U.S. Department of Justice

Office of Community Oriented Policing Services

www.cops.usdoj.gov

How to Correctly Collect and Analyze Racial

Profiling Data:

Your Reputation Depends on it!
HOW TO CORRECTLY COLLECT AND ANALYZE RACIAL

PROFILING DATA:

YOUR REPUTATION DEPENDS ON IT!

Authors:

Joyce McMahon, Ph.D.

Joel Garner, Ph.D.

Captain Ron Davis

Amanda Kraus, Ph.D.

Prepared by:

The CNA Corporation
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.

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 Report for: Racial Profiling–Data Collection and Analysis.

(Washington, DC: Government Printing Office, 2002).
Table of Contents i

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

ii How to Correctly Collect and Analyze Racial Profiling Data
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 and to address the public's perception. 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

Letter From the Director iii

LETTER FROM THE DIRECTOR

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

Missouri–Columbia, 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 police–public 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

About the Authors v

ABOUT THE AUTHORS
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.

vi How to Correctly Collect and Analyze Racial Profiling Data
Executive Summary 1

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 agencies–Baltimore, Phoenix, Chattanooga,

and St. Paul–conduct 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

EXECUTIVE SUMMARY
2 How to Correctly Collect and Analyze Racial Profiling Data

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
Executive Summary 3

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 used–who 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.

Overview and Recommendations 5

1.1 Overview and Scope

The Office of Community Oriented Policing Services (COPS) 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

1.0 OVERVIEW AND RECOMMENDATIONS
6 How to Correctly Collect and Analyze Racial Profiling Data

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 crosspurposes. 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
Overview and Recommendations 7

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 community–a 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 (CA) Police

Department, a Vice President of NOBLE; Chief of Police Jerry

Oliver of the Richmond (VA) Police Department; and Chief of Police

Leonard G. Cooke of the Portsmouth (VA) 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.
8 How to Correctly Collect and Analyze Racial Profiling Data

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
Overview and Recommendations 9

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 CNAC’s 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.
10 How to Correctly Collect and Analyze Racial Profiling Data

! 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.
Overview and Recommendations 11

! 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 (COPS) 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.

Introduction 13
14 How to Correctly Collect and Analyze Racial Profiling Data

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.

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.

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. Specifically, it did not evaluate drug

interdiction efforts or, for example, interdictions for weapons

smuggling. 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 collection–not 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 limitations–funding, 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.

Introduction 15

2 Washington Post article dated June 21, 2001.

3 1999 Gallup Poll.

Methodology 17

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.
18 How to Correctly Collect/Analyze Racial Profiling Data

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.
Methodology 19

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 (CA) Police Department (a Vice President of NOBLE),

Chief of Police Jerry Oliver of the Richmond (VA) Police

Department, and Chief of Police Leonard G. Cooke of the

Portsmouth (VA) 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 process–in 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 will–and what will not–tend 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.
4 Racial Profiling: "What Does the Data Mean?" A Practitioner's Guide to Understanding Data Collection & Analysis, by Captain Ronald Davis, written for NOBLE.

20 How to Correctly Collect/Analyze Racial Profiling Data

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 of the 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
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 methods–essentially 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.

Methodology 21

4.0 LITERATURE REVIEW OF DATA

COLLECTION AND ANALYSIS APPROACHES

6 This listing does not include secondary sources, such as press accounts of reports that have not been made public.

Literature Review of Data Collection and Analysis Approaches 23

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.

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
7 The data tables for Chapter 4 are included in Appendix A. Some summary tables are included in the text.

24 How to Correctly Collect and Analyze Racial Profiling Data

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 4.1–4.4).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
Literature Review of Data Collection and Analysis Approaches 25

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.

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 contacts–arrests, 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.
26 How to Correctly Collect and Analyze Racial Profiling Data

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 contraband–typically illegal drugs

or weapons–were 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 selfidentify 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.
Literature Review of Data Collection and Analysis Approaches 27

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.
28 How to Correctly Collect and Analyze Racial Profiling Data

Summary Statement of Reported Finding for Stops and Searches by

Jurisdiction (and Author)

Type of Finding Stops Searches

Racial Profiling

No Racial Profiling

Mixed Evidence

Cannot Determine

No Statement

Issue Not Addressed

New Jersey (Lamberth: I-95)

New York City

Richmond

St. Paul

California

Connecticut

Florida

Lansing

Oakland

Sacramento

San Jose

Texas

Washington State

Missouri

North Carolina

New Jersey (NJAG)

San Diego

United States

Baltimore

Chattanooga

Michigan

Maryland (Knowles and Persico)

Maryland (Lamberth: Not I95)

Maryland (Lamberth: I-95)

Maryland (Lamberth: I-95)

New Jersey (NJAG)

St. Paul

Washington State

Connecticut

Lansing

Richmond

Sacramento

Maryland (Knowles and

Persico)

Missouri

North Carolina

Oakland

San Diego

United States

Baltimore

Maryland (Lamberth: Not I -

95)

Michigan

Texas

California

Chattanooga

Florida

New Jersey (Lamberth: I-95)

New York City

San Jose

Summary Table 4A
8 This categorization of the substantive findings of these reports is presented in tabular form in Table 4.5–4.6. 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.

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.

Literature Review of Data Collection and Analysis Approaches 29
30 How to Correctly Collect and Analyze Racial Profiling Data

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
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.

Literature Review of Data Collection and Analysis Approaches 31

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.
32 How to Correctly Collect and Analyze Racial Profiling Data

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 approach–using multiple

comparison groups–as 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.
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.

Literature Review of Data Collection and Analysis Approaches 33

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 contacts–the 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 searches–the 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 nonresidents 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."

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
34 How to Correctly Collect and Analyze Racial Profiling Data

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 4.7-4.8

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.
Literature Review of Data Collection and Analysis Approaches 35

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 examples–the New Jersey AG's

report and the Lamberth report on New Jersey–the 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 bestdesigned 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.
36 How to Correctly Collect and Analyze Racial Profiling Data

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 order–such as drug enforcement, violent

crime, property theft, problem-solving, or traffic laws–will 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
Literature Review of Data Collection and Analysis Approaches 37

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.

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 these–and not officer attitudes–may 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.
12 More extensive analyses of North Carolina data by Zingraff and his associates are expected in 2002.

38 How to Correctly Collect and Analyze Racial Profiling Data

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.

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, onevariable models–one 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' age, race, and sex.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, nature 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.

Race Stops
Literature Review of Data Collection and Analysis Approaches 39

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:

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.

Race

Age

Sex

Time of Stop

Location of Stop

Police Assignment

Suspect Behavior

Stops
40 How to Correctly Collect and Analyze Racial Profiling Data

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

Summary of Connecticut State Population and the Statewide Traffic

Stops

State Population Traffic Stops

White

Black

American Indian

Asian/Pacific

Islander

Other/Unknown

Totals

2,859,353 87.0%

274,269 8.4%

6,654 0.2%

50,698 1.5%

96,142 2.9%

3,287,116 100.0%

264,747 83.7%

38,272 12.1%

665 0.2%

5,421 1.8%

7,053 2.2%

316,158 100.0%

Summary Table 4B

Number Percent Number Percent

Summary Information of Traffic Stop Data for St. Paul

City Population

Non-Hispanic White

Black

Asian

Hispanic

Native American

Totals

Summary Table 4C

Count Percent Count Percent Count Percent

Race

Race

186,583 65.6%

34,861 12.3%

10,828 26.25%

20,756 7.3%

4,542 1.6%

284,526 100.0%

152,542 73.2%

21,302 10.2%

18,731 9.0%

13,076 6.3%

2,808 1.3%

208,459 100.0%

23,788 57.67%

10,828 26.25%

3,659 8.87%

2,768 6.71%

206 0.50%

41,249 100.00%

Over Age 18 Population Traffic Stops
Literature Review of Data Collection and Analysis Approaches 41

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.

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 nonresponse rates.

Police Contacted Respondents

Reasons for Contact Total White Black Hispanic Other Race

Summary Table 4D

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
42 How to Correctly Collect and Analyze Racial Profiling Data

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.

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.

North Carolina Search Rates

African Americans Whites

Searches

Citations/Warnings

Proportion of

Citations/Warnings

That Were Searched

Incident Rate of

Searches (Per 100,000)

Summary Table 4E

281

223,241

.00126

13

545

683,517

.00080

8

Difference in Incident Rate 5

African American/White Ratio 1.63
Literature Review of Data Collection and Analysis Approaches 43

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.
44 How to Correctly Collect and Analyze Racial Profiling Data

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 information–official records, citizen

surveys, independent observations–best 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.
Literature Review of Data Collection and Analysis Approaches 45

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 Research–Operational 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
46 How to Correctly Collect and Analyze Racial Profiling Data

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.
Literature Review of Data Collection and Analysis Approaches 47

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.
48 How to Correctly Collect and Analyze Racial Profiling Data

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 police–not 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.
Literature Review of Data Collection and Analysis Approaches 49

Alternative Study Samples:

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.

Resident Population

Available Population

Non-resident Population

Violator

Population

Stopped

Population

Searched

Population
50 How to Correctly Collect and Analyze Racial Profiling Data

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.

Literature Review of Data Collection and Analysis Approaches 51

Findings from the Conferences 53

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.

5.0 FINDINGS FROM THE CONFERENCES
54 How to Correctly Collect and Analyze Racial Profiling Data

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.

CNAC’s 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 gathering–in 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?
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.

Findings from the Conferences 55

! 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

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 comprised of

roughly 155,000 people–59 percent Caucasian, 36 percent African

American, two percent Hispanic, one percent Asian, and two percent

other. The daytime population, on the other hand, ranges from

230,000 to 240,000 people–87 percent Caucasian, 11 percent African
56 How to Correctly Collect and Analyze Racial Profiling Data

American, one percent Hispanic, one percent Asian, and .5 percent

other. The Chattanooga Police Department is 69 percent Caucasian,

28 percent African American, two percent Hispanic, zero percent

Asian, and one 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
14 These forms have considerable overlap, which will be discussed further in Chapter 6.

Findings from the Conferences 57

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 databases–the 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 1 January 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.

Second, public safety and community-police relations were important

issues in the campaign of Baltimore's recently elected mayor. In his
58 How to Correctly Collect and Analyze Racial Profiling Data

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.

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.)
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.

Findings from the Conferences 59

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.
17 The police department representative indicated that the press compared its information to the 2000 Ramsey County data–a 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.

60 How to Correctly Collect and Analyze Racial Profiling Data

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 Anglo, 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 Anglos slightly overrepresented. 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
Findings from the Conferences 61

A third issue is a technological one–currently, 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 for–in 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.
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 much–what kind of profiling is going on, and who is doing it is important to

devising proper policies.

62 How to Correctly Collect and Analyze Racial Profiling Data

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

community. 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
Findings from the Conferences 63

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 policecommunity 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.
64 How to Correctly Collect and Analyze Racial Profiling Data

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 absent–they rarely attend and often answer that they are too busy. This observation was echoed by the other cities.

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 on an ongoing basis. 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. The 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
Findings from the Conferences 65

24 One city indicated that citizen participation on review boards and community meetings was ineffective.

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.

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 highdiscretion 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
25 Possibly this was due to expectations of strong reactions to their viewpoints from some of the community representatives and/or police leadership.

66 How to Correctly Collect and Analyze Racial Profiling Data

! 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

! 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.
Findings from the Conferences 67

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 used–who 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.

Report on Site Visits 69

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

city–after all, the cities may or may not choose to consider CNAC’s

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
70 How to Correctly Collect and Analyze Racial Profiling Data

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

addressed–the 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.
Report on Site Visits 71

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 profiling–which 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 it–the media, politicians, individual citizens, outside

researchers.

# 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 job–they 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.
72 How to Correctly Collect and Analyze Racial Profiling Data

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 1 January 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.
Report on Site Visits 73

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, White,

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)

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 & badge number*

! Race/ethnicity of the person stopped

(African American, Asian, Hispanic, White,

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*

Figure 1

Figure 2

Starred items are also collected with the State Vehicle Stop Form
74 How to Correctly Collect and Analyze Racial Profiling Data

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 fair–and thorough–evaluation.

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
Report on Site Visits 75

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. 

The data on the citizen's side of the receipt include:

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.

! 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

explanation

Citizen/Police Contact Receipt
76 How to Correctly Collect and Analyze Racial Profiling Data

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.

29 As part of CNAC’s 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.

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

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 three and six-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

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 problem–they 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
Report on Site Visits 77

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.
78 How to Correctly Collect and Analyze Racial Profiling Data

! 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
Report on Site Visits 79

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.

80 How to Correctly Collect and Analyze Racial Profiling Data
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.

Subject Matter Expertise: Viewpoints from NOBLE 81

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.30He 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 biasbased 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.
82 How to Correctly Collect and Analyze Racial Profiling Data

Points About Collecting and Using Data

Most data that are being collected relate to traffic stops–e.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 Profiling–the 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.
Subject Matter Expertise: Viewpoints from NOBLE 83

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 practical–a critical

step to ending racial profiling–or is it merely symbolic–necessary 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 time–it 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.
84 How to Correctly Collect and Analyze Racial Profiling Data

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 "perfectly" match the demographics of the city.

This type of comparison–vehicle stop data against citywide census

data–became 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 inaccurate–it 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
Subject Matter Expertise: Viewpoints from NOBLE 85

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 jurisdiction–commonly 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 Study–Oakland, 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 lines–areas 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 unfortunately a high-crime,

low-income area. The hills area has lower crime and more affluent

neighborhoods.
86 How to Correctly Collect and Analyze Racial Profiling Data

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 racialgeographic 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 racialgeographic statistics. As discussed above, the best baseline for

Oakland is racial-geographic.

The next step is to identify staffing deployments relative to the racialgeographic 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.

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). Although 45

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
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 ten 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.

Subject Matter Expertise: Viewpoints from NOBLE 87

percent represents a reasonable initial stop-benchmark for Oakland,

the 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 trafficviolator or population demographics. As 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 three to ten 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
88 How to Correctly Collect and Analyze Racial Profiling Data

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, poststop 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 policegeographic 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.
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.

Subject Matter Expertise: Viewpoints from NOBLE 89

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 ten 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 reside–the 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 policedriven.35
90 How to Correctly Collect and Analyze Racial Profiling Data

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.

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.

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

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 AfricanAmericans have seatbelt non-compliance rates that are three times

higher than any other race or ethnicity. Consequently, AfricanAmerican youth are victims of traffic fatalities at similarly disparate

rates.

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 seatbelts–that 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
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.

Subject Matter Expertise: Viewpoints from NOBLE 91

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 societalbased 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 nonminorities, 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

profiling–it 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).
92 How to Correctly Collect and Analyze Racial Profiling Data

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.

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

yields–also known as "hit rates,"–indicates the exploratory searches

may be based primarily on biases and stereotypes.

Race

Black

White

Stops

High

Low

Violation(s)

Equipment/

Mechanical

Moving/

Low

Discretion

Searches

High

Low

Search Basis

Consent/

Discretion

Probable

Cause

Search

Results

Low Yields

Low Yields

Arrests

Low Arrests

Low Arrests
Subject Matter Expertise: Viewpoints from NOBLE 93

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.

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

would 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 Identification–More 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

Race

Black

White

Stops

High

Low

Violation(s)

Seatbelt

High

Discretion

Moving/

Low

Discretion

Searches

Low

Low

Search Basis

Probable

Cause

Probable

Cause

Search

Results

Low Yields

Low Yields

Arrests

Low Arrests

High Citation

Low Arrests

Low Citation
94 How to Correctly Collect and Analyze Racial Profiling Data

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.

great potential for misuse, which might further deteriorate policecommunity 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
44 Pockets of corruption (or bigotry) will diminish credibility, and must be screened out.

Subject Matter Expertise: Viewpoints from NOBLE 95

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 success–it'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 effort–data 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.
96 How to Correctly Collect and Analyze Racial Profiling Data

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 be comprised of 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
Subject Matter Expertise: Viewpoints from NOBLE 97

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 biasbased 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.
98 How to Correctly Collect and Analyze Racial Profiling Data

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.
Subject Matter Expertise: Viewpoints from NOBLE 99

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 perfect–but 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.
100 How to Correctly Collect and Analyze Racial Profiling Data

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.
Subject Matter Expertise: Viewpoints from NOBLE 101

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 deployment–to 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 "perfectly" match the citywide demographics. This

type of comparison–vehicle stop data against citywide census

data–became 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.
102 How to Correctly Collect and Analyze Racial Profiling Data

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 costeffective 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 policecommunity 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 importantly–ethically.

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 biasbased policing; the new policy, the agencies' data collection

program–its purposes and expected outcome (not in statistical

terms, but regarding values), and their roles to help ensure

success.

10. Collect & 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.

Subject Matter Expertise: Viewpoints from NOBLE 103

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

relevant–specific local variables or circumstances. Third, investigate

Discussion and Conclusions 105
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.

106 How to Correctly Collect and Analyze Racial Profiling Data
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

Discussion and Conclusions 107
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 used–who will own it, who will be responsible for

using it, how confidentiality can be maintained, and how frequently

reports should be generated and released.

108 How to Correctly Collect and Analyze Racial Profiling Data
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

incidents–not 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

Discussion and Conclusions 109
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.

110 How to Correctly Collect and Analyze Racial Profiling Data
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.

Discussion and Conclusions 111

Appendix A

Tables for Chapter 4

Appendix A 113

Table 4.1: Behavior Sampled and Agency Characteristics in Racial Profiling Reports

Jurisdiction/Author

Baltimore Police Department 

California Highway Patrol

Chattanooga Police Department

Connecticut: Chief State's

Attorney

Florida Highway Patrol

Lansing: Carter, et al.

Maryland/I - 95 Corridor:

Lamberth

Maryland/Not I-95 Corridor:

Lamberth

Maryland (I-95): Knowles and

Persico

Michigan State Police

Missouri Attorney General

New Jersey State Police:

Lamberth

New Jersey State Police:

Venerio & Zoubek

New York City: Spitzer

North Carolina: Zingraff, et al.

Oakland Police Department

Richmond: Smith and Petrocelli

Sacramento Police Department

San Diego Police Department,

2001

San Jose Police Department, 2000

St. Paul: Inst. on Race and

Poverty

Texas Department of Public

Safety

United States

Washington State Police

Type of Police

Behavior Sampled

All Stops

Traffic Contacts

Traffic Citations/

Field Interviews

Traffic Stops

Traffic Stops

Traffic Stops

Traffic Searches

Traffic Searches

Traffic Searches

Traffic Stops

Traffic Stops

Traffic Stops

Traffic Stops

Pedestrian Stops

Traffic Stops

Traffic Stops

Traffic Stops

Traffic Stops

Traffic Stops

Traffic Stops

Traffic Stops

Traffic Stops

Police Public

Contacts

Traffic Stops

Number

1

1

1

92

1

1

1

1

1

1

634

1

1

1

1

1

1

1

1

1

1

1

All

1

Geographical

Scope

Citywide

Statewide

Citywide

Statewide

Statewide

Citywide

Part of 1 Road

Statewide

(minus 1 Road)

Part of 1 Road

Statewide

Statewide

Part of Turnpike

Part of Turnpike

Citywide

Statewide

Citywide

Citywide

Citywide

Citywide

Citywide

Citywide

Statewide

Nationwide

Statewide

Type

City Police

State Police

City Police

State & Local Police

State Police

City Police

State Police

State Police

State Police

State Police

State and Local

Police & Sheriffs

State Police

State Police

City Police

State Police

City Police

City Police

City Police

City Police

City Police

City Police

State Police

Any Agency

State Police

Agencies Studied
114 How to Correctly Collect and Analyze Racial Profiling Data

Table 4.2: Police Activities Measured in Racial Profiling Reports

Jurisdiction/Author

Baltimore Police Department 

California Highway Patrol

Chattanooga Police Department

Connecticut: Chief State's Attorney

Florida Highway Patrol

Lansing: Carter, et al.

Maryland/I - 95 Corridor: Lamberth

Maryland/Not I-95 Corridor: Lamberth

Maryland (I-95): Knowles and Persico

Michigan State Police

Missouri Attorney General

New Jersey State Police: Lamberth

New Jersey State Police: Venerio &

Zoubek

New York City: Spitzer

North Carolina: Zingraff, et al. 2000

Oakland Police Department

Richmond: Smith and Petrocelli

Sacramento Police Department

San Diego Police Department, 2001

San Jose Police Department, 2000

St. Paul: Inst. on Race and Poverty

Texas Department of Public Safety

United States

Washington State Police

Contact

X

X

Stop

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

Search

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

Arrest

X

X

X

X

X

X

X

Police Behavior

Contraband

X

X

X

X

X

X

Force

X
Appendix A 115

Table 4.3: Characteristics of Suspects and Encounters in Racial Profiling Data Analyses

Jurisdiction/Author

Baltimore Police Department 

California Highway Patrol

Chattanooga Police Department

Connecticut: Chief State's Attorney

Florida Highway Patrol

Lansing: Carter, et al.

Maryland/I - 95 Corridor: Lamberth

Maryland/Not I-95 Corridor: Lamberth

Maryland (I-95): Knowles and Persico

Michigan State Police

Missouri Attorney General

New Jersey State Police: Lamberth

New Jersey State Police: Venerio &

Zoubek

New York City: Spitzer

North Carolina: Zingraff, et al. 2000

Oakland Police Department

Richmond: Smith and Petrocelli

Sacramento Police Department

San Diego Police Department, 2001

San Jose Police Department, 2000

St. Paul: Inst. on Race and Poverty

Texas Department of Public Safety

United States

Washington State Police

Race

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

Age

X

X

X

X

X

X

X

X

X

Residence

X

X

X

X

X

District

X

X

X

X

X

X

X

X

Police Behavior

License

X

Hour

X

X

X

X

Suspect Characteristics

Sex

X

X

X

X

X

X

X

X

X

X

X

X

X

X

Month

X

X
116 How to Correctly Collect and Analyze Racial Profiling Data

Table 4.4: Time Periods and Numbers of Activities Studied in Racial Profiling Reports

Jurisdiction/Author

Baltimore Police Department 

California Highway Patrol: Seperate

Reports on Contacts and Searches

Chattanooga Police Department

Connecticut: Chief State's Attorney

Florida Highway Patrol

Lansing: Carter, et al.

Maryland/I - 95 Corridor: Lamberth

Maryland/Not I-95 Corridor: Lamberth

Maryland (I-95): Knowles and Persico

Michigan State Police

Missouri Attorney General

New Jersey State Police: Lamberth

New Jersey State Police: Venerio &

Zoubek

New York City: Spitzer

North Carolina: Zingraff, et al. 2000

Oakland Police Department

Richmond: Smith and Petrocelli

Sacramento Police Department

San Diego Police Department, 2001

San Jose Police Department, 2000

St. Paul: Inst. on Race and Poverty

Texas Department of Public Safety

United States

Washington State Police

Primary

Author

PD

PD

PD

R/State

PD

R/PD

LT/R

LT/R

R

PD

State/R

LT/R

State

State

R

PD

R

R

PD/R

PD

R

PD

FED

PD/Other

Start End

01/01/2001 06/30/2001

07/01/1999 04/30/2000

10/01/1999 04/30/2000

07/01/2001 07/31/2001

01/01/2000 06/30/2000

01/01/2000 01/01/2001

02/12/2001 09/12/2001

01/01/1995 09/30/1996

01/01/1995 09/30/1996

01/01/1995 01/01/1999

01/01/2000 12/31/2000

08/28/2000 12/31/2000

01/01/1989 12/31/1991

04/01/1997 11/30/1998

01/01/1998 03/31/1999

01/01/1998 12/31/1998

03/01/2000 05/31/2000

02/14/2000 03/31/2000

07/01/2000 06/30/2001

01/01/2000 12/31/2000

07/01/1999 06/30/2000

04/15/2000 12/15/2000

03/01/2000 07/31/2000

07/01/1998 12/31/1999

05/01/2000 10/31/2000

Studied

All Stops

Traffic Contacts

Traffic Searches

Traffic Citations/

Field Interviews

Traffic Stops

Traffic Stops

Traffic Stops

Traffic Searches

Traffic Searches

Traffic Searches

Traffic Stops

Traffic Stops

Traffic Stops

Traffic Stops

Pedestrian Stops

Traffic Stops

Traffic Stops

Traffic Stops

Traffic Stops

Traffic Stops

Traffic Stops

Traffic Stops

Traffic Stops

Any Contact

Traffic Stops

Activity

Months

6 months

10 months

7 months

1 month

6 months

13 months

7 months

21 months

21 months

49 months

12 months

4 months

25 days

19

months*

15 months

12 months

3 months

6 weeks

12 months

12 months

12 months

8 months

4 months

12 months

6 months

Time Period

Number

89,889

2,638,589

23,584

4,239

316,158

604,108

19,353

823

1,549

1,590

564,672

453,189

2,896

87,489

174,919

651,556

21,338

2,673

36,854

168,901

97,154

41,249

779,961

80,543

338,885
Appendix A 117

Table 4.5: Reported Findings about Traffic Stops in Racial Profiling Reports 

Jurisdiction/Author

Baltimore Police Department 

California Highway Patrol: 

Chattanooga Police Department

Connecticut: Chief State's Attorney

Florida Highway Patrol

Lansing: Carter, et al.

Maryland/I - 95 Corridor: Lamberth

Maryland/Not I-95 Corridor: Lamberth

Maryland (I-95): Knowles and Persico

Michigan State Police

Missouri Attorney General

New Jersey State Police: Lamberth

New Jersey State Police: Venerio &

Zoubek

New York City: Spitzer

North Carolina: Zingraff, et al. 2000

Oakland Police Department

Richmond: Smith and Petrocelli

Sacramento Police Department

San Diego Police Department, 2001

San Jose Police Department, 2000

St. Paul: Inst. on Race and Poverty

Summary

None

NO

None

NO

NO

NO

Not Addressed

Not Addressed

Not Addressed

None

Maybe

Yes

Cannot Say

YES

MIXED

NO

YES

NO

Cannot Say

NO

YES

Text

The results show that CHP officers do not employ race/ethnicity as

a basis for enforcement stops (p. v)

Minority drivers do not appear to be treated differently than nonminority (p. ii).

The race, ethnicity and gender of the drivers stopped is basically

the same as the population at the state and county level (p. 1).

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).

The data have done nothing to disprove the perception of racial

profiling (p. 7).

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).

There is no way to interpret the significance of this data (p. 34).

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)

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. 

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).

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).

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).

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).

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). 

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). 
118 How to Correctly Collect and Analyze Racial Profiling Data

Table 4.5 (cont’d)

Jurisdicton/Author (cont’d)

Texas Department of Public Safety

United States

Washington State Police

Summary

(cont’d)

NO

Cannot Say

NO

Text (cont’d)

These statistics closely relate to the estimated population of Texas

(p. 1).

These racial differences are not necessarily evidence that police use

race as a factor in deciding whether to make a traffic stop (p. 13).

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).
Appendix A 119

Table 4.6: Reported Findings about Traffic Searches in Racial Profiling Reports

Jurisdiction/Author

Baltimore Police Department 

California Highway Patrol: 

Chattanooga Police Department

Connecticut: Chief State's Attorney

Florida Highway Patrol

Lansing: Carter, et al.

Maryland/I - 95 Corridor: Lamberth

Maryland/Not I-95 Corridor: Lamberth

Maryland (I-95): Knowles and Persico

Michigan State Police

Missouri Attorney General

New Jersey State Police: Lamberth

New Jersey State Police: Venerio &

Zoubek

New York City: Spitzer

North Carolina: Zingraff, et al. 2000

Oakland Police Department

Richmond: Smith and Petrocelli

Sacramento Police Department

San Diego Police Department, 2001

San Jose Police Department, 2000

St. Paul: Inst. on Race and Poverty

Texas Department of Public Safety

Summary

No statement

Not Addressed

Not Addressed

No

Not Addressed

No

Yes

None

MIXED

No statement

Maybe

Not Addressed

Yes

Not Addressed

MIXED

Cannot Say

No

No

Cannot Say

Not Addressed

Yes

No statement

Text

Minority drivers do not appear to be treated differently than nonminority (p. ii).

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).

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).

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).

The data have done nothing to disprove the perception of racial

profiling (p. 7).

The data presented to us show that minority motorists were

disproprotionately subject to consent searches (p. 30).

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.

The group concluded that a comprehensive analysis could not be

formed. ( p. 9).

Thus, minorities were no more likely than whites to be searched.

(p. 14 of report).

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).

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).

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).
120 How to Correctly Collect and Analyze Racial Profiling Data

Table 4.6 (cont’d)

Jurisdiction/Author (cont’d)

United States

Washington State Police

Summary

(cont’d)

Cannot Say

Yes

Text (cont’d)

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.

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).
Appendix A 121

Table 4.7: Annual and Per Capita Rates of Police Stops

Jurisdiction/Author

Baltimore Police Department 

California Highway Patrol

Chattanooga Police Department

Connecticut: Chief State's Attorney

Florida Highway Patrol

Lansing: Carter, et al.

Maryland/I - 95 Corridor:

Lamberth

Maryland/Not I-95 Corridor:

Lamberth

Maryland (I-95): Knowles and

Persico

Michigan State Police

Missouri Attorney General

New Jersey State Police: Lamberth

New Jersey State Police: Venerio &

Zoubek

New York City: Spitzer

North Carolina: Zingraff, et al.

2000

Oakland Police Department

Richmond: Smith and Petrocelli

Sacramento Police Department

San Diego Police Department,

2001

San Jose Police Department, 2000

St. Paul: Inst. on Race and Poverty

Texas Department of Public Safety

United States

Washington State Police

Type

All Stops

Stops of

Residents

Traffic Contacts

Traffic Citations

Field Interviews

Traffic Stops

Traffic Stops

Traffic Stops

No data

No data

No data

Traffic Stops

Traffic Stops

Traffic Stops

Traffic Stops

Pedestrian Stops

Traffic Stops

Traffic Stops

Traffic Stops

Traffic Stops

Traffic Stops

Traffic Stops

Traffic Stops

Traffic Stops

Any Contact

Traffic Stops

Pedestrian Stops

Traffic Stops

Data

Collection

Months

6

6

10

1

1

6

13

7

12

4

0.8

18

15

12

12

2

12

12

12

8

4

12

12

12

12

Estimated

Number

per Day

492

433

8,669

95

44

1,731

1,527

91

1,546

3,722

121

160

383

1,784

234

59

101

462

266

169

6,406

119,993

62,236

4,543

928

Estimated

Number

per Year

179,778

158,200

3,166,307

34,752

16,116

632,316

557,638

33,177

564,672

1,359,567

44,253

58,326

139,935

651,556

85,352

21,384

36,854

168,901

97,154

61,874

2,339,883

43,827,419

22,731,790

1,659,367

338,885

2000

Resident

Population

651,154

651,154

33,871,648

155,554

155,554

3,405,565

15,982,378

119,128

9,938,444

5,595,211

N.A.

N.A.

8,008,278

8,049,313

399,484

197,790

407,018

1,223,400

894,943

287,151

20,851,820

281,421,906

281,421,906

281,421,906

5,894,121

Police Behavior

Analyzed

Number

89,889

79,100

2,638,589

2,896

1,343

316,158

604,108

19,353

564,672

453,189

2,974

87,489

174,919

651,556

21,338

2,673

36,854

168,901

97,154

41,249

779,961

43,827,419

22,731,790

1,659,367

338,885

Stops

per 100

Residents

27.6

24.3

9.3

22.3

10.4

18.6

3.5

27.8

N.A.

N.A.

N.A.

5.7

24.3

N.A.

N.A.

1.7

8.1

21.4

10.8

9.1

13.8

10.9

21.5

11.2

15.6

8.1

0.6

5.7
122 How to Correctly Collect and Analyze Racial Profiling Data

Table 4.8: Annual and Per Capita Rates of Police Searches

Jurisdiction/Author

Baltimore Police Department

California Highway Patrol

Chattangooga Police Department

Connecticut: Chief State's

Attorney

Florida Highway Patrol

Lansing: Carter, et al.

Maryland/I - 95 Corridor:

Lamberth

Maryland/Not I-95 Corridor:

Lamberth

Maryland (I-95): Knowles and

Persico

Michigan State Police

Missouri Attorney General

New Jersey State Police: Lamberth

New Jersey State Police: Venerio

& Zoubek

New York City: Spitzer

North Carolina: Zingraff, et al.,

2000

Oakland Police Department

Richmond: Smith and Petrocelli

Sacramento Police Department

San Diego Police Department,

2001

San Jose Police Department, 2000

St. Paul: Inst. on Race and

Poverty

Texas Department of Public

Safety

United States

Washington State Police

Searches

Analyzed

Number

759

23,584

11,984

No data

1,418

823

1,549

1,590

27,800

31,906

No data

1,193

940

2,229

211

6,562

10,754

No data

3,540

26,737

1,272,282

7,729

Data

Collection

Months

6

7

6

7

21

21

49

12

4

18

12

3

2

12

12

8

4

12

12

Estimated

Number

per Day

4.2

110.7

65.6

6.7

1.3

2.4

1.1

76.1

262.1

2.2

2.6

24.4

4.6

18.0

29.4

14.5

219.6

3,483.3

21.2

Estimated

Number

per Year

1,518

40,430

23,968

2,431

470

885

389

27,800

95,718

795

940

8,916

1,688

6,562

10,754

5,310

80,211

1,272,282

7,729

2000

Resident

Population

651,154

33,871,648

155,554

3,405,565

15,982,378

119,128

N.A.

N.A.

N.A.

9,938,444

5,595,211

N.A.

N.A.

8,008,278

8,049,313

399,484

197,790

407,018

1,223,400

894,943

287,151

20,851,820

281,421,906

5,894,121

Searches

per 100

Stops

1.0

1.3

N.A.

3.8

N.A.

7.3

N.A.

N.A.

N.A.

4.9

7.0

N.A.

1.4

N.A.

0.1

10.4

7.9

17.8

6.4

N.A.

8.6

3.4

5.6

2.3

Searches

per 100

Residents

0.2

0.1

N.A.

0.7

N.A.

2.0

N.A.

N.A.

N.A.

0.3

1.7

N.A.

N.A.

N.A.

0.0

2.2

0.9

1.6

0.9

N.A.

1.8

0.4

0.5

0.1

Data collected but not reported

Data collected but not reported
Appendix A 123

Table 4.9: Comparison Groups Used in Racial Profiling Reports

Jurisdiction/Author

Baltimore Police Department

California Highway Patrol

Chattangooga Police Department

Connecticut: Chief State's

Attorney

Florida Highway Patrol

Lansing: Carter, et al.

Maryland/I - 95 Corridor:

Lamberth

Maryland/Not I-95 Corridor:

Lamberth

Maryland (I-95): Knowles and

Persico

Michigan State Police

Missouri Attorney General

New Jersey State Police:

Lamberth

New Jersey State Police: Venerio

& Zoubek

New York City: Spitzer

North Carolina: Zingraff, et al.,

2000

Oakland Police Department

Richmond: Smith and Petrocelli

Sacramento Police Department

San Diego Police Department,

2001

San Jose Police Department,

2000

St. Paul: Inst. on Race and

Poverty

Texas Department of Public

Safety

United States

Washington State Police

Resident

Population

X

X

X

X

X

X

X

X

X

X

X

X

X

X

Driving

Age Population

X

X

X

X

Traffic

Accidents

X

X (Map)

Licensed

Drivers

X1

X2

X

Traffic

Violators

X

X

X

Arrested

Persons

X

X

X (Map)

X

Crime

Suspects

X

X

X

X (Map)

Type of 

Statistical

Analysis

BV

BV

BV

BV

BV

BV

BV

MV

BV

BV

BV

BV

BV

MV

BV/TV

BV

MV

BV

BV

BV

BV

BV

BV

BV

Comparison Groups Used

Appendix B 125

Appendix B 

Agenda for August Conference

Profiling Technical Assistance Conference

Irving Shaknov Conference Center

0800-0900

0900-0930

0930-1000

1000-1030

1030-1045

1045-1115

1115-1145

1145-1200

1200-1300

1300-1330

1330-1430

1430-1530

1530-1545

1545-1630

1630-1730

1730

Registration & Continental Breakfast

Welcome & Opening Remarks

Dr. Joyce McMahon, CNAC

Mr. James (Chips) Stewart, CNAC

Presentation

Chattanooga

Presentation

Baltimore

Break

Presentation

St. Paul 

Presentation

Phoenix

Discussion of presentations, follow-on questions

Lunch at CNAC

Keynote Speaker

Jerry Oliver, Chief of Police

Richmond Police Department

Joel Garner, Joint Centers for Justice Studies

Technical assistance topics 

Ronald Davis from Oakland Police Department, NOBLE

Operational Issues

Break

Set up working groups, work on analysis plan

Dr. Ellen Scrivner will join us

Deputy Director, Community Oriented Policing Services

(NOBLE Executives will also join us)

Adjourn

Informal Reception

Clyde's Restaurant (Deck Area) 

(Half-price appetizers; also a good place for dinner)

Monday, August 20, 2001
126 How to Correctly Collect and Analyze Racial Profiling Data

0800-0900

0900-0915

0915-1000

1000-1020

1020-1040

1040-1050

1050-1110

1110-1130

1130-1200

1200-1300

1300-1330

1330

Continental Breakfast

Welcome back – Administrative Details

Get in groups, review/revise city analysis plans 

and share input with paired city

Presentation

Chattanooga

Presentation

Baltimore

Break

Presentation

St. Paul

Presentation

Phoenix

Overall Assessment, Advice to Cities, What is at Stake?

Jerry Oliver & Ronald Davis

Lunch at CNAC

Discuss October meeting

Adjourn

Tuesday, August 21, 2001
Appendixc C 127

Appendix C

Agenda for October Conference

Profiling Technical Assistance Conference

CNAC Conference Center (Boardroom)

8:00-9:00

9:00-9:30

9:30-10:00

10:00-10:30

10:30-10:45

10:45-11:45

11:45-12:00

12:00-1:00

1:00-2:00

2:00-2:30

2:30-3:00

3:00-4:00

4:00-5:00

5:00-5:30

6:30-7:30

Registration & Continental Breakfast

Welcome to Our 2nd Conference & Opening Remarks

Dr. Joyce McMahon, CNAC

Keynote Speaker: James K. (Chips) Stewart, CNAC

The Importance of "Getting it Right"

Discuss overall theme of second conference–working conference

Data collection and analysis issues: practical measures that you can undertake

Review of existing reports and articles–rating their usefulness to you

Joel Garner

Break

Captain Ronald Davis, Commander, Oakland Police Department, and Vice-President

of NOBLE

Captain Davis will talk about his methodology for estimating the "expected" stop rates, given

specific within-city variation in characteristics (noted during the August conference), which

could be applied effectively for many cities and municipalities

Discussion of the morning sessions, follow-on questions 

Lunch at CNAC

CNAC analysts will lead a discussion about specific data issues

How to extend your resources; add technical capabilities at low cost

Other uses of data collected (management and efficiency)

Data issues: POV of Police Department data representatives and analysts

Response to suggestions offered in previous session

Break

Captain Ronald Davis

Reflections from the Town Hall at Cincinnati (lessons learned on police-community

interactions)

Break into smaller working groups

to discuss specific techniques and applications of methodologies

Subject matter experts (e.g., Ronald Davis) and analysts will work individually with each

group

Shuttle service to return conference attendees to the Washington Suites

Complimentary reception provided by The Washington Suites (Duke's Market Café –

2nd Floor)

Thursday, October 25, 2001
128 How to Correctly Collect and Analyze Racial Profiling Data

8:00-9:00

9:00-9:15

9:15-10:00

10:00-10:30

10:30-11:30

11:30-12:00

12:00-1:00

1:00-1:30

1:30

Continental Breakfast

Welcome back –administrative details

Split into three groups

Police, Union, and Community

Discuss common threads observed

Roles with other two groups, the media, politicians

Discuss group perspectives on profiling for terrorists

Break

Start reimbursement paperwork with Bernadette Lynch

Bring together issues of terrorist profiling

How is it being done? How should it be done?

Hazards?

Are there parallels to draw or lessons learned to apply?

Solicit comments from participants

Feedback for the direction for data collection, analysis, and evaluation

What are the future challenges and risks for these endeavors?

Lunch at CNAC

Wrap up–discuss any issues / themes identified during the conference

Closing comments by Captain Ronald Davis 

More reflections on the importance of getting it right

Adjourn

(Or linger around and discuss some more)

Finish filing paperwork with Bernadette Lynch

Friday, October 26, 2001
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.

Appendix D 129

Paper

bjs.Public Contact99.pdf

BJS.Traffic Stop

Data.Survey99.PDF

california.chp.pdf

Paper

Conn.traffic.pdf

florida.pdf

Paper

lamberth.pdf

Lansing.6 Month

Report.pdf

lansing.policy.2000.pdf

lexington.traffic.pdf

michigan.2000.pdf

Baltimore Police Department. Citizen/Police Contact Receipt Analysis Report,

01/01/2001 - 06/30/2001

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

Strom, Kevin and Matthew R. Durose. Traffic Stop Data Collection Policies for State

Police, 1999, Bureau of Justice Statistics, 2000

Department of CA Highway Patrol. Public Contact Demographic Data Summary:

Report to the Governor, July 2000

Chattanooga Police Department. Courtesy, Professionalism, Respect. Overview of Racial

Profiling Procedures

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 Highway Patrol. Racial Profiling [web pages on policies and data analysis at

http://www.fhp.state.fl.us/html/census/profile.html]

Knowles, John and Nicola Persico. "Racial Bias in Motor Vehicle Searches:

Theory and Evidence," Journal of Political Economy, vol. 109, #1, 2001

Lamberth, John. Report of John Lamberth, American Civil Liberties Union, 1996

Carter, David, Andra Katz-Bannister, and Joseph Schafer. Lansing Police Department

MATS Data Six Months Analysis, Lansing Police Department, October, 2001

Carter, D.L. & Katz-Bannister, A.J. Racial Profiling: Issues and Responses for the

Lansing, Michigan Police Department, December 2000

August 2000 Traffic Charges Report, Lexington-Fayette County, Department of Police,

September 2000

Michigan Department of State Police. Traffic Enforcement Summary, Third Quarter

Report, July through September 2000.

U.S. Single Site Studies
130 How to Correctly Collect and Analyze Racial Profiling Data

minn.datacollect.pdf

missour.2001.pdf

newjersey.farmer.pdf

NJ.AG.interim.pdf

NYAG.stop.frisk.pdf

Paper

Paper

sandiego.pdf

Paper

Paper

Paper

Paper

sacramento.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.]

Missouri Attorney General. 2000 Annual Report on Missouri Traffic Stops, 2000

Farmer, J.J. Final Report of the State Police Review Team. Trenton: Attorney General

of New Jersey, 1999

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

Spitzer, E. The New York City Police Department's 'Stop and Frisk' Practices. New York:

Attorney General of New York, 1999

Oliver, J.A. and A.R. Zatcoff. "Lessons Learned: Collecting Data on Officer

Traffic Stops," Police Chief, July 2001, pp. 23-24

San Diego Police Department. Vehicle Stop Study Mid-Year Report. San Diego: San

Diego Police Department, 2000

San Diego Police Department. Vehicle Stop Study Year end Report: 2000. San Diego:

San Diego Police Department, May, 2001

San Jose Police Department. Vehicle Stop Demographic Study: First Report. San Jose:

San Jose Police Department, 1999

San Jose Police Department. Vehicle Stop Demographic Study: Second Report. San Jose:

San Jose Police Department, 2000

Smith, Michael and Matthew Petrocelli. "Racial Profiling?: A Multivariate Analysis

of Police Traffic Stop Data," Police Quarterly, March, 2001, 4-27

Smith, Michael. The Traffic Stop Practices of the Richmond, Virginia Police Department,

Department of Criminal Justice, November, 2000

Greenwald, H.P. Final Report: Police Vehicle Stops in Sacramento, CA. University of

Southern California, 2001

Appendix D (cont’d)
Appendix D 131

SPPD.traffic.pdf

texas.2000.pdf

washington.state2000.pdf

washington.state.2001.pdf

zingraff.2000.pdf

General Studies

AG report.Feb2000.pdf

denver.datasheet.pdf

Early.warn.pdf

gao.2000.pdf

harris.dwb.pdf

iacp.trafficstopssummnet

2.pdf

minn.raceprofiling.issues.

pdf

Noble.perspective.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 Department of Public Safety. Traffic Stop Report, October 2000

Sandberg, A.M. Washington State Patrol Demographic Data Collection, October 1999 to

February 2000, May 2000

Washington State Patrol and Criminal Justice Training Commission. Report to the

Legislature on Routine Traffic Stop Data, January 2001

Zingraff, Matthew T., Marcinda Mason, William Smith, Donald TomaskovicDevey, 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

Reno, Janet. Traffic Stops and Data Collection: Analyzing and Using the Data, A Report

of the Proceedings, February, 2000

Denver Police Department Citizen Contact Sheet, 2001-03

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

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, David A. Driving While Black: Racial Profiling on our Nation's Highways,

American Civil Liberties Union, 1999

IACP. IACP Police Trafffic Stops II, Alexandria, Va: IACP, March 2001

Cleary, J. Racial Profiling Studies in Law Enforcement: Issues and Methodology. Minnesota

House of Representatives, Research Department. June 2000

Davis, Ronald L., Ida Gillis, Maurice Foster. A NOBLE Perspective: Racial

Profiling–A Symptom of Bias-Based Policing (Next Steps–Creating Blindfolds of Justice),

National Organization of Black Law Enforcement Executives, May 3, 2001

Appendix D (cont’d)
132 How to Correctly Collect and Analyze Racial Profiling Data

PERF.Racial Biased 

Policing.pdf

Ramizrez.pdf

USDOJ.Principles.pdf

British Studies

brit.stops.crime.prs127.

pdf

british.crime.survey.200

0.pdf

brits.crimesurvey.r59.

pdf

brits.pace.pdf

brits.police.stops.prs130

.pdf

brits.pop.avail.prs131.

pdf

brits.public.views.prs129

.pdf

brits.search.manage.prs

132.pdf

Fridell, Lori, Robert Lunney, Drew Diamond, and Bruce Kubu. Racial Biased

Policing: A Principled Response, Police Executive Research Forum, Washington, D.C.,

2001

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

U.S. Department of Justice. Principles for Promoting Police Integrity: Examples of

Promising Police Practices and Policies, Washington, D.C.: January 2001

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

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

Bucke, Tom. Ethnicity and Contacts with the Police: Latest Findings from the British Crime

Survey, Research and Statistics Directorate, Home Office, 1997

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

Quinton, Paul, Nick Bland, and Joel Miller. Police Stops, Decision-Making, and

Practice, Planning and Reducing Crime Unit, Home Office, London, 2000

MVA and Joel Miller. Profiling Populations Available for Stops and Searches, Planning

and Reducing Crime Unit, Home Office, London, 2000

Stone, Vanessa and Nick Pettigrew. The Views of the Public on Stops and Searches,

Planning and Reducing Crime Unit, Home Office, London, 2000

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

Appendix D (cont’d)
Appendix D 133

brits.stop.search.impact.

pdf

brits.summary.polstop.

pdf

Bland, Paul. Stop/Search: Impact on Crime and on Public Opinion, Home Office, 2000

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 D (cont’d)

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 Steps–Creating

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 biasbased 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

Appendix E 135
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. We will consider each of these

areas separately below.

Blindfold #1–Mission 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.

136 How to Correctly Collect and Analyze Racial Profiling Data
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 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 agency...every 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 #2–Recruitment 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).

Appendix E 137
Administrators must recognize the true value of diversity to an

organization. The race or gender of an officer does not make a better

officer–diversity, 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 #3–Training

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.

138 How to Correctly Collect and Analyze Racial Profiling Data
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.

Blindfold #4–Discipline 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 policecommunity 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."

Appendix E 139
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.

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 #5–Assignment 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 #6–Promotion(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, roleplaying, 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.

140 How to Correctly Collect and Analyze Racial Profiling Data
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 communityoriented 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.

Appendix E 141
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.

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.

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 rewards–they 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 #7–Community 

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

142 How to Correctly Collect and Analyze Racial Profiling Data
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 80's. 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 crimereduction 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 #8–Leadership

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 thing–not 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.

Appendix E 143
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.

144 How to Correctly Collect and Analyze Racial Profiling Data
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www.cops.usdoj.gov

FOR MORE INFORMATION:

U.S. Department of Justice

Office of Community Oriented Policing Services

1100 Vermont Avenue, NW

Washington, D.C. 20530

To obtain details on the COPS Office program, call the

U.S. Department of Justice Response Center at 1.800.421.6770

Visit the COPS internet web site by the address listed below.

e11021793 Created Date: December 26, 2002