RACIAL PROFILING

Limited Data

Available on Motorist

Stops

United States General Accounting Office

GAO Report to the Honorable

James E. Clyburn, Chairman

Congressional Black Caucus

March 2000

GAO/GGD-00-41

United States General Accounting Office General Government Division

Washington, D.C. 20548

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March 13, 2000

The Honorable James E. Clyburn

Chairman, Congressional Black Caucus

Dear Mr. Chairman:

Racial profiling of motorists by law enforcement—that is, using race as a

key factor in deciding whether to make a traffic stop—is an issue that has

received increased attention in recent years. Numerous allegations of

racial profiling of motorists have been made and several lawsuits have

been won.

As agreed with your office, this report provides information on (1) the

findings and methodologies of analyses that have been conducted on racial

profiling of motorists; and (2) federal, state, and local data currently

available, or expected to be available soon, on motorist stops.

We found no comprehensive, nationwide source of information that could

be used to determine whether race has been a key factor in motorist stops.

The available research is currently limited to five quantitative analyses that

contain methodological limitations; they have not provided conclusive

empirical data from a social science standpoint to determine the extent to

which racial profiling may occur. However, the cumulative results of the

analyses indicate that in relation to the populations to which they were

compared, African American motorists in particular, and minority

motorists in general, were proportionately more likely than whites to be

stopped on the roadways studied. Data on the relative proportion of

minorities stopped on a roadway, however, is only part of the information

needed from a social science perspective to assess the degree to which

racial profiling may occur.

A key limitation of the available analyses is that they did not fully examine

whether different groups may have been at different levels of risk for being

stopped because they differed in their rates and/or severity of committing

traffic violations.1

 Although we have no reason to expect that this

 

1

 As used in this report, traffic violations that can legitimately put motorists at risk of being stopped

include actions by drivers and characteristics of motor vehicles that constitute traffic/vehicle code

infractions. These could include, for example, speeding, tailgating, failing to signal a lane change,

driving an unregistered vehicle, driving with license plates not clearly visible, failing to dim the

vehicle’s high beams when there is oncoming traffic, and equipment violations.

Results in Brief
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occurred, such data would help determine whether minority motorists are

stopped at the same level that they commit traffic law violations that are

likely to prompt stops. The best studies that we identified sought to

determine the racial composition of motorists at risk of being stopped and

collected data on the population of travelers and traffic violators on

specific roadways. However, even these well-designed studies made no

distinction between the seriousness of different traffic violations, and it is

not clear that all violations are equally likely to prompt a stop. There

appears to be little comparative research on traffic violations committed

by different racial groups, including possible differences in the type or

seriousness of traffic violations. In addition, none of the studies provided

information on which traffic violations, if any, were more likely to prompt

a stop. More information is needed to determine the extent to which race,

as opposed to other factors, may be the reason for the traffic stop.

Several analyses compared the racial composition of stopped motorists

against that of a different population, but the validity of these comparison

groups was questionable. In addition, missing data may have skewed the

results of some analyses. Finally, because only a few locations have been

studied, and these locations were not selected to be generally

representative of motorist roadways, the results cannot be generalized to

roadways and locations other than those reviewed. These limitations

notwithstanding, we believe that in order to account for the disproportion

in the reported levels at which minorities and whites are stopped on the

roadways, (1) police officers would have to be substantially more likely to

record the race of a driver during motorist stops if the driver was a

minority than if the driver was white, and (2) the rate and/or severity of

traffic violations committed by minorities would have to be substantially

greater than those committed by whites. We have no reason to expect that

either of these circumstances is the case.

Federal, state, and local agencies are in various stages of gathering data on

motorist stops, and these efforts should augment the empirical data

available from racial profiling studies. The federal government, which has

a limited role in making motorist stops, is undertaking several efforts to

collect data. For example, the Justice Department’s Bureau of Justice

Statistics (BJS) is conducting a national household survey that should

provide aggregate data on the characteristics of stopped motorists and the

nature of the traffic stops. BJS is also conducting other surveys that should

identify the motorist stop information maintained by state and local law

enforcement agencies. In accordance with a presidential directive, three

federal departments are preparing to collect data on the race, ethnicity,

and gender of individuals whom they stop or search. State and local
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agencies are in the best position to provide law enforcement data on

motorist stops because most motorist stops are made by state and local

law enforcement officers. A number of state legislatures are considering

bills to require state and/or local police to collect race and other data on

motorist stops, and Connecticut and North Carolina have passed such

legislation. Several local jurisdictions are also making efforts to collect

motorist stop data.

Given the paucity of available data for assessing whether and to what

extent racial profiling may exist, current efforts to collect information on

who is stopped and why are steps in the right direction. Getting more and

better data involves a variety of methodological considerations and

information needs. Whether the efforts that are currently under way will

produce the type and quality of information needed to answer questions

about racial profiling remains to be seen.

The Fifth and Fourteenth Amendments prohibit law enforcement officers

from engaging in discriminatory behavior on the basis of individuals’ race,

ethnicity, or national origin. The Fifth Amendment protects against

discrimination by federal law enforcement officers, and the Equal

Protection Clause of the Fourteenth Amendment protects against

discrimination by state and local law enforcement officers. Two federal

statutes also prohibit discrimination by law enforcement agencies that

receive federal financial assistance. Title VI of the Civil Rights Act of 19642

prohibits discrimination on the basis of race, color, or national origin by all

recipients of federal financial assistance. The Omnibus Crime Control and

Safe Streets Act of 19683

 prohibits discrimination on the basis of race,

color, national origin, sex, or religion by law enforcement agencies that

receive federal funds pursuant to that statute. In addition, a 1994 statute

grants the Attorney General the authority to seek injunctive relief when a

state or local law enforcement agency engages in a pattern or practice of

conduct that violates the Constitution or federal law, regardless of whether

the agency is a recipient of financial assistance.4

The Fourth Amendment guarantees the rights of people to be secure from

unreasonable searches and seizures. The temporary detention of

individuals during the stop of an automobile by police constitutes a seizure

of persons within the meaning of the Fourth Amendment. The Supreme

 2

 42 U.S.C. 2000d.

3

 42 U.S.C. 3789d(c).

4

 42 U.S.C. 14141.

Background
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Court recently held that regardless of an officer’s actual motivation, a stop

of an automobile is reasonable and permitted by the Fourth Amendment

when the officer has probable cause to believe that a traffic violation

occurred.5

 The Court noted, however, that the Constitution prohibits

selective enforcement of the law based on considerations such as race, but

the constitutional basis for objecting to intentionally discriminatory

application of laws is the equal protection provisions of the Constitution,

not the Fourth Amendment.

Some have expressed concern that the escalation of this country’s war on

drugs has placed minorities at increased risk of discriminatory treatment

by law enforcement. The allegation is that law enforcement officers stop

minority motorists for minor traffic violations when, in reality, the stop is a

pretext to search for drugs or other contraband in the vehicle.

In 1986, the Drug Enforcement Administration (DEA) established

Operation Pipeline, a highway drug interdiction program that trains

federal, state, and local law enforcement personnel on indicators that

officers should look for that would suggest possible drug trafficking

activity among motorists. In a 1999 report,6

 the American Civil Liberties

Union (ACLU) stated that Operation Pipeline fostered the use of a racially

biased drug courier profile, in part by using training materials that

implicitly encouraged the targeting of minority motorists. DEA’s position is

that it did not and does not teach or advocate using race as a factor in

traffic stops. Further, according to DEA officials, a 1997 review of

Operation Pipeline by the Justice Department’s Civil Rights Division,

which is responsible for the enforcement of statutory provisions against

discrimination, concluded that Operation Pipeline did not instruct trainees

to use race as a factor in traffic stops.

Representatives of organizations representing law enforcement officers

have stated that racial profiling is unacceptable. The National Association

of Police Organizations, representing more than 220,000 officers

nationwide, has expressed opposition to pulling over an automobile,

searching personal property, or detaining an individual solely on the basis

of the individual’s race, ethnicity, gender, or age. The International

Association of Chiefs of Police, one of the largest organizations

representing police executives, stated that stopping and searching an

individual simply because of race, gender, or economic level is unlawful

 5

 Whren v. U.S., 116 S. Ct. 1769 (1996).

6

 “Driving While Black: Racial Profiling On Our Nation’s Highways.” American Civil Liberties Union,

June, 1999.
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and unconstitutional and should not be tolerated in any police

organization. Neither group supports federally mandated collection of data

on motorist stops.

Lawsuits alleging racial profiling have been filed in a number of states,

including Oklahoma, New Jersey, Maryland, Illinois, Florida, Pennsylvania,

and Colorado. For example, in Colorado, a class action suit filed on behalf

of 400 individuals asked the court to halt racially based stops by a Sheriff’s

Department highway drug interdiction unit. Traffic infractions were cited

as the reason for stopping the motorists, but tickets were not issued. The

court ruled that investigatory stops based solely on motorists’ match with

specified drug courier indicators violated the Fourth Amendment’s

prohibitions against unreasonable seizures.7

 A settlement was reached that

awarded damages to the plaintiffs and disbanded the drug unit. In another

case, a class action lawsuit filed by ACLU against the Maryland State

Police resulted in a settlement that included a requirement that the state

maintain computer records of motorist searches. These records are

intended to enable the state to monitor for any patterns of discrimination.8

In yet another case, a Superior Court in New Jersey ruled that the New

Jersey State Police engaged in discriminatory enforcement of the traffic

laws.9

The Justice Department’s Civil Rights Division has recently completed

investigations in New Jersey and Montgomery County, MD, which included

reviewing complaints of discriminatory treatment of motorists. In the New

Jersey case, Justice filed suit in U.S. District Court alleging that a pattern

or practice of discriminatory law enforcement had occurred. The parties

filed a joint application for entry of a consent decree, which the judge

approved in December 1999. Under the consent decree, state troopers in

New Jersey will be required to collect data on motorist stops and searches,

including the race, ethnicity, and gender of motor vehicle drivers. In the

Maryland case, the Justice Department and Montgomery County signed a

Memorandum of Understanding in January 2000 that resolved the issues

raised in Justice’s investigation. The agreement included the requirement

that the Montgomery County Police Department document all traffic stops,

including information on the race, ethnicity, and gender of drivers.

 

7

 Whitfield v. Board of County Commissioners of Eagle County, 837 F. Supp. 338 (D. Colo.1993).

8

 Both cases are described in David A. Harris, “Driving While Black” and All Other Traffic Offenses: The

Supreme Court and Pretextual Traffic Stops.” Journal of Criminal Law and Criminology, Vol. 87, No. 2

(1997), pp. 544-582.

9

 New Jersey v. Soto, 734 A.2d 350 (N.J. Super. Ct. Law Div. (1996)). The court therefore granted

motions to suppress evidence of criminal activity by motorists that was obtained in these stops.
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Lack of empirical information on the existence and prevalence of racial

profiling has led to calls for local law enforcement to collect data on which

motorists are stopped, and why. To support local data collection efforts,

the Bureau of Justice Assistance plans to release a Resource Guide in

spring of 2000. The guide is expected to focus on how data can be

collected to monitor for bias in traffic stops, with specific “lessons

learned” and implementation guidance from communities that have begun

the data collection process.

Our objectives were to provide information on (1) analyses that have been

conducted on racial profiling of motorists by law enforcement; and (2)

federal, state, and local data currently available, or expected to be

available soon, on motorist stops.

To obtain information on analyses that have been conducted on racial

profiling of motorists, we did a search of on-line databases and reviewed

all of the quantitative analyses that we identified that attempted to address

whether law enforcement officers stop motorists on the basis of race. We

also contacted the authors of the analyses and obtained references to any

other analysis or research sources they considered to be pertinent. Our

criterion for selecting analyses to be included in this report was that they

provide quantitative information on motorist stops, although these

analyses might have also measured searches, arrests, and/or other

activities. We used social science research principles to assess the

methodological adequacy of the available analyses and to discuss factors

that should be considered in collecting stronger empirical data. Our review

is not intended to constitute a statement regarding the legal standard for

proving discrimination in this context.

To obtain information on the federal government’s efforts to collect data

on racial profiling of motorists, we reviewed published and electronic

literature and discussed data sources with officials at the Justice

Department’s Bureau of Justice Statistics (BJS), officials in the office of

the Attorney General, academic experts, the American Civil Liberties

Union (ACLU), and several police associations.

To obtain information on states’ efforts to collect data on racial profiling of

motorists, we conducted Internet searches and reviewed the literature. We

also held discussions with academic experts, state officials, ACLU

officials, and representatives of the National Conference of State

Legislatures.

Scope and

Methodology
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To obtain information on local efforts to collect data on racial profiling of

motorists, we reviewed the literature and held discussions with academic

experts, interest groups, local police officials, and knowledgeable federal

officials. On the basis of these discussions, we judgmentally selected

several communities that had voluntarily decided to require their police

departments to collect motorist stop data. In September 1999, we visited

four police departments in California—in San Diego, San Jose, Alameda,

and Piedmont. We selected these police departments because they

appeared to be furthest along in their plans for collecting data, could

provide examples of different data collection methods, and varied greatly

in size.

We performed this work from August through February 2000 in

accordance with generally accepted government auditing standards.

We found no comprehensive, nationwide source of information on

motorist stops to support an analysis of whether race has been a key factor

in law enforcement agencies’ traffic stop practices. We identified five

quantitative analyses on racial profiling that included data on motorist

stops. The quantity and quality of information that these analyses provided

varied, and the findings are inconclusive for determining whether racial

profiling occurred. Although inconclusive, the cumulative results of the

analyses indicate that in relation to the populations to which they were

compared, African Americans in particular, and minorities in general, may

have been more likely to be stopped on the roadways studied.

A key limitation of the available analyses is that they did not fully examine

whether the rates and/or severity of traffic violations committed by

different groups may have put them at different levels of risk for being

stopped. Such data would help determine whether minority motorists are

stopped at the same level that they commit traffic law violations that are

likely to prompt stops. Most analyses either compared the proportion of

minorities among stopped motorists to their proportion in a different

population (e.g., the U.S. population, the driving age population of a state)

or did not use a benchmark comparison at all. There appears to be little

comparative research on traffic violations committed by different racial

groups, including possible differences in the type or seriousness of traffic

violations. Therefore, there are no firm data indicating either that the types

and seriousness of driving violations committed by whites and minorities

are comparable, nor that they are not.10 Although we have no reason to

 10 In 1997, the National Highway Traffic Safety Administration (NHTSA) conducted a large-scale

nationally representative telephone survey of drivers 16 and older to learn about the public’s

experiences and beliefs concerning speeding, and unsafe driving. Among other questions in a lengthy

Few Studies of Racial

Profiling
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expect that such differences exist, collecting research data on this issue—

though difficult to do—could help eliminate this as a possible explanation

for racial disparities in the stopping of motorists.

The studies with the best research design collected data on the population

of travelers on sections of interstate highways and on the portion of those

travelers who violated at least one traffic law. The studies compared the

racial composition of these groups against that of motorists who were

stopped. However, the studies made no distinction between the

seriousness of different traffic violations. Although violating any traffic law

makes a driver eligible to be stopped, it is not clear that all violations are

equally likely to prompt a stop.

None of the available research provided information on which traffic

violations, if any, were more likely to prompt a stop. We recognize that it is

difficult to determine which traffic violations specifically prompt a law

enforcement officer to stop one motorist rather than another. Different

jurisdictions and officers may use different criteria, and candid

information on the criteria may be difficult to obtain. Pursuing such

information would be worthwhile, however, as would analyses that

considered the seriousness of the traffic violation. Below, we summarize

the reported results and our judgment of the key limitations of each

analysis. More detail on each analysis is provided in appendix I.

• An analysis by Lamberth of motorists traveling along a segment of the New

Jersey Turnpike11 found the following: (1) 14 percent of the cars traveling

the roadway had an African American driver or other occupant; (2) 15

percent of cars exceeding the speed limit by at least 6 miles per hour had

an African American driver or other occupant; (3) of stops where race was

noted by police, 44 percent of the individuals in one section of the roadway

and 35 percent of the individuals in this section and a larger section

combined were African American.12 Lamberth also reported that 98 percent

of all drivers violated the speed limit by at least 6 miles per hour. This

 interview, respondents were asked whether they had committed a series of specific unsafe actions

while driving. Demographic data, including race and ethnicity, were obtained on each respondent.

Although answers to the unsafe or aggressive driving behavior questions were analyzed by some

demographic characteristics, no analyses by race or ethnicity of driver were conducted. National

Survey of Speeding and Other Unsafe Driving Actions, U.S. Department of Transportation, National

Highway Traffic Safety Administration, September 15, 1998.

11 Lamberth, J.L. (1994, unpublished). Revised Statistical Analysis of the Incidence of Police Stops and

Arrests of Black Drivers/Travelers On the New Jersey Turnpike Between Exits Or Interchanges 1 and 3

From the Years 1988 Through 1991.

12 The race of the driver was not available in two-thirds of the cases.
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study is notable in that it attempted to determine the percentage and

characteristics of drivers who put themselves at risk for being stopped.

However, we are uncertain whether traveling over the speed limit by at

least 6 miles per hour on a major highway is the violation for which most

police stops occurred.

• In a similar analysis of motorists traveling along a segment of Interstate 95

in northeastern Maryland,13 Lamberth found the following: (1) 17 percent

of the cars had an African American driver; (2) 18 percent of cars

exceeding the speed limit by at least 1 mile per hour or violating another

traffic law14 had an African American driver; (3) 29 percent of the motorists

stopped by the Maryland State Police were African American. This study

also found that 92 percent of all motorists were violating the speeding law,

2 percent were violating another traffic law, and 7 percent were not

violating any traffic law.15 However, we are uncertain whether Lamberth’s

criteria for traffic violations were the basis for which most police stops

were made.

• Another analysis examined motorist stops in Florida. Using data that were

first presented in 1992 in two Florida newspaper articles, Harris16 reported

that more than 70 percent of almost 1,100 motorists stopped over a 3-year

period in the late 1980s along a segment of Interstate 95 in Volusia County,

FL, were African American or Hispanic. In comparison, African Americans

made up 12 percent of Florida’s driving age population and 15 percent of

Florida drivers convicted of traffic offenses in 1991. Harris also reported

that African Americans and Hispanics made up 12 percent and 9 percent,

respectively, of the U.S. population.

The findings reported by Harris were based on videotapes of almost 1,100

motorist stops made by Volusia County Sheriff deputies. However,

videotapes of stops were not made for much of the 3-year period, and

sometimes deputies taped over previous stops. Because no information

was provided on other motorist stops made by the deputies over the 3-year

 

13 Report of John Lamberth, Ph.D. from ACLU Freedom Network,

http://www.aclu.org/court/Lamberth.html

14 Lamberth told us that his study noted four other types of traffic violations in addition to speeding.

The other violations consisted of no signal for a lane change, unsafe lane change, weaving, and

tailgating.

15 Does not sum to 100 percent due to rounding.

16 David A. Harris, “Driving While Black and All Other Traffic Offenses: The Supreme Court and

Pretextual Traffic Stops.” The Journal of Criminal Law and Criminology, Vol. 87, No. 2 (1997), pp. 544-

582.
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period, we do not know whether the videotaped stops were representative

of all stops made during that period. In addition, no information was

provided on drivers who put themselves at risk for being stopped.

• The Philadelphia ACLU reported that motorists stopped by Philadelphia

police in selected districts during 2 weeks in 1997 were more likely to be

minority group members than would be expected from their

representation in census data.17 Limitations of this analysis included the

use of census data as a basis for comparison and an absence of

information on drivers who put themselves at risk for being stopped. In

addition, there were substantial amounts of missing data. The race of the

driver was not recorded for about half of the approximately 1,500 police

stops made during the 2 weeks.

• The New Jersey Attorney General’s Office reported that African Americans

and Hispanics, respectively, represented 27 percent and 7 percent of the

motorists stopped by New Jersey State Police on the New Jersey

Turnpike.18 Interpreting these results is difficult because no benchmark

was provided for comparison purposes.

Because of the limited number of analyses and their methodological

limitations, we believe the available data do not enable firm conclusions to

be made from a social science perspective about racial profiling. For

example, we question the validity of comparing the racial composition of a

group of stopped motorists on a given roadway in a given location with the

racial composition of a population that may be vastly different. It would be

more valid to compare the racial characteristics of stopped motorists with

those of the traveling population who violated similar traffic laws but were

not stopped. This is what Lamberth did, although we are not certain that

the traffic violations committed by the motorists observed in his studies

were the same as those that prompted police stops. Nonetheless,

Lamberth’s analyses went furthest by attempting to determine the racial

composition of motorists at risk of being stopped by police as a function of

traveling on the same roadways and violating traffic laws. We believe that

the state of knowledge about racial profiling would be greater if

Lamberth’s well-designed research were augmented with additional

studies looking at the racial characteristics of persons who commit the

types of violations that may result in stops.

 

17 Plaintiffs’ Fourth Monitoring Report: Pedestrian and Car Stop Audit, Philadelphia Office of the

American Civil Liberties Union, July 1998.

18 Interim Report of the State Police Review Team Regarding Allegations of Racial Profiling, New Jersey

Attorney General’s Office, April 20, 1999.
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Other significant limitations of the available analyses were that the results

of some analyses may have been skewed by missing data and may not have

been representative of roadways and locations other than those reviewed.

These limitations notwithstanding, we believe that in order to account for

the disproportion in the reported levels at which minorities and whites are

stopped on the roadways, (1) police officers would have to be substantially

more likely to record the race of a driver during motorist stops if the driver

was a minority than if the driver was white, and (2) the rate and/or severity

of traffic violations committed by minorities would have to be

substantially greater than those committed by whites. We have no reason

to expect that either of these circumstances is the case.

Appendix II contains a discussion of some of the methodological

considerations and information needs involved in getting stronger original

data from empirical research on the racial profiling of motorists. These

include the need for high-quality data from multiple sources, such as from

law enforcement records, surveys of motorists and police, and empirical

research studies. By high quality, we mean data that are complete,

accurate, and consistent and that provide specific information on the

characteristics of the stop and the individuals involved in the stop in

comparison to those who are not stopped. The accumulation of these data

would form a better foundation for assessing whether, and to what extent,

racial profiling exists on the roadways.

Although the federal government has a limited role in making motorist

stops, several federal activities currently planned or under way represent

the first efforts to collect national level information. The Police Public

Contact Survey conducted by BJS will include information on the

characteristics of individuals reporting they were subject to traffic stops

and other information about the stop. BJS is also conducting surveys of

state and local law enforcement agencies to determine what motorist stop

data they maintain. In addition, to help determine whether federal law

enforcement agencies engage in racial profiling, three federal departments

are under a presidential directive to collect information on the race,

ethnicity, and gender of individuals whom they stop or search.19

 

19 Bills to provide for the collection of data on traffic stops were introduced in the House and Senate on

April 15, 1999. These bills, H.R. 1443 and S. 821, called for the Justice Department to study racial

profiling by acquiring data on motorist stops from law enforcement agencies. Neither bill had passed as

of March 1, 2000.

Federal Efforts to

Collect Data on

Motorist Stops
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A national household survey now under way asks respondents to discuss

their contacts with police during motorist stops. As part of BJS’ 1999

Police Public Contact Survey, BJS is conducting interviews with 90,000

people aged 16 or older to ask them up to 36 questions pertaining to the

most recent occasion (if any) during the prior 12 months that their motor

vehicles were stopped by police officers. For example, the interview

questions ask for information on the race of the motorist and police

officer, the reason for the stop, whether a search was conducted, and

whether the officer asked what the person was doing in that area. (See

app. III for the survey questions to be asked.) BJS completed the survey in

December 1999, and expects the results to be available in September 2000.

BJS is conducting two surveys in an effort to determine whether law

enforcement agencies collect stop data that can be used to address the

question of racial profiling. One survey targets state police agencies; the

other survey targets both state and local law enforcement agencies.

In April 1999, BJS administered a survey of all state police agencies in the

nation. The Survey of State Police Agencies asked, in general, whether the

agency required its officers to report demographic information on the

driver or other occupants of every vehicle stopped for a routine traffic

violation. If the agency reported that it did collect such information, then

more detailed questions were to be answered, such as whether individual

records were kept detailing the driver’s race and immigration status and

whether a search was conducted. BJS issued the results of the state police

survey in February 2000. BJS found that 3 of the nation’s 49 state law

enforcement agencies whose primary duties included highway patrol

reported that they required officers to collect racial/ethnic data for all

traffic stops. Of the three states, Nebraska and New Mexico reported

storing the racial/ethnic data electronically, and New Jersey reported that

it did not store the data electronically.

BJS administers the Law Enforcement Management and Administrative

Statistics (LEMAS) survey to a sample of state and local law enforcement

agencies every 3 to 4 years. The survey collects information on the budget,

salaries, and administrative practices of the agencies. The 1999 survey

included a single question asking if the agencies collected data on traffic

stops. The survey was sent to a sample of about 3,000 police/sheriff

departments and was to include all agencies with 100 or more employees.

The 1999 survey results are expected to be available during the summer of

2000. According to a BJS official, the 2000 LEMAS survey will contain

more questions about what records are kept on motorist stops and

whether they contain information on race.

Population Survey of

Motorist Contacts With Law

Enforcement

Surveys of Motorist Stop

Data Collected by Law

Enforcement Agencies
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Pursuant to a presidential directive, three federal departments are to

collect data on contacts between their law enforcement officers and the

public. The directive did not instruct the departments to focus solely on

motorist stops, but data on motorist stops are to be included.

In June 1999, the President issued a memorandum on fairness in law

enforcement that addressed the issue of racial profiling. The memorandum

directed the Departments of Justice, the Interior, and the Treasury to

design and implement a system for collecting and reporting statistics on

the race, ethnicity, and gender of individuals who are stopped or searched

by law enforcement. The three departments were tasked with developing

data collection plans within 120 days and implementing field tests within

60 days of finalizing the plans. After 1 year of field testing, the departments

are to report on complaints received that allege bias in law enforcement

activities, the process for investigating and resolving complaints, and their

outcome. The memorandum also required a report to the President within

120 days of the directive concerning each department’s training programs,

policies, and practices regarding the use of race, ethnicity, and gender in

law enforcement activities, as well as recommendations for improvement.

The departments submitted data collection plans and proposed locations

for the field tests to the White House in October 1999. (See app. IV for the

list of data elements to be collected and all federal data collection test

sites.) Federal law enforcement offices and proposed locations likely to be

involved in motorist stops included the following:

• INS inspectors at the land border crossing at Del Rio, TX;

• INS border patrol agents from San Diego, CA; Yuma, AZ; and El Paso, TX;

• National Park Service officers at eight national parks; and

• National Park Service officers on three federally maintained memorial

highways.

According to Department of Justice plans, officials will also pursue a

variety of techniques at some sites to try to determine if the characteristics

of those stopped differed from populations encountered at the field site in

general.

Data Collection on Motorist

Contacts With Federal Law

Enforcement
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Most traffic stops are made by state and local law enforcement officers.

Consequently, state and local agencies are in the best position to collect

law enforcement data on the characteristics of stopped motorists. Several

states have introduced legislation that would require their state and/or

local police departments to collect data on motorists’ traffic stops.

However, few bills have passed.

As of October 15, 1999, at least 15 states had taken some action to address

concerns about racial profiling of motorists. Two of the 15 states—North

Carolina and Connecticut—enacted legislation requiring the collection and

compilation of data on motorist traffic stops. Similar legislation requiring

the collection of specific stop data was introduced in 11 states. The

legislation was pending in 7 of those 11 states and was either not carried

over to the next legislative session or vetoed in 4. The two remaining

states, New Jersey and Virginia, issued resolutions. New Jersey’s

resolution calls for the investigation of racial profiling, and Virginia’s

resolutions call for data on traffic stops to be compiled and analyzed. See

table 1 for a list of the states that had proposed or enacted traffic stop bills

or resolutions and their status as of October 15, 1999.

All 13 states with data collection legislation proposed to collect data on

driver’s race or ethnicity, the alleged traffic violation that resulted in a

motorist stop, and whether an arrest was made. Most of these states also

proposed to collect data on age, on whether a search was conducted, and

on whether an oral warning or citation was issued. The number of data

elements that each state proposed to collect ranged from 6 to 16. For a list

of data elements that each of the 13 states proposed to collect, see

appendix V.

North Carolina passed legislation in April 1999 that called for the

collection of statistics on a variety of law enforcement actions. Part of the

legislation detailed what information on routine traffic stops by state law

enforcement officers should be collected, maintained, and analyzed. All of

the state’s approximately 40 state law enforcement agencies are to collect

the data, although about 90 to 95 percent of all traffic stops are made by

the North Carolina State Highway Patrol.

Connecticut’s legislation passed in June 1999 and requires collection of

certain traffic stop data on stops made by state as well as local police

departments. In addition, Connecticut’s legislation bans the practice of

racial profiling and calls for the collection of data on complaints that were

generated as a result of law enforcement officer actions at traffic stops.

North Carolina and Connecticut were both in the process of developing

Several States

Proposed Traffic Stop

Data Collection

Legislation, but Few

Bills Passed
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specifications for data collection. They planned to begin data collection

January 1, 2000.

State Bill number Date introduced Bill status

Arkansas HB 1261 January 1999 Referred to committee;

session adjourned, no

carryover

California SB 78 December 1998 Vetoed by Governor 9/99

Connecticut Sub. SB 1282 March 1999 Bill became law 6/99 –

Public Act No. 99-198

Florida HB 177 September 1999 Pending – referred to

committee 10/99

Illinois HB 1503 February 1999 Pending – referred to

committee 3/99

Maryland SB 430 February 1999 Passed House; session

adjourned; no carryover,

Massachusetts SB 1854 June 1999 Pending – referred to

committee 6/99

New Jersey Concurrent

Resolution No. 162

March 1999 Pending – referred to

Committee 3/99

North Carolina SB 76 February 1999 Bill became law 4/99 –

Session Law 1999-26

Ohio HB 363 May 99 Pending – referred to

Committee 5/99

Oklahoma SB 590 February 1999 Referred to Committee;

no carryover

Pennsylvania HB 873 March 1999 Pending – referred to

Committee 3/99

Rhode Island SB 131 January 1999 Pending – referred out of

Committee, 5/99

South Carolina SB 778 April 1999 Pending – Referred to

Committee; session

adjourned; bill carried

over

Virginia Joint Resolutions

736 and 687

Both January 1999 Both referred to

committee; session

adjourned; no carryover

Sources: Professor David Harris, University of Toledo College of Law; National Conference of State

Legislators; Internet search of state legislatures; WESTLAW database.

We visited four California police departments—San Diego, San Jose,

Alameda, and Piedmont—to learn about local efforts to collect traffic stop

data. These departments had either begun or planned to begin to

voluntarily collect traffic stop data. Some officials told us that their

departments were interested in collecting traffic stop data because they

wanted to address community concerns about racial profiling. San Jose

began collecting data in June 1999, Alameda and Piedmont began

Table 1: Status of Traffic Stop Bills

Introduced in State Legislatures

Local Initiatives to

Collect Motorist Stop

Data
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collecting data in October 1999, and San Diego began collecting data

January 2000.

The departments generally planned to collect similar data; however, their

data collection methods and plans for analyzing the data differed. All four

police departments planned to collect data on five data elements: race or

ethnicity, age, and gender of the driver; the reason for the traffic stop; and

whether the stop resulted in a warning or citation or an arrest. In addition,

Alameda, Piedmont, and San Diego planned to collect data on searches

conducted during traffic stops. San Diego planned to collect six additional

pieces of information. Table 2 summarizes the data that the four police

departments will collect.

Data element San Diego San Jose Alameda Piedmont

Driver’s race or

ethnicity

X X X X

Age X X X X

Gender X X X X

Reason for stop X X X X

Location of stop X

Search conducted X X X

Legal basis of search X

Obtain consent

search form

X

Result of stop/stop

disposition (e.g. oral

warning or citation

Issued, arrest made)

X X X X

Property seized X

Contraband found X

Officer on special

assignment

X

Total number of data

elements to be

collected

11 5 7 6

Source: GAO summary of police department information.

In San Jose, officers use their police radios to report traffic stop

information to the dispatcher, who then enters the data into a computer

system. Officers can also use mobile computers located in their patrol cars

to report traffic stop information, and this can be transmitted directly to

the computer system. In San Diego, officers initially are collecting vehicle

stop data using manually completed forms, and plan later to use a wireless

system to transmit information to the department’s database. The Alameda

police department also planned to use its computer-assisted dispatch

system to collect data, but only on stops where citations are not issued,

Table 2: Traffic Stop Data Elements

Collected by Four California Police

Departments
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such as stops resulting in warnings or arrests. For stops in which the

motorist receives a citation, traffic stop data are to be abstracted from

patrol officers’ ticket books and from motor officers’ hand-held computer

printouts and input into a citations database. Police officials in Piedmont, a

police department consisting of 21 officers, decided that manually

recording traffic stop information on paper forms would work best for its

small department.

Three of the four departments indicated that they expect to analyze their

traffic stop data. A preliminary report, issued in December 1999 and

providing analysis results on data collected between July and September

1999 in San Jose, indicated some racial disparity in traffic stops.20

According to the San Jose Police Department, the differences were due to

socioeconomic factors rather than ethnicity. The report noted that more

police were assigned to areas of San Jose that generated more police calls,

and those neighborhoods tended to have more minorities. Because more

police were available in these areas to make traffic stops, more stops were

made there than in districts with a lower police presence. Within each

police district, the stops reportedly reflected the demographics of the

district. In the report, the San Jose Police Chief emphasized that more data

were needed, along with the cooperation of the community to analyze

what the data mean. Alameda officials told us they had no current plans to

analyze their data, but the data will be available should there be a public

request. None of the four departments planned to independently validate

the accuracy of the data provided by the police officers. They said they

rely on the integrity of the officers and supervisory oversight to ensure that

the data are correct.

Officials from two of the departments reported that the amount of data to

be collected was limited so as not to be burdensome for officers. However,

a lack of information may limit the types of analyses possible. For

example, the data collection efforts do not require data on the specific

violation for which a motorist was stopped, so questions about whether

minorities were stopped more often for less serious violations cannot be

answered. None of four localities planned to collect this information.

Officials noted, however, that trade-offs needed to be considered: police

officers would be more likely to record motorist data if the data collection

requirements imposed on them were not overly detailed or burdensome.

 

20 Vehicle Stop Demographic Study, San Jose, California Police Department, December 17, 1999. For

each group, the percent of San Jose residents and the percent of motorist stops reported were as

follows: Hispanics were 31 percent of residents and 43 percent of stops; African Americans were 4.5

percent of residents and 7 percent of stops; whites were 43 percent of residents and 29 percent of

stops; and Asian Americans were 21 percent of residents and 16 percent of stops.
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For a more detailed discussion on each of the four police departments’

traffic stop data collection plans, see appendix VI.

The five quantitative examinations of racial profiling that we identified did

not produce conclusive findings concerning whether and to what extent

racial profiling exists. Although methodologically limited, their cumulative

results indicate that in relation to the populations to which they were

compared, African Americans in particular, and minorities in general, may

have been more likely than whites to be stopped on the roadways studied.

Because of methodological weaknesses in the existing analyses, we cannot

determine whether the rate at which African Americans or other minorities

are stopped is disproportionate to the rate at which they commit violations

that put them at risk of being stopped. Although definitive studies may not

be possible, we believe that more and better research data on the racial

characteristics of persons who commit the types of violations that may

result in stops could be collected.

To date, little empirical information exists at the federal, state, or local

levels to provide a clear picture of the existence and/or prevalence of

racial profiling. Data collection efforts that are currently planned or under

way should provide more data in the next few years to help shed light on

the issue. These efforts are steps in the right direction. However, it remains

to be seen whether these efforts will produce the type and quality of

information needed for answering questions about racial profiling.

We requested comments on a draft of this report from the Justice

Department. Based on a January 18 meeting with a Deputy Associate

Attorney General and other Justice officials, and technical comments

provided by Justice, we made changes to the text as appropriate. In

addition, Justice’s Acting Assistant Attorney General for Civil Rights

provided us with written comments, which are printed in full in appendix

VII. Justice agreed with us that there is a paucity of available data for

assessing whether and to what extent racial profiling of motorists may

exist. Justice also agreed that current data collection efforts by law

enforcement agencies, as well as additional research studies, could

generate information that may help answer questions about racial

profiling. Justice felt, however, that our report set too high a standard for

proving that law enforcement officers discriminate against minority

motorists.

We believe that Justice’s letter mischaracterized the conclusion of our

report. Justice states that it disagrees with the “draft report’s conclusion

that the only ‘conclusive empirical data indicating’ the presence of racial

Conclusions

Agency Comments and

Our Evaluation
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profiling would be data that proved the use of race to a scientific

certainty.” Our conclusion, however, was that the “available research is

currently limited to five quantitative analyses that contain methodological

limitations; they have not provided conclusive empirical data from a social

science standpoint to determine the extent to which racial profiling may

occur” (page 1). We also noted that to account for the disproportion in the

reported levels at which minorities and whites are stopped on roadways,

(1) police officers would have to be substantially more likely to record the

race of a driver during motorist stops if the driver was a minority than if

the driver was white, and (2) the rate and/or severity of traffic violations

committed by minorities would have to be substantially greater than those

committed by whites. We do not believe that our approach to reviewing

the research studies was so rigorous that we required “scientific certainty”

in the data to draw conclusions about the occurrence of racial profiling.

And we make clear in the report that our review was not intended to

comment on the legal standard for proving discrimination in this context

(see our Scope and Methodology section).

With respect to Justice’s suggestion that we required research studies to

provide scientific certainty of racial profiling, we would note that the

concept of scientific certainty is generally not applicable to social science

research. This is because social science research data are generally

imperfect because they are collected in the “real world” rather than under

controlled laboratory conditions. A fundamental, universally accepted,

social science research principle that we did incorporate into our

assessment of study results was whether the studies ruled out plausible

alternative explanations for findings. We found that the available research

on the racial profiling of motorists did not sufficiently rule out factors

other than race—that is, other factors that may place motorists at risk of

being stopped— that may have accounted for differences in stops. We

observed that the two studies by Professor Lamberth were well-designed

and went further than others in attempting to determine whether race was

related to traffic violations that increased the risk of being stopped. But

Lamberth established a criterion in each study that cast the net so wide

that virtually the entire population of motorists was eligible to be stopped

(i.e., traveling at least 1 and 6 miles above the speed limit, respectively, on

two major interstate highways), and his studies provided little information

about why motorists actually were stopped. Although law enforcement

officers can use their discretion in deciding whom to stop, more

information is needed on the actual reasons why they stop motorists

before a firm conclusion can be made that the reason was race. As we

indicate in the report, current data collection efforts by local, state, and
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federal law enforcement agencies may provide information on the reasons

for stops that may help answer this question.

With respect to what kind of data would be needed to “prove” the use of

race in motorist stops, this issue was outside the scope of our work. We

recognize that the evidentiary standards that a court may apply in ruling on

an allegation of race-based selective enforcement of the law may be

different from the social science principles that we used to review these

studies. It was not our intention to express or imply anything about legal

standards to prove discrimination.

Justice also criticized our work for failing “to recognize or comment on the

extensive scholarly debate on the subjects of the degree of statistical

certainty, and the extent to which potential variables must be examined in

order to demonstrate discrimination from a social science perspective.”

We did not comment on the matter of statistical certainty because it was

not the basis for our determination that the available research on racial

profiling is inconclusive. The problems that we identified with the research

studies dealt primarily with the design of the studies; that is, using

inappropriate or questionable benchmarks to isolate race from other

factors. More and better data are needed on what traffic violations trigger

stops and whether race is related to them.

Justice agrees that it is important to use an appropriate benchmark against

which to compare the racial composition of stopped motorists. Justice

disagrees, however, about the importance of examining whether certain

driving behaviors or characteristics of vehicles may affect the likelihood of

being stopped. In this context, Justice suggests that we make the

unwarranted assumption in our report that severe traffic violations

account for such a large proportion of traffic stops that they have a

significant effect on the data. We did not intend, nor do we believe, that the

report makes any assumptions about the reasons for which motorists are

stopped. We simply believe that if the objective is to determine whether

minority motorists are disproportionately more likely to be stopped than

whites, then it is important to know what portion of the driving population

on that roadway or in that jurisdiction commits the traffic offenses for

which motorists are actually stopped—as opposed to being eligible to be

stopped. This is the type of benchmark information that would isolate, to

the extent possible, race from other variables that could influence traffic

stops.
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As arranged with your office, unless you publicly announce the contents of

this letter earlier, we plan no further distribution until 15 days after the

date of this report. At that time, we will send a copy to other appropriate

congressional parties, the Honorable Janet Reno, the Attorney General,

and to others upon request. If you or your staff have any questions

concerning this report, please contact me or Evi L. Rezmovic, Assistant

Director, on 202-512-8777. Other key contributors to this report are listed

in appendix VIII.

Sincerely yours,

Laurie E. Ekstrand

Director, Administration of Justice Issues

General Government Division
Page 22 GAO/GGD-00-41 Racial Profiling

Contents

1 Letter

24

A Summary of Analysis Design, Results, and Limitations 24 Appendix I

Studies of Racial

Characteristics of

Drivers Stopped by

Police

Appendix II 34

Methodological Issues

In Studying Racial

Profiling of Motorists

Appendix III 37

Bureau of Justice

Statistics Police Public

Contact Survey

44

Presidential Directive 44 Appendix IV

Federal Law

Enforcement Data

Collection

Appendix V 48

State Legislation and

Proposed State

Legislation to Collect

Traffic Stop Data:

Elements to be

Collected
Contents

Page 23 GAO/GGD-00-41 Racial Profiling

50

San Diego Police Department 50

San Jose Police Department 50

Alameda Police Department 52

Piedmont Police Department 52

Appendix VI

Four Localities Data

Collection Plans

Appendix VII 54

Comments From U.S.

Department of Justice

Appendix VIII 58

GAO Contacts and

Staff

Acknowledgments

Table 1: Status of Traffic Stop Bills Introduced in State

Legislatures

15

Table 2: Traffic Stop Data Elements Collected by Four

California Police Departments

16

Tables

Abbreviations

ACLU American Civil Liberties Union

BJS Bureau of Justice Statistics

DEA Drug Enforcement Administration

III Interstate Identification Index

INS Immigration and Naturalization Service

LEMAS Law Enforcement Management and Administrative Statistics

MSP Maryland State Police

NJSP New Jersey State Police
Appendix I

Studies of Racial Characteristics of Drivers

Stopped by Police

Page 24 GAO/GGD-00-41 Racial Profiling

As part of our work, we reviewed all available quantitative analyses that

we could identify pertaining to the use of race as a factor in motorist stops.

This appendix provides a summary of the design, results, and limitations

for each of the five analyses.

Lamberth, J.L (1994, unpublished). Revised Statistical Analysis of the

Incidence of Police Stops and Arrests of Black Drivers/ Travelers on the

New Jersey Turnpike Between Exits or Interchanges 1 and 3 From 1988

Through 1991.

This analysis, done as part of a research study for a court case, provided a

comparison of the races of vehicle occupants who were involved in traffic

stops and arrests, drivers who violated traffic laws, and motorists in

general who traveled along a segment of the southern end of the New

Jersey Turnpike. The study involved three types of data collection: (1)

direct observation of motorists from fixed observation points along the

side of the road; (2) a moving survey in which an observer drove on the

roadway and noted the races of drivers and whether they were speeding;

and (3) obtaining law enforcement records from the New Jersey State

Police (NJSP).

In the first data collection effort, observers were stationed beside the road.

Using binoculars, they noted the number of cars that passed the

observation point, the race of the driver and/or any other occupant, and

the vehicle’s state of registration. One observer was assigned to each lane

of traffic, and a data recorder was present to record their observations.

Observations were made in 18 randomly selected 3-hour blocks of time at

4 locations between 8 a.m. and 8 p.m. over a 2-week period in June 1993.

The author noted that “most if not all” of the 26 pending cases in

Gloucester County Superior court arose between these hours. Observers

were reported to have been between 14 and 45 feet from the roadway.

According to the observations, 42,706 cars were counted as traveling on

the turnpike, and the race(s) of the occupants were recorded for nearly

100 percent. An African American driver and/or other occupant were in 14

percent of the cars. Seventy-six percent of the cars were registered out of

state.

In the second data collection effort, a moving survey was conducted to

identify the racial distribution of all drivers on the road who violated the

speed limit. In this phase, one observer drove at a constant 60 miles per

hour (5 miles per hour above the speed limit at the time), and he recorded

onto a tape recorder the race of each driver who passed him and whom he

A Summary of Analysis

Design, Results, and

Limitations

Source

Study Design/Results
Appendix I

Studies of Racial Characteristics of Drivers Stopped by Police

Page 25 GAO/GGD-00-41 Racial Profiling

passed. The observer noted all cars that passed him as violators and all

cars that he passed as nonviolators.

In the moving survey, 1,768 cars were counted. More than 98 percent were

speeding and classified as “violators.” Fifteen percent of the cars observed

speeding had an African American driver or other occupant.

A third data collection effort involved gathering data from NJSP. The data

included the race of drivers who were stopped or arrested on randomly

selected days between April 1988 and May 1991 along the section of the

Turnpike covered by the traffic surveys and an additional section of the

roadway. These data included 1,128 arrest reports from turnpike stops;

2,974 stops from patrol activity logs from 35 randomly selected days; and

police radio logs from 25 of the selected days. (The 1988 radio logs had

been destroyed.) Of the 2,974 stops, 870 were from the section covered by

the traffic surveys. Data were not provided on the number of arrests from

this section.

Of 1,128 NJSP reports, the race of the driver/occupants was noted in 1,059

of them. According to these 1,059 reports, 73 percent of those arrested

were African American. The patrol logs and radio logs noted 2,974 events

as “stops.” Of the 2,974 stops, all but 78 noted the state of the registration

of the car. Twenty-three percent of the stops were of New Jersey cars.

Lamberth noted that race was “rarely if ever” noted on the patrol activity

logs and that in the radio logs, race appears about one-third of the time for

the records that had not been destroyed. (Out of 2,974 stops, race was not

noted in 2,041, or 69 percent of the stops. Of the 870 stops that were in the

sections covered by the traffic surveys, race was not recorded in 649, or 75

percent of them.) According to the available race data on all stops, 35

percent of drivers stopped were African American; 29 percent of all raceidentified stops involved out-of-state African Americans; and 6 percent of

the same stops involved in-state African Americans. Of the 221 raceidentified stops from the section covered by the traffic surveys, 44 percent

of the drivers were African American.

In a separate analysis, Lamberth examined the race of individuals who

were ticketed by three different units of the Moorestown, New Jersey State

Police barracks.1

 He compared the proportion of tickets issued to African

Americans by the (1) Radar Unit, which used a remote van and left no

 

1

 The analysis was not included in Lamberth’s unpublished report but was cited in the judge’s decision

in the related court case (New Jersey v. Soto, 734 A.2d 350 (N.J. Super. Ct. Law Div. (1996)).
Appendix I

Studies of Racial Characteristics of Drivers Stopped by Police

Page 26 GAO/GGD-00-41 Racial Profiling

discretion in the hands of patrol officers; (2) Tactical Patrol Unit, which

concentrated on traffic problems at specific locations on the roadway and

exercised more discretion on whom to stop than the Radar Unit; and (3)

Patrol Unit, which was responsible for general law enforcement and

exercised the most discretion among the three units. Lamberth found that

African Americans received 18 percent of the tickets issued by the Radar

Unit, about 24 percent of the tickets issued by the Tactical Patrol Unit, and

about 34 percent of the tickets issued by the Patrol Unit. These results

suggested that increasing levels of trooper discretion translated into

increasing percentages of African American stops.

Although the data suggest that African Americans may have been

disproportionately represented among motorists stopped and arrested,

because of several limitations in the study’s methodology, this study does

not provide clear evidence of racial profiling of African American drivers.

First, the percentage of drivers violating traffic laws was measured by

determining the percentage of drivers who were driving at least 6 miles per

hour over the posted speed limit. The study did not attempt to distinguish

motorists who were driving 6 miles per hour over the speed limit from

those who were speeding more excessively. On the basis of the criterion

used to indicate speeding violation, the report concluded that 98 percent of

the cars were violating at least one traffic law. We are uncertain whether

this is an adequate indication of the type or seriousness of traffic violations

that put motorists at risk for being stopped by police. We also do not know

the reasons for which motorists were stopped.

Second, the traffic surveys and the data on police stops and arrests were

not from comparable time periods. The police data were from about 2 to 5

years prior to when the traffic surveys were conducted—the traffic

surveys were done in June 1993, and the police data were from randomly

selected days from April 1988 to May 1991.

Third, the observed differences in the percentage of African Americans

ticketed by Radar, Tactical Patrol, and general Patrol units may or may not

have been due to discriminatory practices on the part of law enforcement

officers. For the Tactical and general Patrol units, we do not know the

reasons why tickets were issued, nor do we know if different groups may

have been at different levels of risk for being stopped because they

differed in their rates and/or severity of committing traffic violations.

Limitations
Appendix I

Studies of Racial Characteristics of Drivers Stopped by Police

Page 27 GAO/GGD-00-41 Racial Profiling

Fourth, among stopped vehicles, the occupants’ race was not recorded for

three-fourths of cases along the portion of the highway where the traffic

surveys were conducted; race was not recorded for two-thirds of cases

along a larger portion of the highway. Therefore, the race of most

motorists stopped is unknown. Statisticians performed calculations to

determine the implications of the missing data for drawing conclusions

about racial disparities in stops.2

 The calculations revealed that if the

probability of having race recorded if one was African American and

stopped was up to three times greater than if one was white and stopped,

then African Americans were stopped at higher rates than whites. Because

we do not know what factors affected officers’ decisions to record race,

the true extent to which officers tended to record race for African

Americans versus whites is unknown.

Report of John Lamberth, Ph.D. From ACLU Freedom Network, http:-

//www.aclu.org/court/Lamberth.html

This analysis, done as part of a research study for a court case, provided a

comparison between the racial distribution of motorists stopped by the

Maryland State Police (MSP) on I-95 in northeastern Maryland, motorists

whose cars were searched by MSP, all motorists on the roadway, and

motorists on the roadway who violated traffic laws. The study involved

two types of data collection: (1) a moving survey in which a team of

researchers drove on the roadway and noted the race of drivers and

whether they were speeding, and (2) obtaining law enforcement records

from the Maryland State Police.

In the first data collection effort, a moving survey was conducted to

determine the races of highway motorists and the races of highway

motorists who violated traffic laws. A team of observers drove separately

at the posted speed limit (either 55 or 65 miles per hour) and recorded the

race of each driver who passed him or her and whom he or she passed.

The observer noted all cars who passed him or her as violators and all cars

that he or she passed as nonviolators (unless they were observed violating

some other traffic law.) Twenty-one observation sessions were conducted

on randomly selected days between 8 a.m. and 8 p.m. during the period

June to July 1996.

In the moving survey, over 5,700 cars were counted. The author reported

that driver’s race was identified for 97 percent of cars. Seventeen percent

 

2

 These calculations were performed by two statisticians, and the Justice Department provided us a

report of their findings.

Source

Study Design/Results
Appendix I

Studies of Racial Characteristics of Drivers Stopped by Police

Page 28 GAO/GGD-00-41 Racial Profiling

of cars had African American drivers, and 76 percent had white drivers.

Ninety-three percent of cars were observed violating traffic laws. Eighteen

percent of the violators were African American, and 75 percent were

white.

In the second data collection effort, data on motorists traveling a segment

of I-95 were obtained from MSP. These data included information on (1)

motorist stops made between May and September 1997 in Baltimore, Cecil,

and Harford counties; (2) searches conducted between January 1995 and

September 1997; (3) searches by MSP on roadways outside this corridor;

and (4) drug arrests resulting from these searches.

The MSP data indicated that along the I-95 segment studied, 11,823 stops

were made by MSP between May and September 1997. Of the 11,823

vehicles stopped, it was reported that 29 percent had an African American

driver, 2 percent had a Hispanic driver, 64 percent had a white driver, and

5 percent had a driver of another race/ethnicity. With respect to searches,

956 motorists were searched between January 1995 and September 1997. It

was reported that 71 percent were African American, 6 percent were

Hispanic, 21 percent were white, and 2 percent had a driver of another

race/ethnicity. The proportion of searched cars in which contraband was

found was the same for whites and African Americans and the same for I95 as compared to the rest of Maryland.

In comparison, there were 1,549 motorist searches outside the I-95

segment. Of these searches, 32 percent were African American, 4 percent

were another minority, and 64 percent were white.

Although the data suggest that African Americans may have been

disproportionately represented among motorists stopped and/or searched,

because of several limitations in the study’s methodology, this study does

not provide clear evidence of racial profiling of African American drivers.

First, we are uncertain whether the study adequately measured the type or

seriousness of traffic violations that put motorists at risk for being stopped

by police. For example, motorists who greatly exceed the speed limit,

commit certain types of violations, or commit several violations

simultaneously may be more likely to be stopped than others. The measure

used to determine whether a car was speeding was whether it was

traveling at any speed over the posted limit. As with the New Jersey study

by the same researcher, this study did not attempt to distinguish between

motorists who drove 1 mile over the speed limit and those who sped more

excessively. Furthermore, this study recorded whether traffic violations

Limitations
Appendix I

Studies of Racial Characteristics of Drivers Stopped by Police

Page 29 GAO/GGD-00-41 Racial Profiling

other than speeding were committed but treated them as equal in

seriousness and equally likely to prompt a stop. This may or may not have

been a valid assumption. In addition, we do not know the reasons for

which motorists were stopped.

Second, the data on police stops and police searches were not from

comparable time periods. The data for stops were from May through

September of 1997, and the data on searches were from January 1995

through September 1997. Lamberth noted in a correspondence to us that

the stop data were not provided in time for his initial report. These

problems do not necessarily indicate a systematic bias, however.

Harris, David A.; Driving While Black and All Other Traffic Offenses:

The Supreme Court and Pretextual Traffic Stops. Published in The

Journal of Criminal Law and Criminology 87 (2): 1997.

The analysis provides quantitative data from Florida and Maryland. The

Florida data first appeared in two Florida newspaper articles in 1992. The

Maryland data were obtained by the author from lawyers involved in a

Maryland lawsuit.

The journal article compares the racial characteristics of drivers involved

in videotaped stops on a segment of I-95 in Volusia County, FL, over 3

years in the late 1980s (obtained from the County Sheriff’s Department by

the Orlando Sentinel) with population and observational data. It was

reported that videotapes of stops were not made for much of the 3-year

period and sometimes deputies taped over previous stops. More than 70

percent of the persons stopped among nearly 1,100 videotaped stops on I95 were African American or Hispanic. African Americans, however, made

up 12 percent of the driving age population in Florida, 15 percent of the

traffic offenders in Florida in 1991, and 12 percent of the U.S. population.

(Hispanics were 9 percent of the U.S. population.) Moreover, according to

the Orlando Sentinel’s observations of 1,120 vehicles on I-95, about 5

percent of the drivers were dark-skinned.

The article also noted that of the nearly 1,100 stops, 243 were made for

swerving, 128 for exceeding the speed limit by more than 10 mph, 71 for

burned-out tag lights, 46 for improper license tags, 45 for failure to signal,

and a smattering of other offenses. Roughly half of the cars stopped were

searched, 80 percent of the cars searched belonged to African American or

Hispanic drivers, and African American and Hispanic drivers were

detained for twice as long as whites. Only 9 of the 1,100 drivers stopped

received tickets.

Source

Study Design/Results
Appendix I

Studies of Racial Characteristics of Drivers Stopped by Police

Page 30 GAO/GGD-00-41 Racial Profiling

In Maryland, the only data provided in the article are the percentages of

African Americans and Hispanics among 732 motorists stopped and

searched by 12 Maryland State Police officers with drug-sniffing dogs

between January 1995 and June 1996. The article stated that 75 percent of

the persons searched were African American; and 5 percent were

Hispanic. Of the 12 officers involved, 2 stopped only African Americans.

Over 95 percent of the drivers stopped by one officer were African

American and 80 percent of the drivers stopped by six officers were

African American.

Because of several methodological limitations, this analysis does not

provide clear evidence of racial profiling of African American or Hispanic

drivers.

For the Florida data, the validity of the comparisons made is questionable.

For example, the data from the videotaped stops combined African

Americans and Hispanics, but the comparison data for the driving age

population of Florida included African Americans only. More importantly,

no information was provided on the percentage of African Americans and

Hispanics among traffic offenders. It is also not clear how accurately

information on “dark-skinned” drivers was captured. In addition, there was

an unknown amount of missing data because videotapes of stops were not

made for much of the period. Therefore, we do not know whether the

videotaped stops were representative of all stops.

For the Maryland data, no comparative data are provided on the

percentage of African Americans and Hispanics among motorists

generally, among stopped motorists, or among motorists who violated

traffic laws. The data for drivers in Maryland included only motorists who

were stopped and consented to being searched.

Plaintiffs’ Fourth Monitoring Report: Pedestrian and Car Stop Audit,

Philadelphia Office of the American Civil Liberties Union, July 1998.

This was an analysis of the racial characteristics of motorists and

pedestrians stopped by the Philadelphia Police Department in selected

districts and persons stopped by the department’s Narcotics Strike Force.

All police incident reports recording interactions between police and

civilians that involved stops and investigations of pedestrians or

automobiles in the 8th, 9th, 18th, and 25th Police Districts for the week of

October 6, 1997, were obtained. Hardcopy and computerized records were

reviewed and coded according to whether tickets or arrests resulted from

Limitations

Source

Study Design/Results
Appendix I

Studies of Racial Characteristics of Drivers Stopped by Police

Page 31 GAO/GGD-00-41 Racial Profiling

the stops and, if not, whether the record indicated any legal explanation

for the stop. Previously unreported data were also provided on pedestrian

and automobile stops in the 9th, 14th, and 18th Police Districts for the week

of March 7, 1997. All reports filed by the Narcotics Strike Force for

incidents in the 4th, 12th, 17th, 25th, and 35th Police Districts that involved a

pedestrian or a vehicle stop during August 1997 were obtained. Records

were coded in the same way as described above. Demographic data for all

Philadelphia residents from a 1995 census were provided as a benchmark

for the city as a whole, and demographic data by census tract from the

1990 U.S. census were provided as benchmarks for the district-specific

analyses. (The report mentions that Philadelphia Police Districts

approximately encompass specific census tracts.)

For the week of March 7, there were police records of 516 motorist stops

in the 3 districts. Overall, the race of the driver was recorded for only 51

percent of these stops, with race being recorded for between 40 and 58

percent of the stops in the three districts. For the week of October 6, there

were police records of 1,083 motorist stops in the 4 districts. Overall, race

of the driver was recorded for only 48 percent of these stops, with race

being recorded for between 44 and 46 percent of the stops in three of the

districts. (No separate data were provided for the 25th District, and no

explanation was given for this omission.) In both weeks in each district,

for stops with race of driver recorded, the driver was more likely to be a

member of a minority group than would be expected on the basis of racial

characteristics of the district as indicated by 1990 census tract data.

Additionally, for stops with race recorded, the report indicated that

minorities were more likely than whites to be involved in stops that were

judged as not having a legally sufficient explanation than in stops judged to

have a legally sufficient explanation for the March data, but not for the

October data.

There were records of 214 stops by the Narcotics Strike Force in August

1997. (Task Force data were not presented separately for motorists and

pedestrian stops.) However, the race of the individual stopped was

recorded for only 68 percent of the stops. For stops with race recorded,

the report indicated that minorities were more likely to be involved in

stops judged not to have a legally sufficient explanation—43 percent

African American, 39 percent Hispanic, and 18 percent white—than in

stops judged to have a legally sufficient explanation—33 percent African

American, 47 percent Hispanic, and 20 percent white.

Because of several methodological limitations, this analysis does not

provide clear evidence of discriminatory targeting of minority drivers.

Limitations
Appendix I

Studies of Racial Characteristics of Drivers Stopped by Police

Page 32 GAO/GGD-00-41 Racial Profiling

First, data on the racial characteristics of most motorists covered in the

study were not available. The absence of these data is a severe limitation

because the race of most drivers stopped is unknown.

Second, 1990 census tract data were used as benchmarks for the racial

characteristics of the residents of the selected police districts. However, as

the study notes, these census tract data were several years old at the time

the study was conducted, and it is unknown how well these 1990 census

data portrayed the 1997 population of these parts of Philadelphia. More

importantly, no information was provided on the race of drivers who put

themselves at risk for being stopped.

Interim Report of the State Police Review Team Regarding Allegations of

Racial Profiling, New Jersey Attorney General’s Office, April, 20, 1999.

The report provides the racial characteristics of drivers stopped, searched,

and arrested by the New Jersey State Police (NJSP) along the New Jersey

Turnpike. Data were obtained from NJSP on the numbers of stops and

searches made by troopers assigned to the Moorestown and Cranbury

police barracks—two of three barracks assigned to the turnpike. Motorist

stop data were from April 1997 through November 1998 (except February

1998). Data on motorist searches resulting from stops were from the same

two barracks. Only data on searches for which motorists gave their

consent for the search were available. Motorist search data were from

selected months in 1994, all months in 1996 except February, and every

month from April 1997 to February 1999. Data were obtained on motorist

arrests made by troopers assigned to the Cranbury, Moorestown, and

Newark barracks. Data on these arrests were from January 1996 through

December 1998.

Over 87,000 motorists were stopped by NJSP. Twenty-seven percent of

motorists stopped were African American, 7 percent were Hispanic, 7

percent were another minority, and 59 percent were white. Little

difference was reported between the two NJSP barracks in the racial

characteristics of motorists stopped. Only 627, or less than 1 percent, of

these stops involved a search, but the racial characteristics of the

motorists searched were not reported separately.

Racial characteristics were available for 1,193 motorists who gave consent

for searches. Fifty-three percent of motorists searched were African

American, 24 percent were Hispanic, 1 percent were another minority, and

21 percent were white. Little difference was reported between the two

NJSP barracks in the racial characteristics of motorists searched.

Source

Study Design/Results
Appendix I

Studies of Racial Characteristics of Drivers Stopped by Police

Page 33 GAO/GGD-00-41 Racial Profiling

Approximately 2,900 motorists were identified in the state’s Computerized

Criminal History Database as being arrested3

 by troopers assigned to all

three barracks. Sixty-two percent of motorists arrested were African

American, 6 percent were of another minority, and 32 percent were white.

Little difference between the three NJSP barracks in the racial

characteristics of motorists arrested was reported.

Because of several methodological limitations, this analysis does not

provide clear evidence of racial profiling of minority drivers.

First, direct comparisons between the racial characteristics of drivers

stopped, drivers searched, and drivers arrested are problematic because

comparable data for stops, searches, and arrests were not reported.

Although there is some overlap, data for stops, searches, and arrests were

reported for different time periods.

Second, search data were provided for consent searches only. Data on

instances when motorists denied troopers’ search requests were not

available. Without data on denied search requests, it is not possible to

know the racial characteristics of all motorists from which nonwarrant

and nonprobable cause searches were requested.

Overall, as the report acknowledges, it is difficult to interpret the

significance of the study’s results because of the absence of any

benchmark data, such as data from a survey to determine the racial or

ethnic characteristics of turnpike motorists or the racial characteristics of

motorists who put themselves at risk for being stopped.

 

3

 Arrests generally include arrests for more serious offenses, including all drug-related arrests, but

exclude arrests for drunk driving.

Limitations
Appendix II

Methodological Issues In Studying Racial

Profiling of Motorists

Page 34 GAO/GGD-00-41 Racial Profiling

Determining whether and to what extent racial profiling may occur on the

nation’s roadways is a complicated task that would require collecting more

and better data than are currently available. Additional studies using

comparison groups that are similar to the stopped motorist group in terms

of their risk of being stopped for a traffic violation would contribute to our

understanding of this issue. Federal, state, and local data collection efforts

currently under way should augment the available information provided

that the data are complete, accurate, consistent, and specific. To the extent

that such data are gathered by a number of jurisdictions, a more complete

picture of which motorists are stopped and why may emerge. Surveys of

motorists and police officers and reviews of police protocols and training

guides can also contribute to the state of knowledge about racial profiling.

In our judgment, such a multifaceted examination of the issues is the

means for developing a full and meaningful answer to questions about

racial profiling.

We have noted that some of the existing analyses may have made

comparisons that were not valid. These analyses generally compared the

racial characteristics of motorists who were stopped with the racial

characteristics of a larger population. The larger population may have been

a state’s driving age population or the U.S. population as a whole, among

others. The limitation of such analyses is that they do not address whether

different groups may have been at different levels of risk for being stopped

because they differed in their rates and/or severity of committing traffic

violations. Although discretion may play a part in an officer’s decision to

pull over a driver, the justification for initiating a stop is a violation or

infraction committed by drivers. The available research on racial profiling,

however, has given very little attention to potential differences across

groups in the relative risk of being stopped.

Lamberth’s studies1

 have been important steps in the direction of

estimating the relative risks of being stopped, but they did not provide

conclusive results. In both studies, Lamberth found that more than 9 out of

10 motorists violated a traffic law and were thus legally eligible for being

stopped by the police. However, it is not clear that the driving violations

that made motorists legally eligible for being stopped were the same

violations that would prompt actual stops by law enforcement officers. For

example, one of Lamberth’s studies considered only speeding, although

this type of infraction is not the only reason that motorists are stopped.

The extent to which motorists exceed the speed limit and/or the number of

violations they commit simultaneously may also affect their likelihood of

 

1

 See appendix I.
Appendix II

Methodological Issues In Studying Racial Profiling of Motorists

Page 35 GAO/GGD-00-41 Racial Profiling

being stopped. Lamberth’s other study considered speeding plus other

traffic law violations. However, this study also did not differentiate

between the type or seriousness of different violations. For example,

motorists who greatly exceeded the speed limit, committed certain types

of violations, or committed several violations simultaneously may have

been more likely to be stopped than others. None of the analyses that we

identified examined whether there may be racial disparities in motorist

stops that are related to the type or seriousness of the traffic violation

committed. We recognize that it is difficult to determine which traffic

violations specifically prompt a law enforcement officer to stop one

motorist rather than another. Different jurisdictions and officers may use

different criteria, and candid information on the criteria may be difficult to

obtain. Nonetheless, to understand the extent to which motorist stops may

have a discriminatory basis, data are needed on traffic violations—

including the type and seriousness of those violations—that produce stops

and the relative rates at which different groups of drivers in a particular

jurisdiction commit those violations. Although we have no reason to

expect that there are racial differences in committing traffic violations,

such data would enable the most appropriate comparisons to be made in

order to answer a key question; that is, how do the racial characteristics of

motorists who are stopped for a particular traffic violation compare with

the racial characteristics of all drivers who commit the same violation but

are not stopped? Both observational studies and driver surveys may be

useful in developing such comparative information.

Federal, state, and local efforts to collect data on motorist stops should

increase the amount of information on law enforcement practices on the

roadways. However, the usefulness of such data for addressing research

questions about racial profiling will depend on the extent to which the data

are complete, accurate, consistent, and sufficiently specific to provide

meaningful information. Although we recognize that no empirical data are

likely to be perfect, it would be difficult to draw conclusions about racial

profiling if (1) stop data were selectively recorded, (2) race or other stop

information is inaccurately recorded, (3) different jurisdictions capture

different information, and/or (4) the information recorded is too broad to

understand what happened. For example, recording “vehicle code

violation” as the reason for the stop—when such a code can represent

anything from failing to signal a lane change within a designated distance

to a serious speeding offense—could make it difficult to discern whether

and how the traffic violations for which motorists are stopped differ

between racial groups.
Appendix II

Methodological Issues In Studying Racial Profiling of Motorists

Page 36 GAO/GGD-00-41 Racial Profiling

In addition, confidence in the quality of data would be enhanced if

provisions were made to validate the accuracy and completeness of data

that are collected. Also, it would be constructive to have a mechanism in

place for agencies to communicate and coordinate with one another to

ensure that they are collecting comparable information, and at a sufficient

level of specificity, to be useful for answering questions about racial

profiling in a meaningful way.

It could also be instructive to examine whether there was a correlation

between the race of the law enforcement officer and that of the stopped

motorist. In addition, information is needed on the extent to which officers

exercise discretion in the process of stopping, citing, and searching

drivers. Toward this end, a review of established police protocols and

training guides could be useful. In addition, a survey of officers could

provide information on what observations and judgments they factor into

their decisions to make stops. Although survey data of this sort would be

subject to response biases, including the possibility that respondents

would offer socially acceptable responses, well-designed surveys of police

officers could be a useful supplement to official data. Further, in addition

to querying drivers about the frequency with which they were stopped,

cited, and searched, driver surveys could also ask about how many miles

the drivers typically drove and how often they committed infractions that

were likely to prompt stops. Data from police records and surveys could

then be compared with them.
Appendix III

Bureau of Justice Statistics Police Public

Contact Survey

Page 37 GAO/GGD-00-41 Racial Profiling

INTRO 1 – Now I have some additional questions about any contacts you may have had with

the police at any time during the last 12 months, that is, any time since

 1, 1998. Exclude contacts with private security guards, police 

officers you see on a social basis, police officers related to you, or any contacts

that occurred outside the United States.

OMB No. 1121-0111: Approval Expires 06/30/2000

FORM PPCS-1 (5-14-99)

U.S. DEPARTMENT OF COMMERCE BUREAU OF THE CENSUS ACTING AS COLLECTING AGENT FOR THE

U.S. DEPARTMENT OF JUSTICE

J ____

Sample Control number

PSU Segment CK Serial

ASK OF ALL PERSONS 16+

We estimate that it will take from 5 to 10 minutes to

complete this interview with 10 minutes being the

average time. If you have any comments regarding

these estimates or any other aspect of this survey, send

them to the Associate Director for Management

Services, Room 2027, Bureau of the Census,

Washington, DC 20233 or to the Office of Information

and Regulatory Affairs, Office of Management and

Budget, Washington, DC 20503.

NOTICE – Your report to the Census Bureau is confidential by

law (U.S. code 42, Sections 3789g and 3735). All identifiable

information will be used only by persons engaged in and for

the purposes of the survey, and may not be disclosed or

released to others for any purpose.

POLICE PUBLIC CONTACT SURVEY

SUPPLEMENT TO THE

NATIONAL CRIME

VICTIMIZATION SURVEY

Proxy unacceptable for PPCS

D. Reason for PPCS noninterview

FIELD REPRESENTATIVE – Read introduction

CONTACT SCREEN QUESTIONS

1a. Did you have any contact with a police

officer during the last 12 months, that is,

any time since 1, 1998?

1b. Were any of these contacts with a police

officer in person, that is face-to-face?

1999

A. Field 

Representative’s

Code

B. Respondent’s

characteristics

Line no. Age

Last name

M

F

001 002 1 004

2

Sex

003 White

Black

1

2

3

Race

005 Yes

No

1

2

Hispanic

Origin

006

C. Type of PPCS interview

Personal (Self)

Telephone (Self)

Noninterview – FILL ITEM D

1

2

3

007

NCVS Type Z noninterview

Refused PPCS only

Not available for PPCS only 

NCVS proxy interview

1

2

3

4

008

Asian,

Pacific

Islander

4

American

Indian,

Aleut,

Eskimo

5 Other

010 1 Yes

2 No – END INTERVIEW

009 1 Yes

2 No – END INTERVIEW

Include contacts which occurred as a result of being in a vehicle that was stopped

by the police. However, please exclude those contacts which occurred because your

employment or volunteer work brought you into regular contact with the police.

SKIP to Intro 1

First name

FIELD REPRESENTATIVE – Complete a PPCS-1

for all persons 16+ in all interviewed households.

Complete a PPCS-1 through Item D for each

NCVS Type Z person or NCVS proxy interview.

DO NOT complete any PPCS-1 forms if the

household is a Type A.
Appendix III

Bureau of Justice Statistics Police Public Contact Survey

Page 38 GAO/GGD-00-41 Racial Profiling

Page 2 FORM PPCS-1 (5-14-99)

CHECK

ITEM A1 Was the motor vehicle stopped only

once? (Is box 1 marked in Item 1c(1)?) Yes – SKIP to Item 2

No – Go to Check Item A2

1d. You said that you were in a motor vehicle

that was stopped by the police on more than

one occasion in the last 12 months. How

many different times were you stopped?

CONTACT SCREEN QUESTIONS – Continued

1c. How would you best describe the reason or

reasons for these in-person contacts with

the police during the last 12 months, that is,

any time since ______________1, 1998?

As I read some reasons, tell me if any of the

contacts occurred once, more than once, or

not at all.

Mark (X) all that apply.

A motor vehicle stop:

(1) You were in a motor vehicle stopped 

by the police..........................

You contacted a police officer:

(2) To report a crime......................

(3) To report a crime you had witnessed.....

(4) To ask for assistance or information .....

(5) To let the police know about a problem in

the neighborhood .....................

(6) To tell the police about a traffic accident

you had witnessed ....................

(7) For some other reason – Please specify ...

A police officer contacted you because:

(8) You were involved in a traffic accident ...

(9) You were a witness to a traffic accident . .

(10) You were the victim of a crime which

someone else reported to the police .....

(11) The police thought you might have been a

witness to a crime.....................

(12) The police asked you questions about a

crime they thought you were involved in .

(13) The police had a warrant for your arrest . .

(14) The police wanted to advise you about

crime prevention information ...........

(15) Some other reason we haven’t

mentioned – Please specify .............

1 2

ONCE

MORE THAN

ONCE

011

NOT AT ALL

3

Transcribe entries from box 1 or

box 2 to the FLAP on page 11.

012 1 2 3

013 1 2 3

014 1 2 3

015 1 2 3

016 1 2 3

017 1 2 3

018 1 2 3

019 1 2 3

020 1 2 3

021 1 2 3

022 1 2 3

023 1 2 3

024 1 2 3

025 1 2 3

MOTOR VEHICLE STOPS

1

2

CHECK

ITEM A2 Was the motor vehicle stopped more than

once? (Is box 2 marked in Item 1c(1)?) 1

2

(Record actual number.)

026

027

028

Number of times

INTRO 2 – You reported that you were in a motor vehicle that was stopped by the police on

more than one occasion. For the following questions, please tell me about the most

recent occasion.

2. How many people age 16 or over,

INCLUDING YOURSELF, were in the vehicle?

3. Were you the driver?

4. How many police officers were present

during (this/the most recent) incident?

029

Number of persons

Yes 

No – SKIP to Item 37

1

2

030

One – SKIP to Item 6

More than one

031 1

Number of police officers

(Record actual number.)

FIELD REPRESENTATIVE – Read introduction

Yes – Ask Item 1d

No – SKIP to Item 37
Appendix III

Bureau of Justice Statistics Police Public Contact Survey

Page 39 GAO/GGD-00-41 Racial Profiling

Page 3 FORM PPCS-1 (5-14-99)

MOTOR VEHICLE STOPS – Continued

Yes – Ask Item 10 

No

Don’t know

1

2

036

5. Were the police officers White, Black, or some other race? All White

All Black

All of some other race

Mostly White

Mostly Black

Mostly some other race

Equally mixed

Don’t know race of any/some

6. Was the police officer White, Black, or

some other race? White

Black

Some other race

Don’t know

7. Were you arrested?

8. Did the police officer(s) threaten to

arrest you?

VEHICLE/PERSONAL SEARCH

9. Did the police officer(s) search the

vehicle?

10. At any time during (this/the most

recent) incident did the police

officer(s) ask permission to search the

vehicle?

11. Did you give the police officer(s)

permission to search the vehicle?

12. Did the police officer(s) find any of the

following items in the vehicle?

(Read answer categories.)

Illegal weapons

Illegal drugs

Open containers of alcohol, such as beer or liquor

Other evidence of a crime – Please specify

None of the above

13. Do you think the police officer(s) had a

legitimate reason to search the

vehicle?

14. At any time during (this/the most

recent) incident, did the police

officer(s) search you, frisk you, or pat

you down?

15. At any time during (this/the most

recent) incident, did the police

officer(s) ask permission to search

you, frisk you, or pat you down?

16. At any time during (this/the most

recent) incident, did you give the

police officer(s) permission to search

you, frisk you, or pat you down?

17. Did the police officer(s) find any of the

following items on or near you?

032 1

2

3

4

5

6

7

8

SKIP to

Item 7

033 1

2

3

4

Yes

No

Don’t know

035 1

2

3

Yes – SKIP to Item 9

No

Don’t know

034 1

2

3

3

Yes – Ask Item 11 

No

Don’t know

1

2

037

3

Yes

No

Don’t know

038 1

2

3

Mark (X) all that apply.

039 1

2

3

4

5

040

041

042

043

Yes

No

Don’t know

044 1

2

3

Yes – Ask Item 15

No 

Don’t know

1

2

045

3

Yes – Ask Item 16 

No 

Don’t know

1

2

046

3

Yes

No

Don’t know

047 1

2

3

Illegal weapons

Illegal drugs

Open containers of alcohol, such as beer or liquor

Other evidence of a crime – Please specify

None of the above

048 1

2

3

4

5

049

050

051

052

Mark (X) all that apply.

SKIP to Item 14

SKIP to Item 12

SKIP to Item 19

SKIP to Item 17

(Read answer categories.)

18. Do you think the police officer(s) had a

legitimate reason to search you, frisk

you, or pat you down?

Yes

No

Don’t know

053 1

2

3
Appendix III

Bureau of Justice Statistics Police Public Contact Survey

Page 40 GAO/GGD-00-41 Racial Profiling

Page 4 FORM PPCS-1 (5-14-99)

REASON FOR TRAFFIC STOP

(Read answer categories.)

Mark (X) all that apply.

055 1

2

3

056

057

Yes

No

Don’t know

1

2

3

Yes – Ask Item 20 

No

Don’t know

1

2

054

3

19. Did the police officer(s) give a reason

for stopping the vehicle?

20. What was the reason or reasons?

Anything else?

Speeding

Some other traffic offense

A vehicle defect, such as a burned out tail light or an

expired license plate

Roadside check for drunk drivers

To check the respondent’s license plate, driver’s

license, or vehicle registration

The police officer suspected the respondent of

something

Some other reason – Please specify

21. Would you say that the police

officer(s) had a legitimate reason for

stopping you?

OUTCOME OF TRAFFIC STOP

22. During (this/the most recent) incident

were you: Given a warning?

Given a traffic ticket?

Tested for drunk driving?

Charged with driving while under the influence

of drugs or alcohol?

Questioned about what you were doing in the

area?

None of the above

23. Not including anything just

mentioned, were you charged with

any of the following?

Assaulting a police officer

Possession of a firearm or concealed weapon

Something else – Please specify

None of the above

24. At any time during (this/the most

recent) incident were you

handcuffed?

USE OF FORCE IN TRAFFIC STOPS

25a. During (this/the most recent) incident,

did the police officer(s) for any reason

use or threaten to use physical force

against you, such as grabbing you or

threatening to hit you?

25b. Aside from being handcuffed, did the

police officer(s) for any reason use or

threaten to use physical force against

you, such as grabbing you or

threatening to hit you?

Resisting arrest

Disorderly conduct

4

5

6

7

058

059

060

061

Mark (X) all that apply.

1

2

3

062

4

5

6

063

064

065

066

067

1

2

3

068

4

069

070

071

Drug offense

5

6

7

072

073

074

Yes – SKIP to Item 25b

No 

Don’t know

1

2

075

3

Yes – SKIP to Item 26

No 

Don’t know

1

2

076

3

Yes – Ask Item 26 

No

Don’t know

1

2

077

3

SKIP to Item 34

SKIP to Item 22

(Read answer categories.)

Mark (X) all that apply.

SKIP to Item 34

ASK OR VERIFY
Appendix III

Bureau of Justice Statistics Police Public Contact Survey

Page 41 GAO/GGD-00-41 Racial Profiling

Page 5 FORM PPCS-1 (5-14-99)

Yes – Ask Item 28 

No

Don’t know

1

2

092

3

USE OF FORCE IN TRAFFIC STOPS – Continued

1

2

3

26. What type of physical force did the

police officer(s) use or threaten to use

during (this/the most recent) incident?

Did the police officer(s):

Actually push or grab you in a way that did not

cause pain?

Actually push or grab you in a way that did cause

pain?

Actually kick you or hit you with the police

officer’s hand or something held in the police

officer’s hand?

Actually unleash a police dog that bit you?

Actually spray you with a chemical or pepper

spray?

Actually point a gun at you but did not shoot?

Actually fire a gun at you?

Actually use some other form of physical force? –

Please specify

Threaten to push or grab you?

Threaten to kick you or hit you with the police

officer’s hand or something held in the police

officer’s hand?

Threaten you with a police dog?

Threaten to spray you with a chemical or pepper

spray?

Threaten to fire a gun at you?

Threaten to use some other form of physical

force? – Please specify

27. Do you feel that any of the physical

force used or threatened against you

was excessive?

Actually pushing or grabbing the respondent in a way

that did not cause pain?

Actually pushing or grabbing the respondent in a way

that did cause pain?

Actually kicking the respondent or hitting the

respondent with the police officer’s hand or something

held in the police officer’s hand?

Actually unleashing a police dog that bit the

respondent?

Actually spraying the respondent with a chemical or

pepper spray?

Actually pointing a gun at the respondent but did not

shoot?

Actually firing a gun at the respondent?

Actually using some other form of physical force? –

Please specify

Threatening to push or grab the respondent?

Threatening to kick the respondent or hit the respondent

with the police officer’s hand or something held in the

police officer’s hand?

Threatening the respondent with a police dog?

Threatening to spray the respondent with a chemical

or pepper spray?

Threatening to fire a gun at the respondent?

Threatening to use some other form of physical force? –

Please specify

(Read answer categories)

4

5

6

7

8

9

10

11

12

13

14

078

079

080

081

082

083

084

085

086

087

088

089

090

091

(Read items marked in Item 26.)

093 1

2

3

4

5

6

7

8

9

10

11

12

13

14

094

095

096

097

098

099

100

101

102

103

104

105

106

SKIP to Item 29a

28. FIELD REPRESENTATIVE – Mark without

asking when ONLY ONE box is marked in

Item 26.

Mark (X) all that apply.

Mark (X) all that apply.

Specifically, what type of physical

force do you feel was excessive?
Appendix III

Bureau of Justice Statistics Police Public Contact Survey

Page 42 GAO/GGD-00-41 Racial Profiling

Page 6 FORM PPCS-1 (5-14-99)

USE OF FORCE IN TRAFFIC STOPS – Continued

Yes

No 

Don’t know

1

2

114

(Read answer categories.)

29c. What type of care did you receive for

your (injury/injuries)? No care received

Hospitalization

Other – Please specify

Respondent treated self 

Emergency services only

Mark (X) all that apply.

1

2

113

3

4

5

31. At any time during (this/the most

recent) incident did you: Verbal

Argue with or disobey the police officer(s)?

Curse at, insult, or call the police officer(s) a name?

Say something threatening to the police officer(s)?

Cooperation

Resist being handcuffed or arrested?

Resist being searched or having the vehicle searched?

Try to escape by hiding, running away, or being in

a high-speed chase?

Physical Resistance

Grab, hit, or fight with the police officer(s)?

Use a weapon to threaten the police officer(s)?

Use a weapon to assault the police officer(s)?

Do anything else that might have caused the

police officer(s) to use or threaten to use physical

force against you? – Please specify

32. Were you drinking at the time of

(this/the most recent) incident?

34. Looking back at (this/the most recent)

incident, do you feel the police

behaved properly or improperly?

Properly – SKIP to Check Item B1

Improperly

Don’t know – SKIP to Check Item B1

35. Did you take any formal action, such

as filing a complaint or lawsuit?

36. With whom did you file a complaint or

lawsuit? Civilian Complaint Review Board

Law enforcement agency employing the police officer(s)

Local prosecutor’s office

The FBI or the U.S. Attorney’s office

Law enforcement agency or the local government

Police officer involved in the contact

Took other formal action

30. Do you think any of your actions

during (this/the most recent) incident

may have provoked the police

officer(s) to use or threaten to use

physical force?

3

Yes – Ask Item 36

No

1

2

128

3 Don’t know

1

2

3

115

116

117

118

119

120

121

122

123

124

Yes

No 

Don’t know

1

2

125

3

Yes

No 

Don’t know

1

2

126

3

33. Were you using drugs at the time

of (this/the most recent) incident?

1

2

127

3

129

130

131

132

1

2

3

4

5

6

7

133

134

135

4

5

7

8

9

10

6

(Read answer categories.)

Mark (X) all that apply.

Yes

No – SKIP to Item 30

1

2

29a. Were you injured as a result of 107

(this/the most recent) incident?

29b. Did your injuries include any of the

following? Gunshot wound

Broken bones or teeth knocked out

Internal injuries

Bruises, black eyes, cuts, scratches, or swelling

Any other injury – Please specify

108 1

2

3

4

5

109

110

111

112

(Read answer categories.)

Mark (X) all that apply.

SKIP to Check Item B1
Appendix III

Bureau of Justice Statistics Police Public Contact Survey

Page 43 GAO/GGD-00-41 Racial Profiling

Page 7 FORM PPCS-1 (5-14-99)

USE OF FORCE IN TRAFFIC STOPS – Continued

Record actual number.

37. Earlier you reported you had a

face-to-face contact with the police

for the following reason(s), (Read

items marked on the Flap on page 11.)

Did (this/any of these) contact(s)

result in the police handcuffing you

or using or threatening to use

physical force against you, such as

by grabbing you or threatening to

hit you during the last 12 months,

that is, any time since

______________1, 1998?

Yes – Ask Item 38 

No

1

2

138

3 Don’t know

140

141

142

143

1

144

145

146

38. On how many different occasions did

the police handcuff you or use or

threaten to use physical force against

you?

INTRO 3 – You reported that, on more than one occasion, you had contact with the police in

which the police handcuffed you or used or threatened to use physical force against

you. For the following questions, please tell me about the most recent occasion.

A motor vehicle stop:

Respondent was in a motor vehicle stopped by the police

Respondent contacted a police officer:

To report a crime

To report a crime respondent had witnessed

To ask for assistance or information

To let the police know about a problem in the neighborhood

To tell the police about a traffic accident respondent had

witnessed

For some other reason – Please specify

A police officer contacted you because:

Respondent was involved in a traffic accident

Respondent was a witness to a traffic accident

Respondent was the victim of a crime which someone

else reported to the police

The police thought the respondent might have been a

witness to a crime

The police asked the respondent questions about a crime

they thought you were involved in

The police had a warrant for the respondent’s arrest

The police wanted to advise the respondent about crime

prevention information

For some other reason – Please specify

40. How many police officers were

present during (this/the most recent)

incident?

Once – SKIP to Item 39

More than once

139 1

Number of times

2

3

4

5

6

7

8

9

10

11

12

13

14

15

One – SKIP to Item 42

More than one

155 1

Number of police officers

147

148

149

150

151

152

153

154

CHECK

ITEM B1 1

2

136

Was respondent the driver during the traffic

stop? (Is box 1 marked in Item 3?)

Was physical force used or threatened? (Is

box 1 marked in Item 25a OR 25b?)

Yes – END INTERVIEW

No – Go to Check Item B2

Other than a motor vehicle stop, did the

respondent have any other in-person contacts

with the police? (Are there any entries marked

in categories (2) through (15) on the FLAP on

page 11?)

AND

CHECK

ITEM B2 1

2

137 Yes – Ask Item 37

No – END INTERVIEW

END INTERVIEW

FIELD REPRESENTATIVE – Read Introduction

USE OF FORCE IN OTHER FACE-TO-FACE CONTACTS

39. FIELD REPRESENTATIVE – Mark without

asking when ONLY ONE box is marked on

the FLAP on page 11.

Which of these contacts that you

reported earlier resulted in a police

officer using or threatening to use

physical force?
Appendix IV

Federal Law Enforcement Effort to Collect

Motorist Stop Data: Field Test Locations and

Data Elements

Page 44 GAO/GGD-00-41 Racial Profiling

President Clinton directed the Attorney General, Secretary of the Treasury,

and Secretary of the Interior in a June 9, 1999, memorandum to design and

implement a system to collect and report statistics relating to race,

ethnicity, and gender for law enforcement activities in their departments.

Within 120 days of the directive, in consultation with the Attorney General,

the departments were to develop proposals for collecting the data; and

within 60 days of finalizing the proposals, the departments were to

implement a 1-year field test. This appendix presents the field locations

and data elements that the Attorney General’s October 1999 proposal

indicated would be collected during the field test.

Five agencies in three federal departments are to be involved in collecting

data on individuals who are stopped or searched by law enforcement. The

agencies include the Department of Justice’s Drug Enforcement

Administration and the Immigration and Naturalization Service; the

Department of the Interior’s National Park Service; and the Department of

the Treasury’s U.S. Customs Service and uniformed division of the Secret

Service.

Between six and nine of the following Drug Enforcement Administration

Operation Jetway1

 sites are to be included in the field test:

• Detroit Metropolitan Airport;

• Newark International Airport;

• Chicago-O’Hare International Airport;

• George Bush Intercontinental Airport (Houston);

• Miami International Airport;

• Charleston, SC, bus station;

• Cleveland, OH, train station;

• Albuquerque, NM, train station; and

• Sacramento, CA, bus station.

The following Immigration and Naturalization sites are to be included in

the field test:

• John F. Kennedy International Airport (New York City);

• George Bush Intercontinental Airport (Houston);

• Seattle/Tacoma Airport;

• El Cajon, CA, Station;

• Yuma, AZ, Station;

 

1

 Operation Jetway is a drug interdiction program.

Presidential Directive

Locations of Field Testing

Department of Justice
Appendix IV

Federal Law Enforcement Data Collection

Page 45 GAO/GGD-00-41 Racial Profiling

• El Paso, TX, Station; and

• Del Rio, TX, land-border crossing.

The National Park Service was the only agency identified by the

Department of the Interior with regular public contact. The following Park

Service sites are to be included in the field test.

• Lake Mead National Recreation Area (Nevada and Arizona);

• Yosemite National Park (California);

• Grand Canyon National Park (Arizona);

• Glen Canyon National Recreation Area (Arizona and Utah);

• National Expansion Memorial Park (Missouri);

• Indiana Dunes National Lake Shore (Indiana);

• Natchez Trace Parkway (Mississippi and Tennessee);

• Blue Ridge Parkway (Virginia and North Carolina);

• Valley Forge National Historical Park (Pennsylvania);

• Delaware Water Gap National Recreation Area (Pennsylvania and New

Jersey); and

• Baltimore Washington Parkway (Washington, D.C., and Maryland).

The Department of the Treasury identified the U.S. Customs Service and

the uniformed division of the Secret Service as the agencies with regular

public contact. The following sites are to be included in the field test:

U.S. Customs:

• Chicago O’Hare International Airport;

• JFK International Airport (New York City);

• Newark International Airport;

• Miami International Airport; and

• Los Angeles International Airport.

The Secret Service uniformed division will collect data in Washington D.C..

Agencies are to collect data describing demographic characteristics, such

as gender, race, ethnicity, national origin, and date of birth based on

agent’s observation, or from official documents such as drivers’ license

when available. All participating agencies are to collect a core set of data

elements, but they may collect additional data as they deem appropriate.

Following is a core set of data elements contained in the data collection

proposal:

Department of the Interior

Department of the Treasury

Data Elements
Appendix IV

Federal Law Enforcement Data Collection

Page 46 GAO/GGD-00-41 Racial Profiling

• date of encounter,

• start time of contact,

• motorist’s gender,

• motorist’s race and ethnicity,

• motorist’s national origin,

• location of contact,

• motorist’s suspected criminal activity,

• reason for contact,

• external sources of information on person contacted,

• law enforcement action taken, and

• end time of contact.
Appendix IV

Federal Law Enforcement Data Collection

Page 47 GAO/GGD-00-41 Racial Profiling
Appendix V

State Legislation and Proposed State

Legislation to Collect Traffic Stop Data:

Elements to be Collected

Page 48 GAO/GGD-00-41 Racial Profiling

Proposed data elements

Arkansas

HB 1261

California

SB 78

Connecticuta

P.L. 99-198

Race or ethnicity   

Age  

Gender 

Reason for stop/violation   

Search conducted   

Who, what searched 

Legal basis of search 

Oral warning or citation Issued   

Arrest made   

Contraband; type, amount 

Property seized

Resistance to arrest

Officer use of force

Resulting injuries

Location, time of stop

Investigation led to stop

Officer demographics

Passenger demographics

Auto description, license number

Number of Individuals stopped for routine

traffic violations   

Total number of data elements to be

collected 10 6 8

a

Data collection under Public Law 99-108 is to begin January 1, 2000.
Appendix V

State Legislation and Proposed State Legislation to Collect Traffic Stop Data: Elements to

be Collected

Page 49 GAO/GGD-00-41 Racial Profiling

Florida

HB 177

Illinois

HB 1503

Maryland

SB 430

Massachusetts

Sb 1854

North

Carolinab

S.L.1999-26

Ohio

HB 363

Oklahoma

SB 590

Pennsylvania

HB 873

Rhode

Island

SB 131

South

Carolina

SB 778

         

         

     

         

        

        

        

        

      c  

        

     

 

 

 

  

 



  



       

11 9 10 10 16 15 12 10 12 16

b

Data collection under Session Law 1999-26 is to begin January 1, 2000.

c

Including nature of offense for which arrest was made, whether felony or misdemeanor, and whether

occupants checked for prior criminal record, outstanding warrants, or other criminal charges.

Sources: Federal and State Proposals on Racial Profiling, Professor David Harris, University of

Toledo College of Law; California State Legislature Web site.
Appendix VI

Selected Local Law Enforcement Initiatives to

Collect Motorist Stop Data

Page 50 GAO/GGD-00-41 Racial Profiling

The San Diego Police Department initiated its program to collect vehicle

stop data as a result of concerns about police racial profiling that were

expressed by community groups, such as the Urban League and the

National Association for the Advancement of Colored People. Beginning

January 1, 2000, San Diego’s police force, with 1,300 patrol and 60 motor

officers, is to begin using forms to manually collect stop data. Later, plans

are to use laptop or hand-held computers to collect information that would

be sent to a department database via a new wireless system.1

Initial officer concerns about the data collection effort were addressed

through departmental assurances that data would be collected in the

aggregate, keeping officers’ and motorists’ names anonymous. In addition,

the new data collection system is to track when a stop was initiated for a

special assignment, such as when targeting African American gang

members. For each stop, officers are to capture the following information:

motorist’s race/ethnicity; motorist’s age; motorist’s gender; reason for the

stop; whether a search was conducted and whom/what was searched; legal

basis for the search; whether a consent form was obtained; whether an

oral warning or citation was issued; whether an arrest was made; whether

property was seized; whether contraband was found; and whether the

officer was on special assignment.

San Diego police officials said that they plan to enlist the assistance of a

statistical expert in analyzing the data. They hope to obtain an initial

analysis after the first 6 months of data collection. The department is also

working with community-based organizations to address questions they

have about the project and how data will be interpreted. San Diego has no

plans to validate data submitted by officers. However, officials noted that

actions by officers could always be reviewed and scrutinized by their

supervisors.

The San Jose Police Department also began its program to collect traffic

stop data in response to community concerns about racial profiling by

police. According to police officials, the data collection will allow them to

learn more about the types of stops being made and to demonstrate the

department’s commitment to working with all members of the community.

In addition, if analysis of the data reveals a pattern suggesting that race

was a factor in motorist stops, then additional training and supervision will

be considered to ensure fair treatment for all.

 

1

 The department’s move to a wireless system is part of an overall updating of technology for the

agency. As of January, 2000, some technical flaws in the system were still unresolved.

San Diego Police

Department

San Jose Police

Department
Appendix VI

Four Localities Data Collection Plans

Page 51 GAO/GGD-00-41 Racial Profiling

San Jose began collecting motorist stop data on June 1, 1999, and plans to

continue the effort until May 31, 2000. For each stop, officers are to

capture the following information: motorist’s race/ethnicity; motorist’s age;

motorist’s gender; reason for the stop; and what action was taken during

the stop, for example whether a citation was issued or whether an arrest

was made. Identities of the officer and motorist involved in each stop will

be kept anonymous and not included in any reports.

San Jose officers call in traffic stop information by police radio to a radio

dispatcher or by keying the information into a mobile computer terminal

located in patrol cars. Dispatchers enter the radioed information into the

computer-aided dispatch (CAD) system, and information entered into the

mobile terminal is automatically entered into the CAD system. Officers use

single digit alpha codes to identify traffic stop data elements. San Jose’s

code system has been in place since the 1970s; however, what is new is the

addition of three new data elements to the existing code system. In

addition to gender and traffic stop disposition, San Jose now collects

reason for stop, race, and age information. The hardware and software

cost to implement the data collection system was less than $10,000.

According to a police official, costs were minimal because the department

was able to make modifications to its existing automated system, thereby

avoiding the need to design a new, potentially costly, one.

The department’s Crime Analysis Unit is to compile the statistics and

prepare two formal reports; one summarizing results for the first 6 months

of data collection, and the other summarizing results for the full year. An

initial review of the data from July 1, 1999, to September 30, 1999, was

released by the San Jose Police Department in December, 1999. Aggregate

figures indicate that Hispanic citizens in particular were stopped at a rate

above their representation in the population. A spokesman for the

department stated that the results do not support this conclusion when the

figures are disaggregated by police district, although population figures by

police district are not available. The official explained that more officers

are assigned to areas with higher calls for service, and thus more stops are

made in these areas, which tend to have higher minority populations. More

analysis will be forthcoming. If results suggest that race may be a factor in

motorist stops, the department may decide to collect data beyond 1 year.

San Jose does not plan to check the validity of the data being submitted by

officers, except to see if officers have entered the correct number of

codes. However, a police official told us that supervisors have access to

data submitted by officers, and they can “stop-in” on an officer call at any

time.
Appendix VI

Four Localities Data Collection Plans

Page 52 GAO/GGD-00-41 Racial Profiling

According to Alameda Police Department officials, most of Alameda

County’s police departments began to voluntarily collect motorist stop

data in anticipation of state and federal legislation requiring the collection

of such data.2

 The Alameda Police began collecting motorist stop data on

October 1, 1999.

Alameda police officials told us that stop data are recorded on written or

automated citations, if issued. For all noncitation stops, such as warnings

or arrests, officers use the CAD system to call in each of the required data

elements. For each stop, officers are to capture the following information:

motorist’s race/ethnicity, motorist’s age, motorist’s gender, reason for the

stop, who/what was searched, whether an oral warning was given, and

whether an arrest was made.

Alameda police officials said that information patrol officers write on

citations will be keyed into an automated citations database. In addition,

motorcycle officers have hand-held computers that they use to input and

store traffic stop information. These data will be printed out and keyed

into the automated citations database as well. A separate database is to

contain the CAD-collected data for noncitation stops.

Although officers’ and motorists’ information will be captured in the data

system, the department has no plans to generate any reports from the data

collected. According to Alameda police officials, the police department

does not plan to analyze, validate, or publish its data. They said that the

data would be made available to the public if requested.

The Piedmont Police Department, located in Alameda County, began

voluntary collection of motorist stop data in anticipation of pending state

and federal legislation. Piedmont began collecting motorist stop data on

October 1, 1999.

According to a Piedmont police official, Piedmont is a small department

with 21 officers who record motorist stop data manually. For each traffic

stop, the officer is to fill out an index card that contains data fields for

recording the motorist’s race, sex, and age. At the bottom of the card, the

officer is to record the reason for stop, whether the vehicle was searched,

whether an oral warning or citation was issued, and whether an arrest was

made. No officer or motorist names will be included on the cards. A

 2

 As noted in table 1 of our report, the governor of California vetoed legislation proposing the collection

of motorist stop data. A federal bill (H.R. 118) requiring that the Department of Justice conduct a study

of racial profiling was referred to the Senate, but no action has been taken.

Alameda Police

Department

Piedmont Police

Department
Appendix VI

Four Localities Data Collection Plans

Page 53 GAO/GGD-00-41 Racial Profiling

department official indicated that she expects a volume of no more than

400 cards per month. Information from the cards is to be input into an

Excel spreadsheet for analysis, and results are to be tallied on a monthly

basis.

The department reportedly has no planned effort to validate the

information that officers record on the cards. Piedmont police officials

said that the watch commander can monitor the activity of officers by

listening to interactions between the officers and motorists over the

dispatch system. The watch commander can then compare the information

overheard on the dispatch system with that recorded on the index cards

submitted by the officers.
Appendix VII

Comments From U.S. Department of Justice

Page 54 GAO/GGD-00-41 Racial Profiling
Appendix VII

Comments From U.S. Department of Justice

Page 55 GAO/GGD-00-41 Racial Profiling
Appendix VII

Comments From U.S. Department of Justice

Page 56 GAO/GGD-00-41 Racial Profiling
Appendix VII

Comments From U.S. Department of Justice

Page 57 GAO/GGD-00-41 Racial Profiling
Appendix VIII

GAO Contacts and Staff Acknowledgments

Page 58 GAO/GGD-00-41 Racial Profiling

Laurie E. Ekstrand (202-512-8777)

Evi. L. Rezmovic (202-512-8777)

In addition to those named above, David P. Alexander, Carla D. Brown,

Ann H. Finley, Monica Kelly, Anne K. Rhodes-Kline, Jan B. Montgomery,

and Douglas M. Sloane made key contributions to this report.

GAO Contacts

Acknowledgements
Page 59 GAO/GGD-00-41 Racial Profiling
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