on probation and parole in the
City of Oakland. Approximately 700 parolees are wanted for some
type of violation, commonly referred to as "at-large," on a daily basis.
It is estimated that over 50 percent of reported crime in Oakland
is committed by persons on probation and parole. Recidivism rates
for persons on probation and parole exceed 70 percent. In the State
of California, persons on probation and parole are in many cases
subject to warrantless searches and searches without probable cause as
conditions of their probation and parole.
In response to these statistics, the Oakland Police Department
formed a Police and Corrections Team (PACT). The team targets
repeat offenders and provides education, training, and job placement
programs, as well as aggressive enforcement of parole and probation
conditions. The PACT program results in hundreds of stops and
searches of known persons on probation and parole. This situation
can skew the benchmark and provide "false positives," which may be
viewed as disparate and even discriminatory practices. In Oakland, 29
percent of all searches conducted were based on probation and parole
status; 79 percent of these searches were of African-Americans.
Several questions, however, naturally arise for the Oakland statistics.
First, what are the demographics of persons on probation and parole
in the City of Oakland? Where do they residethe flatlands or the
hills? The answers to these questions determine to what extent this
information contributes to the disparity identified earlier. They also
help determine whether the disparity is societal-based or police-
driven.35
35 If 79 percent of people on probation and parole in Oakland are African-American,
this will be consistent with the search data and reflect a societal-based disparity.
It would also be expected that 85 percent of people on probation and parole reside
in the flatlands, which is 50 percent African-American. This too is a societal-based
disparity that skews the aggregate search data.

Repeat Offenders
If the stop-data collected reflect 100 Hispanics stopped, do the data
reflect 100 Hispanics stopped once or ten Hispanics stopped ten
times? The answer to this question is a critical factor in data analysis.
One of the basic premises of community oriented policing is working
closely with the community to identify criminals. Successful officers
recognize known criminals, whether drug dealers, burglars, or auto
thieves, many of whom may be on probation and/or parole.
Officers may stop and detain persons on probation and parole, or
known drug dealers, multiple times during a data-collection period.
The intent of the stops varies: Some cases may be reasonable
suspicion that a crime is in progress, while others are based on
probation and parole status, including invoking search clauses. Many
cases may be based on a pre-textural traffic stop to "dig" further into
suspicious behavior of known criminals. It is crucial that the status of
repeat stops be captured as part of data collection.36
36 The category repeat offender can be added to data collection forms,
with instructions for officers to note if they have ever stopped the person currently
being stopped within a specified time period. The time period should coincide with
data collection and analysis time frames.
Consideration for Special Programs
Another variable to consider in data analysis is the existence of
special enforcement programs.37 Programs such as drunk driving
checkpoints, seatbelt enforcement, and homicide suppression units
can result in disparate stop statistics depending on their purpose
and location. Seatbelt compliance offers an example of the possible
influence of special programs. A recent medical study38 revealed that
African-Americans have seatbelt non-compliance rates that are three
times higher than any other race or ethnicity. Consequently, African-
American youth are victims of traffic fatalities at similarly disparate
rates.
37 An example of the "special units" discussed in Chapter 4.
38 "Achieving a Credible Health and Safety Approach to Increasing Seat Belt Use Among
African Americans," Meharry Medical College, Nashville Tennessee, sponsored by a grant
from General Motors.
The disparity is relevant and even useful to law enforcement, though
not in the context that police are justified in stopping more Blacks
on the chance they are not wearing seatbeltsthat is racial profiling.
Rather, the disparity is relevant in the context that education,
prevention, and enforcement programs should be focused in the
minority community to increase seatbelt compliance and decrease
fatalities. As mentioned earlier, the link between car stops and crime
reduction is not clear. There is, however, a direct link between traffic
enforcement and traffic fatalities. Therefore, aggressive seatbelt

enforcement programs may be appropriate in communities suffering
from high-fatality rates, regardless of the race of the group not
wearing seatbelts.
Officials may fear that the inevitable skewed stop-statistics from an
aggressive seatbelt campaign will be viewed as racial profiling, with
consequent unpleasant effects. Unfortunately, this is probably true in
many cases. However, the agency can justify stop-disparities based on
data collection (both traffic fatalities and traffic stops) and an accurate
analysis that considers all locally relevant variables.
One key to an aggressive enforcement program is to first identify
clear goals and objectives, such as the increase of seatbelt compliance
and the reduction of traffic fatalities through enforcement.39 For this
program, the "hit" rate will be the number of stops in which people
are not wearing their seatbelts, not arrests or narcotics seizures. More
than likely, the stop rate will be disparate, but this is based on societal-
based disparities, not police-based disparities. The other key will be
post-stop activities. Although more minorities may be stopped, the
length and scope of the detention should be the same as for non-
minorities, unless there are other local variables to consider. These
other variables, however, should be validated through a "hit" rate to
justify their use.40 In other words, the goal is to find good police work
versus poor guesswork.
Agencies should also designate these stops as special enforcement
when capturing stop-data. These stops should be analyzed both
separately from the aggregate data and as part of the aggregate data.
By establishing clear goals and objectives before implementing the
program, officers will understand the program's purpose and how to
define "success."
Many critics will say that focusing enforcement programs in the
minority community is profiling and is wrong. However, it is not racial
profilingit is responsive policing. Failing to respond to high traffic
fatality rates is wrong. Enforcement programs designed to increase
seatbelt compliance should be focused in the communities where there
is the most need. In this case, the program should be focused in the
minority community. Law enforcement does not need to apologize for
enforcing the laws or for targeting criminal behavior or behavior that
threatens public safety (such as seatbelts).
39 Agencies implementing these types of programs should consult with their community
prior to the program and discuss the potential outcomes.
40 A hit rate can provide evidence to establish the efficiency of the local variable
or consideration in use. If the policy or action does not have a high yield rate, it is
of questionable value.

Can Statistics Be Misleading? Interpretation Issues: Two Examples
The question of whether racial profiling exists in a specific situation
cannot be answered by data alone. The answer to this question
must consider, among other things, stop data that incorporate local
variables, community perceptions, citizen complaints, misconduct
allegations, policies and practices in place, special programs
implemented, training, officer feedback, and agency mission-visionvalues programs.
Although there are many variables that can skew data analysis,
there is significant value in data. The question that must be asked
is what intelligent inferences can be made. It is possible to identify
organizational bias, either in operational systems or in functional
programs. Statistical disparities do not automatically constitute
discrimination, racial profiling or even bias-based policing. However,
the degree of the disparity, the area or categories of disparities, and
context in which disparities exist may signal "bias."
Single data disparities taken alone may not have much value; however,
when in combination with topical disparities, the data may indicate
bias and identify systems and/or programs that are resulting in
disparate treatment. However, the interpretation of data disparities
must be approached with caution. Even very specific and thorough
analyses can be interpreted in different manners, leading to different
conclusions.
The next chart provides a theoretical case of when statistical
disparities may signal bias.
Race
Stops
Violation(s)
Searches
Search Basis
Search
Arrests
Black
High
Equipment/ Mechanical
High
Consent
Results Low Yields
Low Arrests
White
Low
Moving/ Low Discretion
Low
Discretion Probable Cause
Low Yields
Low Arrests
There may be reasons for the disparities outlined in this chart. Absent
these reasons, (e.g., staffing deployments, special programs) the
disparities in this chart would seem to indicate bias. The fact that the
majority of the Black stops are mechanical or high-discretion coupled
with high or disparate search rates indicates exploratory stops and
searches. That a large percentage of searches are consent, with low
yieldsalso known as "hit rates,"indicates the exploratory searches
may be based primarily on biases and stereotypes.

In this case, the administration may want to identify what criteria
officers are using to determine consent searches. Although officers
may legally conduct consent searches on anyone, the data reveal
possible bias and ineffectiveness. This agency may consider
implementing policies to outline consent search protocol and
supervisory responsibilities.
The next chart outlines a theoretical case in which statistical disparities
are explainable and reasonable.
Race
Stops
Violation(s)
Searches
Search Basis
Search
Arrests
Black
High
Seatbelt High Discretion
Low
Probable Cause
Results Low Yields
Low Arrests High Citation
White
Low
Moving/ Low Discretion
Low
Probable
Cause
Low Yields
Low Arrests
Low Citation
In this case, there are disparities in actual stops and specific types of
violations. Post-stop data such as searches and hit-rates are relatively
the same. Citation rates are somewhat higher for blacks than whites.
At face value, many would focus on the high-stop rates for blacks
versus whites, especially if the percentage variances are more than five
percentage points and higher than the aggregate census data. Most
likely, the citation disparity would also fuel the news headline that
could read: "Blacks stopped and cited more than Whites."
In fact, however, there are locally relevant variables that may explain
this disparity. Special programs such as seatbelt enforcement or
others may be conducted in minority neighborhoods based on need,
community concern, and even at the communities' request. The
point is not to immediately assume racial profiling without further
investigation.
Officer IdentificationMore Pluses and Minuses
There is valid concern by rank-and-file officers that the current
inability to establish credible benchmarks and accurately analyze the
data will result in officers being falsely labeled as racists. There is also
a concern that the information will be used to file frivolous lawsuits
against individual officers.
NOBLE recommends that the decision to identify officers, in data
collection and analysis efforts, should be left to the police chief.
Although there is definite value in officer identification, there is also

great potential for misuse, which might further deteriorate police-
community relations, impact organizational morale, and compromise
the integrity of the data collection program. Collecting individual
officer data during the initial phases of data collection programs may
well lead to distractions that will cloud the issues.
However, a mature data collection effort may want to consider
individual officer identification as a valuable tool for both
early warning systems and officer management and efficiency
considerations.41 Administrators must also ensure that the individual
officer information is treated as strictly "confidential" and to the
extent possible, afford the information the same protections as
personnel files.42
The same principles for organizational analysis apply to individual
officer analysis. There are numerous variables that must be considered
when establishing benchmarks. Even precinct demographics are not
necessarily effective. Officers patrol smaller geographic areas, and
the demographics of those areas must be extracted from census
tracking data. Depending on the location of the officer's beat or area
assigned, there may be major thoroughfares or areas with high daytime
populations to factor in. Officer search and post stop data generally
cannot be compared to overall departmental averages. Each beat and
officer will require tailored benchmarks, depending on the relevant
local variables.
Identifying officer characteristics, such as age, length of service, race,
and gender may provide valuable information for organizational
assessment. Although many data fields can be useful, data collection
should respect practical limitations, based on what administrators
define as the goal(s) of data collection. If data collection is
designed to assess organizational behavior and effectiveness, officer
identification is valuable, but not necessary. If an agency is attempting
to identify organizational systems and operational programs that
may be influenced by bias, officer identification is valuable, but not
necessary. If an agency is attempting to identify "racist" officers or
officers engaging in racial profiling (the bad apples theory), then
officer identification is necessary. However, no single data set will be
likely to accomplish this goal.43
41 In this context, the data obtained will be only one of many factors (e.g., complaints
filed) to determine whether officers are engaged in inappropriate behavior or whether
their behavior suggests there are problems in need of immediate intervention. In addition,
the decision to identify officers should be based, in part, on the communities'
understanding and knowledge of racial profiling and data collection and analysis. If
the community understands benchmarks and the variables that skew aggregate data, there
is less likelihood the information will be misinterpreted and misused.
42 This will vary by jurisdiction, based on state and local government codes and public
information laws.
43 If an officer is engaged in intentional discriminatory practices, it is probably not
in isolation. An effective early warning system will track citizen complaints, rude
conduct, excessive force and other indicators.

In summary, NOBLE recognizes the value of officer identification,
but does not support legislation that mandates officer identification
as part of data collection. That decision should be left to local
authorities, based on local factors. NOBLE does recommend,
however, that to the extent possible, data collection programs include
officers' identification and merge with early warning systems.
7.2 Interactions: Mayor, Police Chief, Media, Community
The interactions of the police with other segments of the community
was a theme of Colonel Jerry Oliver, Chief of Police for Richmond,
Virginia, who served as a keynote speaker for the first conference.
Colonel Oliver is a NOBLE chief, and speaks eloquently of the
connections between the police and the community. He opened the
discussion by noting that "Police departments were formed to provide
services to free people in a democratic society."
Chief Oliver offered two main points: First, the real issue is one of
image and credibility. Police departments and officers no longer get
the benefit of the doubt from the communities they serve. Therefore,
community outreach is of utmost importance. Second, data collection
and analysis are not a cure to the problem and, thus, are not sufficient
by themselves to address the issue of racial profiling. Departments
must also have accompanying anti-profiling policies and professional
development.44
Chief Oliver also raised the following general points:
 Community outreach is being out in the community and bringing
the community into the department. So, in order to increase trust,
police departments and procedures must be de-mystified. Use
language people understand.
 An arrest is not a successit's a failure by the entire community.
To avoid this failure, it's necessary to have community
partnerships early on.
 Officers and managers should be accountable for their actions,
and incentives should be created that induce individuals and
departments to behave properly.
 Complaint processes should be citizen friendly and responsive.
 Any new effortdata collection, professional development, etc.
must be funded.
 Data collection for the sake of data collection is counterproductive,
and diminishes the credibility of police departments.
 Benchmarks and standards are critical, because data collection
alone will not give us the answers we need.
44 Pockets of corruption (or bigotry) will diminish credibility, and must be screened out.

Involving the Stakeholders
Captain Davis discussed this theme as well, stating that the key
to successful data collection lies in the process as much as the
actual result. It will not be effective to engage in data collection
and evaluation in a vacuum, even if the data collected support
a conclusion that no racial profiling is occurring. If the various
stakeholders are not involved in the process, they are likely to feel
disenfranchised and suspicious.
The most effective agencies have formed local task forces that involve
all stakeholders in developing data collection programs and identifying
local variables to establish data analysis benchmarks. The task force
should comprise representatives from civil-rights and community-
based organizations, rank and file, supervisory and command officers,
police union representatives, and local minority law enforcement
organizations.
The primary purpose of the task force is to develop data collection
and analysis processes that fit the local agency and community. The
task force can identify local variables necessary to establish credible
benchmarks and market the department's data collection and analysis
efforts, which establishes credibility in the process and instills public
trust. The task force can also assist in developing racial profiling
policies and training.
Civil rights and community-based organizations also have
responsibilities in assessing racial profiling issues. Specifically,
they have the responsibility of obtaining "expert" knowledge and
understanding about racial profiling, bias-based policing, and data
collection and analysis before launching discrimination allegations.
It is a disservice to the community for reputable organizations,
whether civil-rights or community-based, to accuse law enforcement
of racism and/or discrimination based on statistical disparities or the
implementation of non-bias traffic enforcement programs.
Although the police have the responsibility to work with the
community, the community shares the same responsibility to work
with law enforcement. This partnership provides mutual respect
and a better understanding of community perceptions and a better
understanding of the complexities of policing in a democratic society.
Cooperating with the police does not dilute community activism or
citizen oversight. To the contrary, it empowers communities to hold
law enforcement accountable. Communities should speak out against
racism, discrimination, and biases, but should also speak up in support
of law enforcement when they "get it right." Otherwise, the voice of

the community becomes nothing more than the voice of the critic.
Dissent is necessary to hold government accountable, but it must be
balanced with support.
7.3 Recommendations: How to Eliminate Biased Policing
(This section summarizes Captain Davis' points on the blindfolds of justice:
a more complete version and formal citation of the original article can be
found in Appendix E.)
"Justice is blind" represents the basic motto and principle of our
criminal justice system. It symbolizes equity in the administration of
justice and represents our basic rights in a free society. Many in the
minority community, however, feel that society is not free and justice
is not blind. In fact, the perception is that "justice" in many cases
distinguishes on the basis of race, ethnicity, gender, religious beliefs,
and social and economic status.
Justice is, among other things, a system of people influenced by the
biases and stereotypes brought to and learned at the job. In many
cases, biases and stereotypes may be unintentional and applied
subconsciously. In some cases, however, biases and stereotypes are
intentional and malicious, rising to the level of blatant discrimination.
However, whether intentional or unintentional, the application of bias
in policing tilts the scales of justice and results in unequal treatment
under the law.
Bias-based policing is defined as:
The act (intentional or unintentional) of applying or incorporating
personal, societal, or organizational biases and/or stereotypes as
the basis, or factors considered, in decision-making, police actions,
or the administration of justice.
Bias-based policing impacts all aspects of policing, and many feel
that it should be considered the most serious problem facing law
enforcement today. Racial profiling can be considered a symptom of
bias-based policing.
Administrators often fail to recognize the true problems behind bias-
based policing and respond only to symptoms. Responses are usually
"knee jerk" and largely ineffective. New symptoms will eventually
appear, and still more new responses will be developed. Valuable time
and resources are wasted on creating policies in response to symptoms
instead of eliminating the basic problems through a comprehensive
systematic approach.

The traditional symbol of justice in this country is a woman holding
a scale blindfolded. The symbol does not suggest the woman is free
of bias or that justice is blind. The symbol represents the need to
blindfold those empowered to administer justice from personal and
societal prejudices when exerting the authority and power of office.
Although it is impossible to completely remove bias from people, it
is possible to create systems that "blindfold" people from bias. To
create blindfolds, agencies must analyze formal and informal operating
systems and identify more efficient and equitable practices in each
of the following domains: mission statement, recruiting and hiring,
training, assignment rotation, promotion, discipline/accountability,
community relations, and leadership. These themes for the eight
blindfolds of justice are developed more fully in Appendix E.
In conclusion, the elimination of bias-based policing requires a
comprehensive program that establishes effective systems in all aspects
of policing. The eight blindfolds detailed in Appendix E are important
recommendations to help eliminate biased policing. These systems
must be driven by principle-based leaders with the courage to make
change and demand the best quality of service for our communities.
7.4 Advice for Departments Accused of Racial Profiling
(This material was provided by Captain Davis based on a report he prepared
for NOBLE, Racial Profiling: "What Does the Data Mean?" The report is a
practitioner's guide to understanding data collection and analysis.)
Suppose the headlines in the newspapers read, "Blacks stopped and
cited more than Whites." Community members may read this and
initially assume that racial profiling is occurring: This is a natural
reaction. However, it is important to look beyond the initial reactions
and consider the overall picture. There may be alternative explanations
that should be explored. Special programs, such as seatbelt
enforcement, may be conducted in minority neighborhoods based on
need, community concern and even at the communities' request. The
point is not to immediately assume racial profiling is occurring. Police
departments should also avoid an immediate defensive posture.
Police representatives should work with their community to identify
why these disparities exist. Are they police or societal-based? What
is your response to either potential outcome? If an agency plans to
implement a program that may result in cultural or societal-based
disparities, it would be beneficial to explain the program, its goals and
expected outcomes before implementation, rather than after the fact.

There are many other combinations of factors, variables, and
percentages that provide valuable insight into operational effectiveness
and disparate outcomes. Below are a few variables to consider when
establishing baselines and benchmarks and analyzing data:
 1990 versus 2000 Census
 Driving age population
 Day-time population
 Major thoroughfares
 Violator population
 Area/precinct demographics
 Race-geographic lines
 Population density
 Staff deployment
 Special projects/assignments
 Probation & parole
 Repeat offenders.
In analyzing and applying data, it is crucial to work closely with all
stakeholders during data-collection development, implementation, and
analysis. Ten key points are:
 Do not fear data collection and analysis.
 Data is information, information is knowledge, and knowledge is
power.
 Stop data is not perfectbut it is better than no data.
 Effective baseline comparison data and benchmarks can be
established.
 The key to data analysis is interpretation: What does the data
mean to you, the organization and the community?
 Involve all stakeholders in all aspects of data collection and
analysis.
 Data collection alone will not answer the question: Does racial
profiling exist?
 Data collection is not the solution to racial profiling; it is,
however, a critical tool in developing solutions and measuring
managerial effectiveness.
 Data collection can identify bias in operational systems and
functional programs and reduce disparate treatment and racial
tension.
 False and inaccurate allegations of racial profiling and
discrimination based on inaccurate analysis is as, if not more,
harmful than racial profiling.

7.5 Why Some Chiefs Decline to Collect Data
(This material is based on Captain Davis' conversations with many police
chiefs, including some conducted in early December 2001 at the DOJ CEO
symposium.)
According to a survey conducted by the Police Executive Research
Forum (PERF), over 60 percent of the police chiefs surveyed did not
believe racial profiling occurred in their jurisdiction; compared to 60
percent of Americans surveyed by the Washington Post who believe it
does exists. Although most people agree that racial profiling is wrong,
they may not agree on what it is or to what extent it exists. This
debate has resulted in confusion and a general misunderstanding of
racial profiling and bias-based policing.
It is impossible to solve a problem without being able to define and
identify it. Similarly, it is impossible to recognize the value of data
collection and analysis, unless there is a clear understanding of what it
is, what it is not, and what it can do. This confusion has caused many
police chiefs to be apprehensive and skeptical of data collection and
analysis. Police chiefs who have declined to collect data have done so,
for the most part, for one or more of the reasons discussed below.
Defining Racial Profiling
How racial profiling is defined will affect a determination of whether,
and to what extent, it exists. Without a clear definition and examples
to place in a practical context, many police chiefs do not understand
racial profiling and continue to believe it does not occur in their
agency. Consequently, they are less likely to spend resources to address
a problem that, in their opinion, does not exist.
Standardized Data Collection and Analysis Models
Most people, including police chiefs, do not understand data collection
and analysis and do not recognize its value; or more importantly, its
true purpose. Many police administrators are concerned that there
are no credible, standardized data analysis models. This may lead to
data collected being misinterpreted, providing misinformation to
the community that will discredit the agency and individual officers.
Many police chiefs are also concerned that data can be skewed and
manipulated to support false perceptions and result in frivolous
lawsuits against agencies and officers.

Credible Baseline Comparison Data and Benchmarks
Many police chiefs are concerned that there are no credible data
analysis benchmarks or baseline comparison data. Most chiefs
recognize that aggregate census demographics do not provide a
credible benchmark and relay serious concerns on the tendency of the
media and the community to base racial profiling simply on statistical
disparities between traffic stops and citywide census demographics.
In addition, there is concern that current data collection efforts
do not consider the complexities of policing, such as crime-rates,
calls for services, staffing and deploymentto name just a few. In
short, many chiefs decline to collect data based on their lack of
trust in establishing effective and credible benchmarks and baseline
comparison data.
Media and Press
Police chiefs are also concerned that the media's inability to
understand data collection and analysis results in negative headlines
that contribute to negative perceptions in the community. In most
recent cases, agencies have been accused of racial profiling simply
based on simplified aggregate statistical disparities. As cited earlier, this
can be demonstrated by the case of the Chief Lansdowne and the San
Jose Police Department, one of the first law enforcement agencies to
voluntarily collect traffic stop data.
Chief Lansdowne released his first data-collection report, which
showed a disparity (less than ten percentage points), between traffic
stops of Hispanics compared to the percentage of Hispanics residing
in the city. The department came under immediate criticism from a
few civil-rights and community-based organizations because the stop
statistics did not exactly match the citywide demographics. This type
of comparisonvehicle stop data against citywide census databecame
accepted as the national trend, and the 1990 Census became the sole
benchmark for many people and organizations. Racial profiling and
discrimination accusations were launched against police agencies
based on this comparison. Consequently, many police chiefs are
apprehensive about data collection because they fear that they too will
be accused of racial profiling and racism simply based on aggregate
statistical disparities.

Cost-Effectiveness
Many chiefs recognize that statistical data may prove disparities, and
some even believe it may prove racial profiling exists, but most do not
know how the data can be used to help find ways to eliminate these
disparities or racial profiling. Therefore, it is not considered to be
cost-effective to collect and analyze data that will simply verify what is
already "known", unless the data can help to end the practice. These
chiefs believe law enforcement should simply acknowledge that racial
profiling exists and use their scarce resources to solve the problem,
not identify the problem. Many of these police chiefs would be willing
to collect data if sufficient supplemental funding were allocated. In the
absence of such funding, resources (both financial and manpower) are
limited, and chiefs may prefer to focus resources directly on solutions.
In conclusion, most police chiefs recognize that data collection and
analysis is not a panacea or even the sole answer to racial profiling and
bias-based policing, and also recognize its practical and symbolic value.
NOBLE, the International Association of Chiefs of Police (IACP),
the Police Executive Research Forum (PERF), the National Black
Police Association, the Hispanic American Command Police Officers
Association (HAPCOA), and the Alliance of National Minority Law
Enforcement Agencies (ANMLEA) have all denounced racial profiling
and stated there is value in data collection. Each organization also
agrees that improper data collection and analysis is extremely harmful
to the community and law enforcement profession.
7.6 Overall Recommendations
There are many considerations in establishing the right benchmarks
for data collection purposes. Law enforcement officials must have a
better understanding of data collection and analysis to truly recognize
its value. It is strongly recommended that agencies consult with
professional researchers for both accuracy and validity. Improper
data collection and inaccurate analysis can be as harmful to police-
community relations as racial profiling itself. The process of data
collection should prove extremely beneficial and the data should
provide administrators the necessary information to police effectively,
efficiently and most importantlyethically.
This section provides a practitioner's perspective and a few basic,
nonscientific principles and examples of how data collection can identify
organizational bias, improve managerial effectiveness, and improve
community relations. The examples provided are not intended to
provide a complete guide on data collection and analysis; they do
provide a basic look at variables that impact benchmarking and data
analysis. There are ten practical recommendations to effective data
collection and analysis:

1. Form a local advisory group or task force comprised of all
stakeholders, including police, community, civil rights, union or
police associations, professional researchers and/or academia.
2. Provide training to the advisory group to obtain expert knowledge
and understanding of racial profiling, bias-based policing and the
complexities of data collection and analysis. Do not assume task
force members understand the issues.
3. Utilize the task force to define racial profiling and bias-based
policing in a policy that is in accordance with applicable local
ordinance or state law and CALEA standards.
4. Determine the goal(s) and desired outcomes of data collection
before designing the system. Decide what you want to find out.
Engage the community during this process through marketing
strategies or Town Hall meetings.
5. Identify all locally relevant variables that may skew aggregate
data and all relevant variables that are necessary in establishing
appropriate benchmarks. This process must be completed prior to
identifying what data should be collected.
6. Identify baseline comparison data and establish benchmarks.
7. Identify what data should be collected. Bear in mind that
professional research has been conducted in this area, and can
provide a starting point. However, it is necessary to identify locally
relevant variables as they vary between agencies and jurisdictions.
8. Identify "best practices" and develop a data collection
methodology that fits the organization, the community, and the
budget.
9. Train officers and the community on racial profiling and bias-
based policing; the new policy, the agencies' data collection
programits purposes and expected outcome (not in statistical
terms, but regarding values), and their roles to help ensure success.
10. Collect and analyze the data, and report findings and
recommendations.
These steps are not all-inclusive, but they do provide practical
operational guidance to establishing effective data collection and
analysis programs.

8.0 DISCUSSION AND CONCLUSIONS
Many early efforts to investigate racial profiling, while well intentioned,
have used very simple analytical approaches to investigate complex
issues. As a consequence, in a number of cases the media and public
have leaped to a hasty conclusion that the data collected definitely
show a pattern of racial profiling, and demanded that the police fix
this problem. As a result, many police administrators are apprehensive
about data collection because they fear that they too will be accused
of racial profiling and racism based on simple statistical disparities
observed from preliminary superficial comparisons.
It is crucial that data be collected objectively and evaluated using
careful and thorough analytical methods. Data that is assessed
using simple metrics may "appear" to show racial profiling, and be
misunderstood and/or incorrectly used by special interest groups. This
may potentially lead to inappropriate demands to rectify a situation
that may not even exist. On the other hand, a carefully crafted and
executed data analysis plan can generate valid information for police
departments, which can be used to evaluate not only racial profiling,
but general management and efficiency issues as well.
Criminal justice experts and the operational experts reach the
same basic conclusion although via different approaches. From the
"academic" point of view, discussed in Chapter 4, the message is that
simplistic evaluations that link a single variable (influence) to racial
disparities will almost certainly fail to reach the correct conclusions.
In this context, bivariate analysis is inherently flawed in that it fails
to consider the complexities of policing activities and the multiple
influences that affect the decisions by police officers to stop, and
search, individuals. Multivariate analysis, essentially a multiple
regression approach, can account for the simultaneous influence of
many different factors, and will yield a more accurate representation
of police activities.
The operational point of view, exemplified in Chapter 7 from the
NOBLE subject matter operational experts, echoes these opinions
in less academic terms. They point out that simply looking at stop
data stratified by race, compared to city-wide census demographics,
fosters both inaccurate and counterproductive conclusions. In the
operational terminology, what is required is a stepwise approach to
investigating the issues. First, examine the stop data compared to
appropriate and reasonable baseline comparison data. Second, evaluate
the initial findings compared to what other factors are known to be
relevantspecific local variables or circumstances. Third, investigate

additional strata of information, such as search disparities, parole and
probation stops and searches, special programs, and descriptive stops,
to determine if there are additional influences at play.
It is important to determine what the term racial profiling means.
Conference participants felt that the Department of Justice should
focus on facilitating discussions among interested parties to move
towards a widely accepted definition of racial profiling. This definition
would provide standards to measure against, and should include clear
guidelines for officers as to how they are supposed to do business.
This will also enable researchers to establish agreement as to what
evidence they are looking for in terms of identifying racial profiling
behavior. Society needs a clear definition that can be used as a starting
point for further comparisons. In addition, it is important to everyone,
from community members to police chiefs to politicians, that the
evidence is evaluated in a fair and thorough manner. Only then will
society have accurate information to use in considering policy changes
and recommendations for future actions.
8.1 Data Collection: Costs and Benefits
Many of the city police departments have raised the cost of data
collection and evaluation as an issue. If data collection is to be done
correctly, attention must be given to discussing the questions at issue
and setting up an analysis plan to address the appropriate concerns
and local issues. Data should then be collected, recorded, and
analyzed. At the end, a report will be issued, and briefings should be
arranged with political leaders, city representatives, community groups,
and members of the media. All of these steps require considerable
input of resources, time, money, and expertise from various
individuals.
If data collection is mandated by an outside agency, then it is
appropriate to consider whether the agency offers funding or other
support to assist in the effort. Otherwise, the requirement may be
viewed as an unfunded mandate. However, requirements are not
always accompanied by funding. In addition, there are costs that
departments will face in terms of lost resources. In other words, the
time personnel spend on designing a data collection system, collecting
the data, processing and recording data and then analyzing it, will be
time that could have been spent on other endeavors. In particular,
police officers may resent taking time from their primary duties for
this purpose.

Calculating the benefits from engaging in data collection and analysis
is a very difficult matter. In many respects, only potential benefits can
be cited. Individual departments will have to determine how far they
are willing to go in using the data collected and for what purposes
they are willing to use the data. The first, and most obvious use of the
data, is to address the issues involved in racial profiling accusations.
While it is indisputable that some instances of racial profiling
occur, isolated incidents are not of as much concern as systematic
racial profiling practices. Isolated incidents will most likely never be
eliminated. If, however, racial profiling (however defined) proves to be
a systemic problem, then it will require further attention.
An additional benefit from data collection is that it focuses attention
on the issue, and may result in making members of the community
feel that their concerns are at least being addressed in a substantive
fashion. If police departments begin to engage their communities and
interact with community groups and leaders, as part of the attempt to
defuse racial profiling accusations, there may be positive benefits from
this as well. The results from analysis of data collected will offer much
new information about police practices and patterns, which will allow
for valuable discussion and consideration of the appropriate roles for
police and community members. And finally, the data collected can
show police managers a great deal of information about the efficiency
and productivity of the staffing patterns and practices currently
employed.
8.2 Technical Expertise Issues for Local Departments
Many departments do not have discretionary resources to allocate to
data collection and analysis. In particular, large departments in major
urban areas may be best situated with respect to having computer
resources and manpower that can address data collection and analysis
issues. For mid-sized departments, it may be difficult to find funding
to support data collection and analysis, and institute proper recording
procedures. For small departments, such an effort will be very
difficult. If data collection is externally mandated, it is important to
realize that the scope and extent of data collection and analysis that
can be undertaken will be limited by available funding. Agencies will
have to prioritize their overall operational needs and fund competing
efforts accordingly. Small and mid-size departments especially may
need guidance and additional funding to facilitate thorough data
collection and evaluation programs.
Computer capabilities are also important issues. However, the needs
of hardware and software depend critically on the size of the database
being collected, and the scope of the analysis under consideration.
Stand-alone systems may provide superior processing with respect to

speed as well as specialized software not generally available on police
computer networks. Most departmental requirements for data analysis
can be met by a reasonably sophisticated Pentium PC, and do not
require a major financial investment for hardware and/or software.
On the other hand, internal processing and evaluation of data may
necessitate specialized training of personnel (or recruiting specialized
personnel), which could be both costly and time-consuming.
8.3 Leveraging Resources Via Outside Partnerships (e.g.,
Academic)
It is important for police departments to explore establishing linkages
with the professional research community. By partnering with social
science researchers, it is possible to gain access to outside analytical
expertise. One way to start is by identifying and approaching local
analytical organizations to establish a mutually beneficial partnership.
If local resources are not available, state or national professional
research groups may be contacted. The word partnership is an
important key to the recommended relationship: an ongoing shared
dialogue should characterize the association. The police department
and professional analysts should work together, not as separate
entities.
One possibility is to establish partnerships with faculty or graduate
students at local academic institutions. It is strongly recommended,
however, that police agencies do not outsource the analytical part of
the partnership completely to professional research staff. It is through
a combination of different expertise that the operational knowledge
of the police force and the analytical skills of social scientists can
best be blended. Combining social science research techniques with
specific police knowledge of operational procedures and local issues,
circumstances, and programs should generally yield the most accurate
and thorough evaluations.
Conference participants recommended that the Department
of Justice provide guidelines to police departments on how to
establish partnerships with university researchers. In addition, they
recommended guidance on the appropriate roles for academic
or public research groups to play. Finally, they also suggested the
establishment of clear guidelines on how information on racial
profiling should be usedwho will own it, who will be responsible for
using it, how confidentiality can be maintained, and how frequently
reports should be generated and released.

8.4 Value of Objective Information Versus Anecdotal
Information
Ultimately, the issues of data collection and analysis revolve around
the crucial interests of truth and justice. Racial profiling accusations
have become a common accusation around the country, and
community perceptions support the concept that racial profiling is a
pervasive problem that must be eliminated. However, in many cases,
these perceptions are based on bodies of anecdotal evidence. This
does not state that anecdotes or stories are incorrect or slanted. It is
well established, however, that people are more impelled to complain
if they are unhappy than they are compelled to praise if they are
contented. Therefore, it should be expected that reports of incidents
would be more likely to cite negative experiences with the police than
positive experiences.
Making policy decisions regarding racial profiling issues is a very
important matter. That said, it is also true that policy decisions and
operational initiatives should be based on factual evaluations rather
than opinions and anecdotal evidence. Policy changes and operational
initiatives should be driven by balanced and objective evaluations of
circumstances. While anecdotal evidence may (or may not) indicate
that, in certain cases, racial profiling has occurred, this should not be
considered sufficient to establish that there is a systematic underlying
bias supporting and reinforcing the use of biased policing. There
are undoubtedly incidents that occur, and judgments that are made,
that derive from bias and prejudice. However, these may be isolated
incidentsnot necessarily based on pervasive and systematic policies.
It is critical to be able to distinguish between isolated incidents,
individually biased officers, individual instances of inappropriate
police behavior, and the statistical implications of societal disparities
versus a pattern of sustained and systematic biased policing. Policies
are needed to address racial profiling issues, but the policies will
be ineffective, and potentially counterproductive, if they are driven
by, and based on, incorrect assumptions about the underlying
relationships between police agencies and the communities they serve.
8.5 Importance of Communication and Community
Interactions
Conference participants and subject matter experts agreed that it
is critical to establish regular lines of communication with many
different community groups. In particular, minority community
leaders, community groups, media representatives, and local political
leaders need to be involved in regular meetings. It is not conducive
to smooth relationships to wait until some crisis occurs, and then

set up meetings. It is far better for police agencies to foster ongoing
relationships with all interested parties.
In particular, for data collection and evaluation efforts, it is important
for community groups to be aware of the activities being planned,
and if possible to assist in the planning process. Subject matter
experts identify the need for a "task force" approach to planning and
executing data collection and analysis to investigate racial profiling
issues. Conference representatives, in turn, agreed that cities and
police departments should be given specific guidance on how to put
together an appropriate task force and make it work. In addition, they
agreed that there should also be guidelines provided on how police
departments should go about educating the community, and guidance
on the appropriate ways to release and present data to the community.
8.6 Recommendations for Further Study
Although many specific recommendations have been offered, actual
implementation will require that city-specific input and circumstances
be considered. In addition, there are a number of areas where it seems
clear that more information should be gathered in order to fully
implement the recommendations.
It is appropriate to fill in the details of the picture by focusing
on citizen surveys. In particular, by looking only at citizens who
are stopped by the police, we are observing a partial slice of the
community. It is important to understand what the community thinks
about police department policies, behavior, practices, and goals. By
listening only to media representation of community beliefs and
preferences, an unrepresentative view of true community values and
desired police behavior may be formed.
In addition, it is time to conduct a complete data collection and
evaluation program in a selected city, using the tools and methods
recommended in this paper. This should be an approach that relies on
a blending of research methods with operational police insights. The
evaluation should consider the joint impact of locally relevant issues
and demographic considerations, police assignments, and enforcement
issues. This effort should seek the guidance of operational subject
matter experts to focus the effort. Also, research and operational
experts should meet early on to discuss what questions they want to
answer, and how best to craft a plan to collect data that will be able to
answer those questions.

Lastly, it is important that the interested parties understand that
finding answers for one city, or one jurisdiction, does not mean that
these answers will apply everywhere. It is entirely likely that different
cities will reach different conclusions with respect to the issues and
concerns raised regarding racial profiling. In this context, it is very
important that all interested parties become educated on the relevant
issues, various methods of evaluation, and how to react to findings. It
is difficult enough to reach definitive conclusions about racial profiling
issues. However, it is also important to think ahead to what kind of
policy implications should follow, depending on the answers found.

Appendix A
Tables for Chapter 4
Table 4.1: Behavior Sampled and Agency Characteristics in Racial Profiling Reports
Jurisdiction/Author
Type of Police Behavior Sampled
Agencies Studied:
Number
Geographical Scope
Type
Baltimore Police Department
All Stops
1
Citywide
City Police
California Highway Patrol
Traffic Contacts
1
Statewide
State Police
Chattanooga Police Department
Traffic Citations/ Field Interviews
1
Citywide
City Police
Connecticut: Chief State's Attorney
Traffic Stops
92
Statewide
State & Local Police
Florida Highway Patrol
Traffic Stops
1
Statewide
State Police
Lansing: Carter, et al.
Traffic Stops
1
Citywide
City Police
Maryland/I-95 Corridor: Lamberth
Traffic Searches
1
Part of 1 Road
State Police
Maryland/Not I-95 Corridor: Lamberth
Traffic Searches
1
Statewide (minus 1 Road)
State Police
Maryland (I-95): Knowles and Persico
Traffic Searches
1
Part of 1 Road
State Police
Michigan State Police
Traffic Stops
1
Statewide
State Police
Missouri Attorney General
Traffic Stops
634
Statewide
State and Local Police & Sheriffs
New Jersey State Police: Lamberth
Traffic Stops
1
Part of Turnpike
State Police
New Jersey State Police: Venerio & Zoubek
Traffic Stops
1
Part of Turnpike
State Police
New York City: Spitzer
Pedestrian Stops
1
Citywide
City Police
North Carolina: Zingraff, et al.
Traffic Stops
1
Statewide
State Police
Oakland Police Department
Traffic Stops
1
Citywide
City Police
Richmond: Smith and Petrocelli
Traffic Stops
1
Citywide
City Police
Sacramento Police Department
Traffic Stops
1
Citywide
City Police
San Diego Police Department, 2001
Traffic Stops
1
Citywide
City Police
San Jose Police Department, 2000
Traffic Stops
1
Citywide
City Police
St. Paul: Inst. on Race and Poverty
Traffic Stops
1
Citywide
City Police
Texas Department of Public Safety
Traffic Stops
1
Statewide
State Police
United States
Police Public Contacts
All
Nationwide
Any Agency
Washington State Police
Traffic Stops
1
Statewide
State Police

Table 4.2: Police Activities Measured in Racial Profiling Reports
Jurisdiction/Author
Police Behavior:
Contact
Stop
Search
Contraband
Arrest
Force
Baltimore Police Department
X
X
X
X
California Highway Patrol
X
X
X
Chattanooga Police Department
X
Connecticut: Chief State's Attorney
X
Florida Highway Patrol
X
Lansing: Carter, et al.
X
X
Maryland/I-95 Corridor: Lamberth
X
Maryland/Not I-95 Corridor: Lamberth
X
Maryland (I-95): Knowles and Persico
X
X
Michigan State Police
X
Missouri Attorney General
X
X
New Jersey State Police: Lamberth
X
New Jersey State Police: Venerio & Zoubek
X
X
X
New York City: Spitzer
X
X
North Carolina: Zingraff, et al. 2000
X
X
Oakland Police Department
X
X
X
Richmond: Smith and Petrocelli
X
X
X
Sacramento Police Department
X
X
X
San Diego Police Department, 2001
X
X
X
San Jose Police Department, 2000
X
X
St. Paul: Inst. on Race and Poverty
X
X
Texas Department of Public Safety
X
X
United States
X
X
X
X
X
X
Washington State Police
X
X
X
X

Table 4.3: Characteristics of Suspects and Encounters in Racial Profiling Data Analyses
Jurisdiction/Author
Suspect Characteristics: Race
Sex
Age
Residence
License
Police Behavior: District
Hour
Month
Baltimore Police Department
X
X
X
X
California Highway Patrol
X
X
X
Chattanooga Police Department
X
X
X
Connecticut: Chief State's Attorney
X
Florida Highway Patrol
X
X
X
X
Lansing: Carter, et al.
X
Maryland/I-95 Corridor: Lamberth
X
Maryland/Not I-95 Corridor: Lamberth
X
Maryland (I-95): Knowles and Persico
X
X
X
Michigan State Police
X
X
Missouri Attorney General
X
New Jersey State Police: Lamberth
X
X
X
New Jersey State Police: Venerio & Zoubek
X
New York City: Spitzer
X
X
North Carolina: Zingraff, et al. 2000
X
X
X
X
X
Oakland Police Department
X
X
X
X
Richmond: Smith and Petrocelli
X
X
X
X
Sacramento Police Department
X
X
X
X
X
San Diego Police Department, 2001
X
X
X
X
X
San Jose Police Department, 2000
X
X
X
St. Paul: Inst. on Race and Poverty
X
X
X
Texas Department of Public Safety
X
United States
X
X
X
Washington State Police
X
X
X
X

Table 4.4: Time Periods and Numbers of Activities Studied in Racial Profiling Reports
Jurisdiction/Author
Primary Author
Time Period: Start
End
Months
Activity: Studied
Number
Baltimore Police Department
PD
01/01/2001
06/30/2001
6 months
All Stops
89,889
California Highway Patrol: Seperate Reports on Contacts and Searches
PD
07/01/1999  10/01/1999
04/30/2000  04/30/2000
10 months  7 months
Traffic Contacts  Traffic Searches
2,638,589  23,584
Chattanooga Police Department
PD
07/01/2001
07/31/2001
1 month Traffic Citations/ Field Interviews
4,239
Connecticut: Chief State's Attorney
R/State
01/01/2000
06/30/2000
6 months
Traffic Stops
316,158
Florida Highway Patrol
PD
01/01/2000
01/01/2001
13 months
Traffic Stops
604,108
Lansing: Carter, et al.
R/PD
02/12/2001
09/12/2001
7 months
Traffic Stops
19,353
Maryland/I-95 Corridor: Lamberth
LT/R
01/01/1995
09/30/1996
21 months
Traffic Searches
823
Maryland/Not I-95 Corridor: Lamberth
LT/R
01/01/1995
09/30/1996
21 months
Traffic Searches
1,549
Maryland (I-95): Knowles and Persico
R
01/01/1995
01/01/1999
49 months
Traffic Searches
1,590
Michigan State Police
PD
01/01/2000
12/31/2000
12 months
Traffic Stops
564,672
Missouri Attorney General
State/R
08/28/2000
12/31/2000
4 months
Traffic Stops
453,189
New Jersey State Police: Lamberth
LT/R
01/01/1989
12/31/1991
25 days
Traffic Stops
2,896
New Jersey State Police: Venerio & Zoubek
State
04/01/1997
11/30/1998
19 months*
Traffic Stops
87,489
New York City: Spitzer
State
01/01/1998
03/31/1999
15 months
Pedestrian Stops
174,919
North Carolina: Zingraff, et al. 2000
R
01/01/1998
12/31/1998
12 months
Traffic Stops
651,556
Oakland Police Department
PD
03/01/2000
05/31/2000
3 months
Traffic Stops
21,338
Richmond: Smith and Petrocelli
R
02/14/2000
03/31/2000
6 weeks
Traffic Stops
2,673
Sacramento Police Department
R
07/01/2000
06/30/2001
12 months
Traffic Stops
36,854
San Diego Police Department, 2001
PD/R
01/01/2000
12/31/2000
12 months
Traffic Stops
168,901
San Jose Police Department, 2000
PD
07/01/1999
06/30/2000
12 months
Traffic Stops
97,154
St. Paul: Inst. on Race and Poverty
R
04/15/2000
12/15/2000
8 months
Traffic Stops
41,249
Texas Department of Public Safety
PD
03/01/2000
07/31/2000
4 months
Traffic Stops
779,961
United States
FED
07/01/1998
12/31/1999
12 months
Any Contact
80,543
Washington State Police
PD/Other
05/01/2000
10/31/2000
6 months
Traffic Stops
338,885

Table 4.5: Reported Findings about Traffic Stops in Racial Profiling Reports
Jurisdiction/Author
Summary
Text
Baltimore Police Department
None
California Highway Patrol:
NO
The results show that CHP officers do not employ race/ethnicity as
a basis for enforcement stops (p. v)
Chattanooga Police Department
None
Connecticut: Chief State's Attorney
NO
Minority drivers do not appear to be treated differently than non-minority (p. ii).
Florida Highway Patrol
NO
The race, ethnicity and gender of the drivers stopped is basically
the same as the population at the state and county level (p. 1).
Lansing: Carter, et al.
NO
That is, given the previous caveats, these data do no point to any
serious problem and suggests that the variations (differences) are
with accepted statistical parameters as being normal (p.10).
Maryland/I-95 Corridor: Lamberth
Not Addressed
Maryland/Not I-95 Corridor: Lamberth
Not Addressed
Maryland (I-95): Knowles and Persico
Not Addressed
Michigan State Police
None
Missouri Attorney General
Maybe
The data have done nothing to disprove the perception of racial profiling (p. 7).
New Jersey State Police: Lamberth
Yes
While no one can know the motivations of each individual trooper
in making a stop, the statistics presented herein, representing a very
broad and detailed sample of highly appropriate data, demonstrate
without question a discriminatory impact on blacks and out of state
blacks in particular (p. 29).
New Jersey State Police: Venerio & Zoubek
Cannot Say
There is no way to interpret the significance of this data (p. 34).
New York City: Spitzer
YES
In sum, even when population rates and crime rates are controlled
for, minorities were "stopped" at a higher rate in New York City
than Whites (p. 135)
North Carolina: Zingraff, et al. 2000
MIXED
African-Americans were generally found to be over-represented in
the outcomes examined, with the exception that young African-
Americans were under-represented in in citations (both males and
females) and African American females are no more likely than
white females to be searched.
Oakland Police Department
NO
Based on the total vehicle stop and Area-based comparisons,
no evidence from this phase of data collection suggests racially
disproportionate vehicle stops (p. 7, 5/22/2001 letter report).
Richmond: Smith and Petrocelli
YES
One conclusion to be drawn from the present analysis is that is that
minorities are being disproportionately targeted for traffic stops by
the Richmond Police (article, p. 21).
Sacramento Police Department
NO
Several observations suggest that the Sacramento Police
Department does not differentially stop, detain, or search members
of any racial group for reasons other than police work of a kind
consistent with community needs and requests (p. 4).
San Diego Police Department, 2001
Cannot Say
While the analysis demonstrates that Hispanic and Black/African-
American drivers are over represented in vehicle stops in San
Diego in comparison to the driving age population, and also over
represented in the subsequent vehicle searches, it does not explain
why (p.vi).
San Jose Police Department, 2000
NO
The Department believes that the in-depth analysis of the data
indicates there is not a racial profiling problem in the city of San
Jose (p. 8).
St. Paul: Inst. on Race and Poverty
YES
African-American drivers were stopped in disproportionately high
numbers compared to their proportion of the city's population.
This pattern occurred throughout the city, in 80 of 82 census tracts
(p. 4).

Table 4.5 (contd)
Jurisdicton/Author (contd)
Summary (contd)
Text (contd)
Texas Department of Public Safety
NO
These statistics closely relate to the estimated population of Texas
(p. 1).
United States
Cannot Say
These racial differences are not necessarily evidence that police use
race as a factor in deciding whether to make a traffic stop (p. 13).
Washington State Police NO An analysis of the current data shows that the Washington Sate
Patrol is not engaged in any statewide practice or pattern of
initiating traffic stops based on the race of the drivers (p. 1).

Table 4.6: Reported Findings about Traffic Searches in Racial Profiling Reports
Jurisdiction/Author
Summary
Text
Baltimore Police Department
No statement
California Highway Patrol:
Not Addressed
Chattanooga Police Department
Not Addressed
Connecticut: Chief State's Attorney
No
Minority drivers do not appear to be treated differently than non-
minority (p. ii).
Florida Highway Patrol
Not Addressed
Lansing: Carter, et al.
No
This significant majority of cases wherein searches of drivers are
non-discretionary searches clearly indicates officer behavior tends
to be based on law and departmental procedure, not an extraneous
reason, such as "profiling" (p. 12).
Maryland/I - 95 Corridor: Lamberth
Yes
The evidence examined in this study reveals dramatic and highly
statistically significant disparities between the percentages of black
Interstate motorists detained and searched by MSP troopers on this
roadway (p. 6).
Maryland/Not I-95 Corridor: Lamberth
None
Maryland (I-95): Knowles and Persico
MIXED
Our findings suggest that police search behavior is not biased
against African-Americans drivers. The lower guilty rate for
Hispanics are suggestive of prejudice against this group (p. 222).
Michigan State Police
No statement
Missouri Attorney General
Maybe
The data have done nothing to disprove the perception of racial
profiling (p. 7).
New Jersey State Police: Lamberth
Not Addressed
New Jersey State Police: Venerio & Zoubek
Yes
The data presented to us show that minority motorists were
disproprotionately subject to consent searches (p. 30).
New York City: Spitzer
Not Addressed
North Carolina: Zingraff, et al. 2000
MIXED
African-Americans were generally found to be over-represented in
the outcomes examined, with the exception that young African-
Americans were under-represented in in citations (both males and
females) and African-American females are no more likely than
white females to searched.
Oakland Police Department
Cannot Say
The group concluded that a comprehensive analysis could not be
formed (p. 9).
Richmond: Smith and Petrocelli
No
Thus, minorities were no more likely than whites to be searched.
(p. 14 of report).
Sacramento Police Department
No
Several observations suggest that the Sacramento Police
Department does not differentially stop, detain or search members
of any racial group for reasons other than police work of a kind
consistent with community needs and requests. (p. 4).
San Diego Police Department, 2001
Cannot Say
While the analysis demonstrates that Hispanic and Black/African-
American drivers are overrepresentated in vehicle stops in San
Diego in comarison to the driving age population, and also
overrepresentated in the subsequent vehicle searches, it does not
explain why (p. vi).
San Jose Police Department, 2000
Not Addressed
St. Paul: Inst. on Race and Poverty
Yes
After being stopped, African -American, Hispanic and Native
American drivers are subject to both pat down searches of their
person and searches of their vehicles at rates higher than the search
rates for whites and Asian drivers (p. 4).
Texas Department of Public Safety
No statement

Table 4.6 (contd)
Jurisdiction/Author (contd)
Summary (contd)
Text (contd)
United States
Cannot Say
However, while the survey data can reveal these various racial
disparities, they cannot answer the question of whether the driver's
race, rather than the driver's conduct at the time or any other
specific circumstance surrounding the stop, is the reason the search
was conducted.
Washington State Police
Yes
Even so, differences were found for white persons and non-white
persons regarding enforcement action and related searches that
require more thorough analyses to account for the differences (pp.
1-2).

Table 4.7: Annual and Per Capita Rates of Police Stops
Jurisdiction/Author
Police Behavior Analyzed: Type
Number
Data Collection Months
Estimated Number per Year
Estimated Number per Day
2000 Resident Population
Stops per 100 Residents
Baltimore Police Department
All Stops
89,889
6
179,778
492
651,154
27.6
Stops of
Residents
79,100
6
158,200
433
651,154
24.3
California Highway Patrol
Traffic Contacts
2,638,589
10
3,166,307
8,669
33,871,648
9.3
Chattanooga Police Department
Traffic Citations
2,896
1
34,752
95
155,554
22.3
Field Interviews
1,343
1
16,116
44
155,554
10.4
Connecticut: Chief State's Attorney
Traffic Stops
316,158
6
632,316
1,731
3,405,565
18.6
Florida Highway Patrol
Traffic Stops
604,108
13
557,638
1,527
15,982,378
3.5
Lansing: Carter, et al.
Traffic Stops
19,353
7
33,177
91
119,128
27.8
Maryland/I-95 Corridor: Lamberth
No data N.A.
Maryland/Not I-95 Corridor: Lamberth
No data N.A.
Maryland (I-95): Knowles and Persico
No data N.A.
Michigan State Police
Traffic Stops
564,672
12
564,672
1,546
9,938,444
5.7
Missouri Attorney General
Traffic Stops
453,189
4
1,359,567
3,722
5,595,211
24.3
New Jersey State Police: Lamberth
Traffic Stops
2,974
0.8
44,253
121
N.A.
N.A.
New Jersey State Police: Venerio & Zoubek
Traffic Stops
87,489
18
58,326
160
N.A.
N.A.
New York City: Spitzer
Pedestrian Stops
174,919
15
139,935
383
8,008,278
1.7
North Carolina: Zingraff, et al. 2000
Traffic Stops
651,556
12
651,556
1,784
8,049,313
8.1
Oakland Police Department
Traffic Stops
21,338
12
85,352
234
399,484
21.4
Richmond: Smith and Petrocelli
Traffic Stops
2,673
2
21,384
59
197,790
10.8
Sacramento Police Department
Traffic Stops
36,854
12
36,854
101
407,018
9.1
San Diego Police Department, 2001
Traffic Stops
168,901
12
168,901
462
1,223,400
13.8
San Jose Police Department, 2000
Traffic Stops
97,154
12
97,154
266
894,943
10.9
St. Paul: Inst. on Race and Poverty
Traffic Stops
41,249
8
61,874
169
287,151
21.5
Texas Department of Public Safety
Traffic Stops
779,961
4
2,339,883
6,406
20,851,820
11.2
United States
Any Contact
43,827,419
12
43,827,419
119,993
281,421,906
15.6
Traffic Stops
22,731,790
12
22,731,790
62,236
281,421,906
8.1
Pedestrian Stops
1,659,367
12
1,659,367
4,543
281,421,906
0.6
Washington State Police
Traffic Stops
338,885
12
338,885
928
5,894,121
5.7

Table 4.8: Annual and Per Capita Rates of Police Searches
Jurisdiction/Author
Searches Analyzed Number
Data Collection Months
Estimated Number per Year
Estimated Number per Day
2000 Resident Population
Searches per 100 Residents
Searches per 100 Stops
Baltimore Police Department
759
6
1,518
4.2
651,154
0.2
1.0
California Highway Patrol
23,584
7
40,430
110.7
33,871,648
0.1
1.3
Chattangooga Police Department
Data collected but not reported
155,554
N.A.
N.A.
Connecticut: Chief State's Attorney
11,984
6
23,968
65.6
3,405,565
0.7
3.8
Florida Highway Patrol
No data
15,982,378
N.A.
N.A.
Lansing: Carter, et al.
6.7
119,128
2.0
7.3
Maryland/I-95 Corridor: Lamberth
1,418   823
7  21
2,431  470
1.3
N.A.
N.A.
N.A.
Maryland/Not I-95 Corridor: Lamberth
1,549
21
885
2.4
N.A.
N.A.
N.A.
Maryland (I-95): Knowles and Persico
1,590
49
389
1.1
N.A.
N.A.
N.A.
Michigan State Police
27,800
12
76.1
9,938,444
0.3
4.9
Missouri Attorney General
31,906
4
27,800
262.1
5,595,211
1.7
7.0
New Jersey State Police: Lamberth
No data
95,718
N.A.
N.A.
N.A.
New Jersey State Police: Venerio & Zoubek
1,193
18
795
2.2
N.A.
N.A.
1.4
New York City: Spitzer
Data collected but not reported
8,008,278
N.A.
N.A.
North Carolina: Zingraff, et al., 2000
940
12
940
2.6
8,049,313
0.0
0.1
Oakland Police Department
2,229
3
8,916
24.4
399,484
2.2
10.4
Richmond: Smith and Petrocelli
211
2
1,688
4.6
197,790
0.9
7.9
Sacramento Police Department
6,562
12
6,562
18.0
407,018
1.6
17.8
San Diego Police Department, 2001
10,754
12
10,754
29.4
1,223,400
0.9
6.4
San Jose Police Department, 2000 No data
894,943
N.A.
N.A.
St. Paul: Inst. on Race and Poverty
3,540
8
5,310
14.5
287,151
1.8
8.6
Texas Department of Public Safety
26,737
4
80,211
219.6
20,851,820
0.4
3.4
United States
1,272,282
12
1,272,282
3,483.3
281,421,906
0.5
5.6
Washington State Police
7,729
12
7,729
21.2
5,894,121
0.1
2.3

Table 4.9: Comparison Groups Used in Racial Profiling Reports
Jurisdiction/Author
Comparison Groups Used: Resident Population
Driving Age Population
Licensed Drivers
Traffic Accidents
Traffic Violators
Crime Suspects
Arrested Persons
Type of Statistical Analysis
Baltimore Police Department
BV
California Highway Patrol
X
BV
Chattangooga Police Department
X
BV
Connecticut: Chief State's Attorney
X
X
BV
Florida Highway Patrol
X
BV
Lansing: Carter, et al.
X
BV
Maryland/I-95 Corridor: Lamberth
BV
Maryland/Not I-95 Corridor: Lamberth
MV
Maryland (I-95): Knowles and Persico
X
BV
Michigan State Police
X
BV
Missouri Attorney General
X
X
BV
New Jersey State Police: Lamberth
X
BV
New Jersey State Police: Venerio & Zoubek
BV
New York City: Spitzer
X
X
X
MV
North Carolina: Zingraff, et al., 2000
X1
X
BV/TV
Oakland Police Department
X
BV
Richmond: Smith and Petrocelli
X
X
MV
Sacramento Police Department
X
X
BV
San Diego Police Department, 2001
X
BV
San Jose Police Department, 2000
X
BV
St. Paul: Inst. on Race and Poverty
X
X
X2
X (Map)
X (Map)
X (Map)
BV
Texas Department of Public Safety
X
BV
United States
X
X
BV
Washington State Police
X
X
BV

Appendix B
 Image Of Agenda for August 2001 Conference

Image Of Agenda for August 2001 Conference

Appendix C
Image of Agenda for October 2001 Conference

Image of Agenda for October 2001 Conference

Appendix D
Bibliography for CD of References
These citations are separated by category, and are also categorized by whether
the source is available in paper copies, or available via website or other
electronic form.
U.S. Single Site Studies
Paper Baltimore Police Department. Citizen/Police Contact Receipt Analysis Report,
01/01/2001 - 06/30/2001
bjs.Public Contact99.pdf Langan, Patrick, Lawrence A. Greenfeld, Steven K. Smith,
Matthew R. Durose, David J. Levin, A. Contacts between Police and the Public: Findings
from the 1999 National Survey, March 2001, Bureau of Justice Statistics
BJS.Traffic Stop Data.Survey99.PDF  Strom, Kevin and Matthew R. Durose. Traffic Stop
Data Collection Policies for State Police, 1999, Bureau of Justice Statistics, 2000
california.chp.pdf  Department of CA Highway Patrol. Public Contact Demographic Data
Summary: Report to the Governor, July 2000
Paper  Chattanooga Police Department. Courtesy, Professionalism, Respect. Overview of
Racial Profiling Procedures
Conn.traffic.pdf  State of Connecticut Division of Criminal Justice, Office of the
Chief State's Attorney. Interim Report of Traffic Stops Statistics. January 2000
to June 2000
florida.pdf  Florida Highway Patrol. Racial Profiling [web pages on policies and data
analysis at www.fhp.state.fl.us/html/census/profile.html]
Paper  Knowles, John and Nicola Persico. "Racial Bias in Motor Vehicle Searches:
Theory and Evidence," Journal of Political Economy, vol. 109, #1, 2001
lamberth.pdf  Lamberth, John. Report of John Lamberth, American Civil Liberties
Union, 1996
Lansing.6 Month Report.pdf  Carter, David, Andra Katz-Bannister, and Joseph Schafer.
Lansing Police Department MATS Data Six Months Analysis, Lansing Police Department,
October, 2001
lansing.policy.2000.pdf  Carter, D.L. & Katz-Bannister, A.J. Racial Profiling: Issues
and Responses for the Lansing, Michigan Police Department, December 2000
lexington.traffic.pdf  August 2000 Traffic Charges Report, Lexington-Fayette County,
Department of Police, September 2000
michigan.2000.pdf  Michigan Department of State Police. Traffic Enforcement Summary,
Third Quarter Report, July through September 2000.

minn.datacollect.pdf  Minnesota Department of Public Safety. Recommendations on Racial
Profiling Data Collection: Initial Report of the Workgroup, 2000 [See especially,
Appendices: House Research Information Brief, Racial Profiling Studies in Law
Enforcement: Issues & Methodology, 2000.]
missour.2001.pdf  Missouri Attorney General. 2000 Annual Report on Missouri Traffic
Stops, 2000
newjersey.farmer.pdf  Farmer, J.J. Final Report of the State Police Review Team.
Trenton: Attorney General of New Jersey, 1999
NJ.AG.interim.pdf  Verniero, P., and Paul H. Zoubek. Interim Report of the State
Police Review Team Regarding Allegations of Racial Profiling. Trenton: Attorney
General of New Jersey, 1999
NYAG.stop.frisk.pdf  Spitzer, E. The New York City Police Department's 'Stop and Frisk'
Practices. New York: Attorney General of New York, 1999
Paper   Oliver, J.A. and A.R. Zatcoff. "Lessons Learned: Collecting Data on Officer
Traffic Stops," Police Chief, July 2001, pp. 23-24
Paper   San Diego Police Department. Vehicle Stop Study Mid-Year Report. San Diego: San
Diego Police Department, 2000
sandiego.pdf   San Diego Police Department. Vehicle Stop Study Year end Report:
2000. San Diego: San Diego Police Department, May, 2001
Paper    San Jose Police Department. Vehicle Stop Demographic Study: First Report.
San Jose: San Jose Police Department, 1999
Paper   San Jose Police Department. Vehicle Stop Demographic Study: Second Report.
San Jose: San Jose Police Department, 2000
Paper   Smith, Michael and Matthew Petrocelli. "Racial Profiling?: A Multivariate
Analysis of Police Traffic Stop Data," Police Quarterly, March, 2001, 4-27
Paper   Smith, Michael. The Traffic Stop Practices of the Richmond, Virginia Police
Department, Department of Criminal Justice, November, 2000
sacramento.pdf  Greenwald, H.P. Final Report: Police Vehicle Stops in Sacramento, CA.
University of Southern California, 2001

SPPD.traffic.pdf  Institute on Race and Poverty. Report on Traffic Stop Data Collected
by the Saint Paul Police Department. Minneapolis, MN: University of Minnesota Law
School, 2000
texas.2000.pdf  Texas Department of Public Safety. Traffic Stop Report, October 2000
washington.state2000.pdf  Sandberg, A.M. Washington State Patrol Demographic Data
Collection, October 1999 to February 2000, May 2000
washington.state.2001.pdf  Washington State Patrol and Criminal Justice Training
Commission. Report to the Legislature on Routine Traffic Stop Data, January 2001
zingraff.2000.pdf  Zingraff, Matthew T., Marcinda Mason, William Smith, Donald
Tomaskovic-Devey, Patricia Warrent, Harvey L. McMurray, and Robert C. Fenlon.
Evaluating North Carolina State Highway Patrol Data: Citation, Warnings, and Searches
in 1998, report submitted to North Carolina Department of Crime Control and Public
Safety and North Carolina State Highway Patrol, November 2000
General Studies
AG report.Feb2000.pdf  Reno, Janet. Traffic Stops and Data Collection: Analyzing and
Using the Data, A Report of the Proceedings, February, 2000
denver.datasheet.pdf  Denver Police Department Citizen Contact Sheet, 2001-03
Early.warn.pdf  Walker, Samuel, Geoffrey P. Alpert, and Dennis J. Kenney. Early
Warning Systems: Responding to the Problem Police Officer, Washington, D.C.: National
Institute of Justice
gao.2000.pdf  U.S. General Accounting Office. Report to the Honorable James E. Clyburn,
Chairman Congressional Black Caucus. Racial Profiling: Limited Data Available on
Motorist Stops. GAO/GGD-00-41, March 2000
harris.dwb.pdf  Harris, David A. Driving While Black: Racial Profiling on our Nation's
Highways, American Civil Liberties Union, 1999
iacp.rafficstopssummnet2.pdf IACP. IACP Police Trafffic Stops II, Alexandria, Va:
IACP, March 2001
minn.raceprofiling.issues.pdf  Cleary, J. Racial Profiling Studies in Law Enforcement:
Issues and Methodology. Minnesota House of Representatives, Research Department. June 2000
Noble.perspective.pdf  Davis, Ronald L., Ida Gillis, Maurice Foster. A NOBLE Perspective:
Racial Profiling A Symptom of Bias-Based Policing (Next StepsCreating Blindfolds of
Justice), National Organization of Black Law Enforcement Executives, May 3, 2001

PERF.Racial Biased Policing.pdf  Fridell, Lori, Robert Lunney, Drew Diamond, and Bruce
Kubu. Racial Biased Policing: A Principled Response, Police Executive Research Forum,
Washington, D.C., 2001
Ramizrez.pdf  Ramirez, Deborah, J. McDevitt, and A. Farrell. A Resource Guide on Racial
Profiling Data Collection Systems: Promising Practices and Lessons Learned. Washington,
DC: Northeastern University, 2000
USDOJ.Principles.pdf  U.S. Department of Justice. Principles for Promoting Police
Integrity: Examples of Promising Police Practices and Policies, Washington, D.C.:
January 2001
British Studies
brit.stops.crime.prs127.pdf   Miller, Joel, Nick Bland, and Paul Quinton. The Impact of
Stops and Searches on Crime and the Community, Planning and Reducing Crime Unit, Home
Office, London, 2000
british.crime.survey.2000.pdf  Clancy, Anna, Mike Hough, Rebbecca Aust, Chris Kershaw.
Crime, Policing and Justice: the Experience of Ethnic Minorities Findings from the
2000 British Crime Survey, Home Office Research Study 223, Development and Statistics
Directorate, October 2001
brits.crimesurvey.r59.pdf  Bucke, Tom. Ethnicity and Contacts with the Police: Latest
Findings from the British Crime Survey, Research and Statistics Directorate, Home
Office, 1997
brits.pace.pdf  Bland, Nick, Joel Miller, and Paul Quinton. Upping the PACE?: An
Evaluation of the Recommendations of the Steven Lawrence Inquiry on Stops and Searches,
Planning and Reducing Crime Unit, Home Office, London, 2000
brits.police.stops.prs130.pdf  Quinton, Paul, Nick Bland, and Joel Miller. Police Stops,
Decision-Making, and Practice, Planning and Reducing Crime Unit, Home Office, London, 2000
brits.pop.avail.prs131.pdf  MVA and Joel Miller. Profiling Populations Available for
Stops and Searches, Planning and Reducing Crime Unit, Home Office, London, 2000
brits.public.views.prs129.pdf  Stone, Vanessa and Nick Pettigrew. The Views of the
Public on Stops and Searches, Planning and Reducing Crime Unit, Home Office, London, 2000
brits.search.manage.prs132.pdf  Bland, Nick, Joel Miller, and Paul Quinton. Managing
the Use and Impact of Searches: A Review of Force Interventions, Planning and Reducing
Crime Unit, Home Office, London, 2000

brits.stop.search.impact.pdf Bland, Paul. Stop/Search: Impact on Crime and on Public
Opinion, Home Office, 2000
brits.summary.polstop.pdf  Miller, Joel, Paul Quinton, and Nick Bland. Police Stops
and Searches: Lessons from a Programme of Research, Planning and Reducing Crime
Unit, Home Office, London, 2000

Appendix E
Recommendations: How to Eliminate Biased Policing
(Blindfolds for Justice)
This Appendix contains Captain Davis' points on the blindfolds
of justice. A summary of this material was included in Chapter 7.
This material is derived from A NOBLE Perspective: Racial Profiling
A Symptom of Bias-Based Policing (Next StepsCreating Blindfolds
of Justice), Ronald L. Davis, Ida Gillis, Maurice Foster, National
Organization of Black Law Enforcement Executives, May 3, 2001.
"Justice is blind" represents the basic motto and principle of our
criminal justice system. It symbolizes equity in the administration of
justice and represents our basic rights in a free society. Many in the
minority community, however, feel that society is not free and justice
is not blind. In fact the perception is that "justice" in many cases
distinguishes on the basis of race, ethnicity, gender, religious beliefs,
and social and economic status.
Justice is, among other things, a system of people influenced by the
biases and stereotypes brought to and learned at the job. In many
cases, biases and stereotypes may be unintentional and applied
subconsciously. In some cases, however, biases and stereotypes are
intentional and malicious, rising to the level of blatant discrimination.
However, whether intentional or unintentional, the application of bias
in policing tilts the scales of justice and results in unequal treatment
under the law.
Bias-based policing is defined as:
The act (intentional or unintentional) of applying or incorporating
personal, societal, or organizational biases and/or stereotypes as
the basis, or factors considered, in decision-making, police actions,
or the administration of justice.
Bias-based policing impacts all aspects of policing, and many feel
that it should be considered the most serious problem facing law
enforcement today. Racial profiling can be considered a symptom of
bias-based policing.
Administrators often fail to recognize the true problems behind bias-
based policing and respond only to symptoms. Responses are usually
"knee jerk" and largely ineffective. New symptoms will eventually
appear; and still more new responses will be developed. Valuable time

and resources are wasted on creating policies in response to symptoms
instead of eliminating the basic problems through a comprehensive
systematic approach.
The traditional symbol of justice in this country is a woman holding
a scaleblindfolded. The symbol does not suggest the woman is free
of bias or that justice is blind. The symbol represents the need to
blindfold those empowered to administer justice from personal and
societal prejudices when exerting the authority and power of office.
Although it is impossible to completely remove bias from people, it
is possible to create systems that "blindfold" people from bias. To
create blindfolds, agencies must analyze formal and informal operating
systems and identify more efficient and equitable practices in each
of the following domains: mission statement, recruiting and hiring,
training, assignment rotation, promotion, discipline/accountability,
community relations, and leadership. We will consider each of these
areas separately below.
Blindfold #1Mission Statement
Most agencies have mission-vision-value statements that are posted
throughout the agencies. In some cases, the only value they provide
to the agency is wall decoration. Mission-vision-value statements must
be "operationalized " in order to actually change the culture of the
organization.
The mission statement should identify the following:
 Who are our customers?
 What service(s) do we provide?
 How do we provide it (them)?
The vision statement should identify the goals of the agency. The
value statement should identify how we treat our customers and
our employees and serve as the organizational "Bill of Rights." The
mission-vision-value statement must be incorporated into every aspect
of operations. Each level of the organization must identify what role
they play in achieving the overall mission. If the mission, vision and
values are not understood, the direction of the agency is left to the
officers in the field to define. Consequently, the focus and direction of
staff as well as the deployment of resources may be based on officer
preferences, which do not necessarily reflect community needs or
priorities.

Administrators will need to be creative and relentless in marketing
the mission-vision-value statements throughout the agency and the
community. Mission-vision-value statements should be posted widely.
Promotional examinations must evaluate a candidate's ability to
"operationalize" the mission, vision, and values of the organization.
Awards and citations, written commendations, and disciplinary
proceedings should all take into consideration actions that either do
or do not reinforce organization values that contribute to the overall
mission. In short, the mission-vision-value statement must become
one of the most important documents in the agencyevery officer
should be able to cite and explain it.
In addition, the mission statement must focus on service, not crime
reduction. Agencies that establish a culture primarily focused on
crime reduction are more likely to experience bias-based policing and
increased officer misconduct. The result is an attitude to reduce crime
"by any means necessary" and, in many cases, target people based on
race, biases, and stereotypes. Phrases such as the "War on Drugs" may
contribute to a culture of community intolerance and a "we versus
them" mentality, thereby overriding the basic message of service.
Administrators must recognize that their words and actions can either
reinforce or contradict their mission statement.
Law enforcement agencies must work to establish a culture that values
quality and effective service over quantitative measures and/or arrests.
Officers must clearly understand that the agency values service above
enforcement. In this context, enforcement must be accepted as a tool,
not the mission, of the police.
Blindfold #2Recruitment and Hiring
Agencies must be forthright in their recruitment efforts. Marketing
strategies must provide prospective candidates a clear understanding
of the duties and responsibilities of the job. Agencies should avoid
using the image of television "cops" to attract candidates, and provide
potential candidates a true picture of law enforcement.45 Marketing
strategies must reinforce the mission, vision, and values of the agency.
Law enforcement agencies across the nation have initiated accelerated
hiring programs, which in many cases equates to the accelerated hiring
of unqualified candidates. Administrators must avoid the temptation
to recruit and hire candidates with clear warning signals in their
backgrounds, and closely evaluate candidates with no experience in
dealing with a diverse community or candidates without any relevant
experience. It is better to have staff shortages than hire the wrong
officer(s).
45 A recent recruiting commercial in northern California displayed officers in gas
masks, pointing firearms, and making high-risk entries. The commercial focused on
excitement and failed to display the basic nature of the job, service. The
commercial appeared to target "thrill seekers" versus service-oriented candidates.

Administrators must recognize the true value of diversity to an
organization. The race or gender of an officer does not make a
better officerdiversity, however, does make for a better organization.
Therefore, agencies should strive to diversify all levels of the
organization to reflect the demographics of the city or jurisdiction
represented. Diversity can help to establish trust in the community
and reinforce organizational values. A diverse agency will reflect
diverse views that provide administrators varying perspectives in the
development of policies, procedures, and crime-reduction strategies.
Blindfold #3Training
Most states have established commissions governing peace officer
standards and training that require police candidates to attend
professional academies. The quality of training provided to new
recruits for the most part is excellent; it is the focus of training that
needs change. Specifically, many police academies devote over a
third of the curriculum to the use of force. This sounds reasonable,
especially considering the impact of the inappropriate use of force on
the agency and community. The training, however, is often focused on
"how" to use force instead of "why" to use force.
Administrators are led to believe that extensive training on how to
use force is required to avoid liability. Clearly, administrators must
ensure that officers receive sufficient firearm and self-defense training
to obtain and maintain a high level of competency. It appears,
however, that most criminal and civil actions against officers and
agencies are based on the decision to use force or the level of force.
It is therefore crucial that we balance the number of training hours
provided in those areas that impact the decisions to use force, such
as police ethics, cultural diversity, community-oriented policing,
conflict resolution, dealing with mentally ill persons, and tactical
communication.
In addition, administrators must have the flexibility to remove
candidates who cannot be "blindfolded" from their personal or
societal biases. Police trainees should be considered probationary
employees. It is better to remove an inappropriate trainee than to
have to terminate a trainee after he or she becomes a police officer.
Agencies must also provide training in ethics, conflict resolution, and
decision-making with the same regularity as firearms and self-defense.
Police ethics must be incorporated in all facets of training, and
trainers must be cross-trained in police ethics and bias identification.
Training should be the responsibility of supervisors, managers, and
administrators, not just the academy staff.

Blindfold #4Discipline and Accountability Systems
Two levels of the organization are usually held accountable for officer
misconduct, the officer(s) who commit the offense and the Chief
of Police. First line supervisors and managers are rarely disciplined
or held accountable for the conduct of their officers or the "tone"
of their units. This should be changed so that accountability systems
hold every level of the organization accountable for misconduct.
Supervisors and managers must be held accountable for the conduct
of their subordinates when it is reasonable for them to have known
about the misconduct and no corrective action has been taken.
Supervisors and managers must also be accountable for establishing
a culture or tone within the agency that embraces the organizational
values and the Law Enforcement Code of Ethics.
Supervisors and managers who "overlook" incidents of misconduct,
protect officers from accountability, or fail to take immediate
corrective action must be removed from positions of responsibility.
However, disciplining supervisors and managers for the actions
of their subordinates is not common and is often met with great
opposition.46 Establishing managerial accountability is somewhat risky,
but the long-term benefits to the department and the community
should outweigh any opposition.
It is critical to give supervisors and managers appropriate tools to
prevent misconduct. One important tool is the ability to identify
officers with track records that would indicate the inability to
"blindfold" bias. An Early Warning System (EWS) must at minimum
identify officers who display bias indicators such as:
 High numbers of citizen complaints
 High numbers of use-of-force incidents
 High numbers of resisting-an-officer arrests
 Large number of arrests not charged due to improper detentions
and/or searches
 A negative attitude regarding programs that enhance police-
community relations.
An effective EWS will also track areas such as vehicle accidents,
sick leave abuse, and other indicators that would reflect a decline in
performance. Increased supervision, as well as additional training and/
or counseling, should be provided to officers identified by the EWS.
In addition, transfers from high-profile assignments, discipline, or
removal from office must also be considered for officers continually
identified as "high-risk."
46 One recent notable case occurred in the aftermath of the tragic shooting of
Tyisha Miller in Riverside, California. The Riverside Police Chief not only fired the
officers who shot and killed Ms. Miller, he also fired the sergeant that supervised
the shooting scene, citing that the sergeant's failure to provide leadership contributed
to the death of Ms. Miller. The chief's decision met with extreme opposition. Officers
in the police association shaved their heads in protest and spent thousands on a
marketing campaign against the chief. In the end, the police association lost the
campaign. The Riverside Police Department is under investigation by the United States
Department of Justice Civil Rights Division for possible patterns or practices of
police misconduct and is undergoing major reform.

Chief Executive Officers (CEOs) must retain the authority to
discipline employees. The power to discipline should not be delegated
either to lower levels of the organization, or to higher levels within
city government or external review boards or commissions.47 The
inability to discipline officers removes the ability to set the "tone" of
the organization or establish accountability systems.
Blindfold #5Assignment Rotation and Officer Development
Too much of a good thing can be bad. This is particularly pertinent to
officer assignments in vice, narcotics, specialized street enforcement,
and gang units, which may place officers in negative environments
for extended periods of time. Such officers spend the majority of
their time interacting with a negative element of the community that
represents a small percentage of the population. Those left too long
in this environment may become involuntarily conditioned to judge an
entire community based on their limited contacts with a subset of the
community.
Officers can also become malicious, callous, and even apathetic. This
is especially true in minority communities characterized by high crime.
Officers must be routinely rotated to increase interaction with all
segments of the community and understand all aspects of policing.
Officers must be conditioned to recognize that the negative segment
of the population is not the standard to evaluate an entire ethnic
group or community.
Blindfold #6Promotion(s)
Selecting future leaders of an agency is one of the most critical
tasks of an administrator. Civil service rules, labor contracts, and
political pressures often limit appointment authority. Most agencies
are required to use a promotional testing process to create eligibility
lists. The most common process is the assessment center, which
usually includes multiple-choice tests, written essays, oral interviews,
role-playing, and in-basket exercises. These processes are generally
effective, but they do have areas that contribute to bias-based policing.
In most assessment centers, assessors are recruited from outside
agencies based on their rank. Captains are sought to evaluate
lieutenants, and so on. In many cases, the agency does not know the
background of the assessor or the guiding philosophy or values of his
or her organization. Promotions are consequently left to the judgment
of the consultant delivering the exam and assessors from other
agencies. Under this system, top candidates may have a "bad day," and
unqualified candidates can "tap dance" to the top of the list.
47 This is not to suggest that employees should not have due process or even an
appeal process. Nor does it suggest that agencies should not support external review
boards that serve as audit or appeal forums for the community. It simply means the CEO,
who is expected to be able to make tough decisions in a fair and effective manner, has
responsibility for the final decision.

Some agencies use assessment centers that select assessors from
within the agency. This too may pose a problem. The candidates'
reputation or past interactions (positive and negative) with supervisors
and managers may taint the objectivity of the assessors and
compromise the integrity of the examination. If the agency lacks
diversity at supervisory and command levels, it may also contribute
to a perception that the process is biased against minorities. Whether
true or not, promotions under this system may appear to be based on
popularity or the "good old boys" system.
An example of the process and potential pitfalls
A NOBLE executive recently participated as an assessor in a captain's
promotion assessment center for a mid-size agency in the south.
The agency was undergoing major reform and adopting community-
oriented policing. The chief of police was very progressive with
a clear vision. A private consulting firm presented the test with
assistance from the city's personnel department. Prior to the start of
the examination the assessors received training on candidate rating and
evaluation.
The assessors were asked to review examples of each exercise, which
included an in-basket exercise, oral presentation, and an employee
subordinate meeting. Included in the in-basket exercise was a letter
from a pastor representing 12 churches in the minority community.
The group was concerned about police relations in the minority
community and felt officers were "racially profiling" young black men.
The churches wanted to conduct training in regard to driving while
black (DWB) and "what to do when stopped by the police." The
group asked for a representative of the police department to attend
the meeting and assist with the training. The letter was sent to the new
precinct captain.
The consultant stated that the successful candidate should recognize
that the minority community often has hidden agendas, and that
even when police-minority community relations are good, leaders in
the minority community would have personal agendas during high-
profile incidents (such as a white officer shooting a black suspect).
The consultant recommended that the successful candidate would
not attend the meeting, but would instead send a reply letter asking
for a future meeting. Also included in the exercise were letters from
a business group and a college administrator outlining their concerns
and requesting attendance at meetings. The consultant suggested the
successful candidate would attend these meetings.

The NOBLE executive became concerned and stressed the need for
every community to question the use of deadly force by the police.
He indicated that the meeting with church pastors provided the
new precinct captain an opportunity to meet with key leaders in the
minority community and listen to their concerns. The meeting also
provided a forum to reinforce the organization's mission, vision, and
values. Most importantly, the new precinct captain must recognize that
the people sharing their concerns at the meeting are the same people
needed to help improve police and community relations.
If the NOBLE executive had not mentioned his concerns to the
consultant, there could have been unfortunate results. Promotion
eligibility lists will reflect the judgment process, and administrators
then must live with the results.48 Promotions are too critical to be
left solely to the judgment of outside personnel consultants. CEOs
must take a personal interest in the process and, to the extent
permissible, review, audit, and approve all materials and assessors
prior to the examination process. CEOs must ensure that promotional
examinations are fair and impartial and designed to measure
competency based on objective behaviors. Also, examinations should
utilize a diverse pool of assessors who share the mission, vision, and
values of the organization as well as the demonstrated ability not to be
influenced by bias.
48 Fortunately for the chief of this agency, his message of service was strong enough
to "blindfold" the bias and prevent it from negatively impacting the testing process.
All but one candidate recognized the value of the meeting and stated not only would
they attend, they would also instruct all of their lieutenants to attend.
Examination results should not surprise a CEO. To the contrary,
examination results should reinforce the knowledge, skills, and abilities
required for the position and reinforce the agency's mission, vision,
and values. Promotions are not rewardsthey are responsibilities. The
baton of leadership must be passed to those who are prepared to
provide leadership, not simply those who can take a test.
Blindfold #7Community
Is there a conflict between safe streets and civil liberties? Drastic
crime reductions over the past few years and the promise of even
greater reductions have resulted in the increase of overly aggressive
police tactics and enforcement programs. Communities are sometimes
forced to choose between safe streets or civil liberties. In many urban
settings, the minority community is the greatest consumer of police
services. Yet, the greatest consumer often observes the most civil
liberty violations.
The minority community is often told that overly aggressive police
tactics are needed to reduce crime. A "we versus them" mentality
is created, and bias-based policing is reinforced. Minorities are, in
many cases, forced to stereotype within their race and accept police

misconduct against other minorities labeled or profiled as suspects of
crime. In fact, many in the minority community support officers found
guilty of misconduct or criminal behavior. For example, in recent
officer misconduct cases in New York City, Los Angeles, and Oakland,
officers were accused of egregious ethics and criminal violations
ranging from excessive force and torture to the planting of narcotics
on suspected drug dealers. Some in the minority community, however,
made public comments in support of the officers, citing a need to be
tough on crime.
This belief clearly displays community willingness to accept officer
misconduct in hopes of crime reduction. When a community believes
that its safety and quality of life is primarily dependent on overly
aggressive police tactics, it may result in an attitude of acceptance
of civil rights violations against persons identified or profiled as
"suspects".
Law enforcement must accept responsibility for the community's
belief that crime reduction outweighs civil liberties. The message of
service must not only be conveyed within the organization, it must
also reach the community. Many administrators continue to embrace
enforcement and arrest(s) as the sole answer to crime. This mentality
has sustained the "war on crime" and resulted in the disproportionate
arrest and conviction rates of minorities.
Statistics suggest that the most notable crime reductions occurred
during the recent community-policing era of policing, not necessarily
the enforcement era of the 80s. It does not appear that we won
the "war on drugs." We have an obligation to move forward and
use police and community relationships to develop comprehensive
crime-reduction strategies that attack all facets of crime, not just
incarceration. To reduce crime and maintain safe neighborhoods, the
police and the community must enter into a partnership.
Blindfold #8Leadership
Administrators must have the courage to manage by principle-based
leadership and serve as the driving force for change. Administrators
must make the commitment to do the right thingnot necessarily
what is popular. The CEO of today must survive politically charged
environments, strong labor unions and laws, and extremely demanding
communities. The true challenge is not to get so focused on keeping
your job that you forget to do your job. Crime reduction, and even
community satisfaction, at the cost of violating the constitutional
rights of one person is never acceptable.

In conclusion, the elimination of bias-based policing requires
a comprehensive program that establishes effective systems
in all aspects of policing. The eight blindfolds are important
recommendations to help eliminate biased policing. These systems
must be driven by principle-based leaders with the courage to make
change and demand the best quality of service for our communities.

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For More InForMatIon:
U.S. Department of Justice
Office of Community Oriented Policing Services
1100 Vermont Avenue, N.W.
Washington, DC 20530
To obtain details on the COPS Office program, call the
COPS Response Center at 800.421.6770
Visit COPS Online at the address listed below.
e06064106
Reprinted: July 5, 2006
www.cops.usdoj.gov