Based on a report and data 

provided by Humanalysis, Inc.

Over the past several years State and

local governments have engaged in

data collection regarding demographic

characteristics of persons stopped by

the police. These efforts are aimed at

understanding factors used by law

enforcement to make such stops.

While data collections on law enforcement encounters have been undertaken, analysts have debated the availability of methods to meaningfully

analyze these data. One complicating

factor is the need to identify the

baseline data necessary to make

assessments regarding different racial

groups’ experience with the police.

In 1999 several Federal law enforcement agencies designed and implemented data collection procedures to

capture race and ethnicity information

on persons stopped by their officers.

The Immigration and Naturalization

Service’s (INS) Border Patrol agents

began collecting race and ethnicity

data for those persons stopped at

selected border crossings and highway

checkpoints. Likewise Drug Enforcement Administration (DEA) agents

collected data on nonspecific suspects

stopped in selected airports. 

At the State level, studies have been

undertaken in Maryland, California, and

New Jersey. New Jersey measured

characteristics of persons using the

New Jersey Turnpike and those that

were speeding. (See list of sources.)

The various Federal and State agencies collecting the data wanted to have

baseline data available to estimate the 

race and ethnicity of all persons

passing through their area of responsibility. Lacking this kind of baseline

data, it would not be possible to know

whether the characteristics of the

persons stopped were disproportionate

to all those who had a probability of

being stopped. 

Scope

The Bureau of Justice Statistics (BJS),

working with the Bureau of Transportation Statistics (BTS), contracted with

Humanalysis, Inc., of Orlando, Florida,

to conduct observational studies at two

sites: 1) Immigration and Naturalization

Service (INS) Border Patrol Checkpoint

along Interstate 5 in San Clemente,

California, and 2) the Detroit Metropolitan Airport. This report describes the

findings from both data collections and

assesses the difficulties in implementing this kind of a study. 

The primary object of the observational

studies was to determine the feasibility

of using such techniques for estimating

the demographic characteristics of

persons coming through the checkpoint

and airport, and what issues would be

involved in replicating this technique in

other locations. Can people’s race and

ethnicity be easily recorded from observational techniques? To what extent do

practical issues, such as gaining

authorized access or proximity to

persons under observation, play in the

implementation of this kind of study?

OMB standards for classification of

Federal data on race and ethnicity 

OMB Statistical Policy Directive No. 15

“Race and Ethnic Standards for

Federal Statistics and Administrative

Reporting” established standards for

observer-collected data on race and

ethnicity. Federal law enforcement

agencies participating in the data

collection used these categories on

their data collection forms. 

The base data collection at the two

sites implemented the combined

race/ethnicity format which uses the

following categories: 

• American Indian or Alaska Native

• Asian

• Black or African American

• Hispanic or Latino

• Native Hawaiian or Other Pacific

 Islander

• White.

U.S. Department of Justice

Office of Justice Programs

Bureau of Justice Statistics

Assessing Measurement Techniques for Identifying

Race, Ethnicity, and Gender: Observation-Based

Data Collection in Airports and at Immigration

Checkpoints

 January 2003, NCJ 196855

This study was supported by Bureau

of Transportation Statistics contract

number DTTS59-01-F-10151 to

Humanalysis, Inc. The contents of

this document do not necessarily

reflect the views or policies of the

Bureau of Justice Statistics, the U.S.

Department of Justice, the Bureau of

Transportation Statistics, or the U.S.

Department of Transportation.
Practical issues for observational

studies

Practical arrangements were necessary to conduct an observational study,

such as gaining permission to access

the site and finding an unobtrusive

location within the site, as well as

dealing with issues of traffic volume,

poor lighting, and multiple points of

ingress and egress. 

Site access

Gaining approval to conduct the observation test project required a great 

deal of effort over many months. BJS

was denied access by three airports

before the Detroit airport was approached and agreed to allow observers into the facility. Numerous sites

were reviewed before the INS San

Clemente checkpoint was selected.

The terrorist attacks of September 11,

2001, also added a 4-month delay in

obtaining permission to conduct the

studies.

Limitations

Demographic data were not available

from either site. Since it was not critical

that the observer accurately categorize

the person’s race or ethnicity, as the

premise of racial profiling is the

perception of the officer, the project

tested the observation method to

assess whether baseline data could

practicably be collected. 

Border crossing checkpoint study

Study location

INS selected the Border Patrol checkpoint at San Clemente, California, as

the site for the observational study.

The checkpoint is located on Interstate

I-5 approximately 5 miles south of San

Clemente, within the Camp Pendleton

US Marine base. Interstate I-5 is the

main north-south coastal highway in

California and has four traffic lanes at

the checkpoint with daytime traffic flow

normally in thousands of cars per hour.

The Border Patrol site has a two-story

operations building and a one-story

administration building for the patrol

agent in charge and staff. 

Border Patrol checkpoint on I-5 south

The actual checkpoint was covered by

a pavilion that shades the area during

the day. Suspended lights provided

illumination after sunset.

The volume of traffic at the checkpoint

varied with time and day. The Border

Patrol monitored traffic flow using video

cameras south of the checkpoint.

When the backup of vehicles extended

more than a mile, the checkpoint was

shut down and vehicles were allowed

to pass at highway speed. This occurred most often during the morning

and afternoon rush hours on weekdays

and from midmorning through evening

on weekends. 

Setting up the checkpoint consisted of

positioning vans in both breakdown

lanes, rolling out two "wheeled" stop

signs, and opening the circuit breaker

controlling power to the checkpoint

area. The vans had two large, flashing

red lights on the front to signal traffic to

prepare to stop and a series of bright

lights along the side that shone into the

cars as they came to a stop. This

additional lighting was particularly

helpful at night, as the overhead lights

of the checkpoint structure created

deep shadows inside the cars. 

The Border Patrol agents positioned

themselves behind the mobile stop

signs between lanes one and two and

lanes three and four. Each agent

controlled the two lanes passing on

either side. The vehicles were waved

through the checkpoint at 5 to 10 miles

per hour until an agent decided to stop

one. 

While agents looked for vehicles carrying anyone they might recognize as a

felon (a "most wanted" gallery was

posted in the operations anteroom),

they also stopped any vehicle with

"covered or occluded objects in the

backseat (or elsewhere)." Most stops

resulted in a quick survey of the interior

and a few verbal questions and the

vehicle was allowed to continue. 

An agent might require a vehicle to pull

forward to a covered inspection area to

the right of the highway. There, additional agents assisted in inspecting the

vehicle and questioning the occupants.

Dogs were also used in the area to

sniff out drugs and other substances.

When criminal activity was suspected,

the suspects were handcuffed and

removed from the area.

Viewing location at checkpoint

From the border checkpoint location on

I-5 the enumerators were able to see

the nearest lane of traffic with a

downward viewing angle of approximately 18 degrees (figure 1). The

distance from enumerator to car was

approximately 20 feet.

Two obstacles limited the viewing

range: the heavy support girders, both

vertical and diagonal, of the checkpoint

and the Border Patrol van parked in the

right breakdown lane at the stop point.

The enumerators had an effective

viewing range, left to right, of approximately 54 degrees. The distance

between vertical supports was approximately 9 feet. 

2 Assessing Measurement Techniques for Identifying Race Ethnicity and Gender 
Enumerators

Four enumerators (two white females

and two white males) rotated through

observation sessions in pairs. All

enumerators were required to wear

Border Patrol identification badges

during their time on the site. 

Materials

All data were recorded on a survey

collection form containing columns for

date, time, vehicle identification,

window tint, driver and passenger

race/ethnicity and gender classification,

as well as indicators for observational

certainty. As specified, the possible

race/ethnicity classifications were in

accordance with the OMB standards.

An additional classification of

"unknown" was also available (appendix A). 

 

Observation sessions

Day one (Thursday, January 10, 2002)

The first pair of observers, a male and

a female, conducted three sessions on

the first day of the study. The observation times were spread out during

morning, afternoon, and early evening.

In the first session it became apparent

that the limited viewing range, coupled

with the speed of the vehicles during

normal operation, impacted the observers’ ability to collect all data on the

survey collection form. 

The observers could not see license

plates, and the only vehicle identification possible was an occasional

notation by both enumerators such as

"red car" or "blue SUV." A slight break

in traffic flow (three car lengths or

more) gave the opportunity to record

the type of vehicle approaching. These

became the only milestones for assuring the alignment of collected data. 

Following the first 5 minutes of the first

recording session, the fields (L, M, H

for low, medium, high surety) on the

collection form for recording the surety

of each assignment of race/ethnicity

were also ignored. There was insufficient time to record any data other than

the race/ethnicity and gender of the

driver and of any passengers. Due to

the pace and volume of traffic during

the first session, subsequent observation sessions were limited to 30

minutes to maintain the quality of the

recordings.

Day two (Friday, January 12, 2002)

On the second day, two additional

enumerators were trained during the

first morning session. They were then

paired with an enumerator from the

previous day for sessions 5 through 8. 

Due to heavy traffic flow during late

Friday afternoon, the checkpoint was

shut down. During the evening the

enumerators experienced difficulty

viewing into the vehicles when the area

lights were illuminated. As a consequence, the evening sessions were

stopped for the day. 

This experience indicated that the use

of enumerators to record data on

passing vehicles at night would not be

productive. This phenomenon could

apply to controlled land border crossings as well.

 Assessing Measurement Techniques for Identifying Race Ethnicity and Gender 3

Viewing angle of

approximately 18 degrees

Border Patrol Checkpoint site layout

Figure 1
Day three (Saturday, January 13,

2002)

On day three of the study, four

sessions were completed which 

included stoppages for checkpoint

shutdowns. The last session of the day

occurred just before noon. The traffic

flow was so heavy the watch

commander determined that the

checkpoint would be shut down 

for the rest of the afternoon.

Results 

All observational data for each session

and by each enumerator were compiled, resulting in 12 sessions that

represented 3,534 pairs of vehicle

observations. The race/ethnicity and

gender classifications were recoded

into numeric values for further

analyses.

The frequency and percent distributions of the total driver observations for

each classification were summarized

for each session. The enumerators

classified the majority of drivers across

all sessions as "White male" (ranging

from 35% to 60% of all observations

(table 1)). The enumerators classified

more drivers as "White female," than

other nonwhite male or female classifications, across seven sessions (ranging from 17% to 23% of all observations). During five sessions — 4, 6,

8, 9, and 10 — at least one enumerator

in each session classified more drivers

as "Hispanic male" than "White

female." 

Across all sessions, no drivers or

passengers were classified as "Native

Hawaiian/Pacific Islander" or "American Indian/Alaska Native." 

4 Assessing Measurement Techniques for Identifying Race Ethnicity and Gender 

Note: Session 1 occurred on Thursday, 10:30-11:55 a.m.; session 2, Thursday, 3:30-4:00 p.m.; session 3, Thursday, 5:00-5:30 p.m.;

session 4, Friday, 9:15-9:50 a.m.; session 5, Friday, 10:00-10:20 a.m.; session 6, Friday, 11:35 a.m.-12:02 p.m.; 

session 7, Friday, 1:55-2:30 p.m.; session 8, Friday, 2:30-2:37 p.m.; session 9, Saturday, 8:25-8:55 a.m.; session 10, 

Saturday, 9:00-9:30 a.m.; session 11, Saturday, 9:31-9:41 a.m.; and session 12, Saturday, 11:34-11:59 a.m.

Detail may not add to 100% due to rounding.

Total number 421 84 324 401 155 244

Missing 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Unknown 2.6 2.6 2.6 16.7 2.5 2.2 5.5 21.2 0.6 1.9 2.5 2.0

Asian female 2.1 2.1 1.2 0.0 3.1 2.2 2.7 0.7 3.2 3.2 3.3 2.9

Asian male 8.8 11.4 10.7 4.8 1.5 3.4 12.5 4.7 3.9 2.6 4.1 2.9

Hispanic female 2.1 1.0 0.0 0.0 4.0 4.0 0.7 2.0 4.5 5.2 2.5 4.5

Hispanic male 13.1 9.3 7.1 21.4 21.6 22.2 11.0 21.9 19.4 18.7 16.4 21.3

Black female 0.7 0.7 0.0 0.0 0.9 1.5 0.7 0.2 0.6 0.6 0.0 0.0

Black male 2.1 2.4 4.8 4.8 2.5 1.9 2.5 1.0 2.6 1.9 2.9 2.5

White female 17.6 18.5 15.5 16.7 17.6 18.2 18.0 13.5 20.0 20.6 21.3 20.5

White male 50.8% 52.0% 56.0% 35.7% 46.3% 44.4% 46.4% 34.7% 45.2% 45.2% 47.1% 43.4%

One Two One Two One Two One Two One Two One Two

Session 7 Session 8 Session 9 Session 10 Session 11 Session 12

Total number 555 448 323 240 250 89

Missing 0.0 0.0 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Unknown 4.0 2.0 3.3 2.2 3.1 1.2 0.8 0.8 2.8 3.6 2.2 27.0

Asian female 1.4 1.4 2.0 1.1 1.5 1.5 1.3 0.8 2.4 2.4 3.4 3.4

Asian male 3.6 3.2 4.0 5.1 2.5 4.0 5.4 5.8 2.0 4.4 3.4 4.5

Hispanic female 0.5 0.5 0.4 0.9 1.2 0.9 1.7 2.9 3.6 0.8 4.5 2.2

Hispanic male 12.8 8.8 7.8 11.2 12.4 11.8 17.1 18.3 15.2 8.8 21.3 7.9

Black female 1.1 0.5 0.7 0.4 0.0 0.0 0.4 0.4 0.4 0.4 0.0 0.0

Black male 2.7 3.1 2.5 2.2 3.1 4.0 3.8 2.5 2.8 2.4 2.2 2.2

White female 22.9 23.1 19.2 19.4 16.7 17.0 16.7 16.7 17.6 18.4 12.4 16.9

White male 51.0% 57.3% 59.8% 57.4% 59.4% 59.4% 52.9% 51.7% 53.2% 58.8% 50.6% 36.0%

One Two One Two One Two One Two One Two One Two

Session 1 Session 2 Session 3 Session 4 Session 5 Session 6

Table 1. Observations at Border Patrol checkpoint, January 2002
The enumerators classified a majority

of vehicles across all sessions as

having only a driver with no passengers (table 2). The percent of driveronly vehicle observations ranged from

60% of the total weekend observations

to 96% of the weekday observations. 

Across the majority of reported observations of drivers with passengers, the

race/ethnicity classification of the driver

matched the race/ethnicity classification of the passenger(s). The percent

of race/ethnicity observed matches of

drivers and passengers ranged from

80% to 100% of all combined

observations.

Discussion

The degree of inter-rater agreement for

driver race/ethnicity classification was

relatively high across all sessions

(table 3). Combined, the paired

enumerators agreed on the race and

ethnicity categorization of observed

persons in 77% of the cases. The

checkpoint study was limited by the

constraints of the enumerators’

position at the site location and the

continuous flow of the traffic being

observed. 

Detroit (Wayne County) Metropolitan

Airport

Study location

The Department of Justice selected the

Detroit Metropolitan Airport for the

observational study. Observation locations and collection times were

restricted by the airport's legal counsel

in consultation with the Detroit Airport

Federal Aviation Administration (FAA)

security chief. Contract personnel were

limited to observations in unsecured

areas of three terminals between 10:00

a.m. and 8:00 p.m. 

Viewing location at airport

Project staff initially visited all possible

viewing locations in the Detroit airport’s

unsecured areas. Ultimately, two clear

viewing locations were found for data

collection. One observation point was

in the Northwest Airlines main terminal.

The terminal consists of two large

ticketing areas (about 12 ticket agent

positions per area) positioned on either

side of the access to the security point.

The Northwest Airlines terminal

manager restricted the enumerators to

a standing position against a wall

approximately 6 feet from the roped

serpentine enclosure that guided

passengers into the security checkpoint. The second observation point

was in the Northwest International

departure. Only one observation

session was conducted at this location

at a departure time when the passenger traffic was substantial enough to

collect an adequate sample. The

viewing location was again within 6 feet

of the roped passenger enclosure.

Sessions were limited to 30 minutes 

to maintain recording quality.

Enumerators

Two enumerators (white female and

white male) conducted all observation

sessions. While arrangements had

been made with local universities for

additional enumerators, the limitations

placed on viewing locations eliminated

the need for additional personnel.

 Assessing Measurement Techniques for Identifying Race Ethnicity and Gender 5

*Drivers with a passenger.

12 244 62.7 91 91.2 244 59.4 99 91.9

11 155 65.8 53 92.5 155 60.0 62 93.5

10 399 64.1 144 95.8 401 74.3 103 99.0

1/12/02 9 324 70.4 96 92.7 324 66.7 108 97.2

8 84 88.1 10 80.0 84 84.5 13 84.6

7 421 78.9 89 93.3 421 80.3 83 96.4

6 142 95.1 7 100.0 142 95.8 6 83.3

5 250 79.2 52 100.0 250 78.0 55 96.4

1/11/02 4 241 82.9 41 97.6 240 81.7 44 95.5

3 323 89.2 35 88.6 323 87.0 42 88.1

2 448 81.9 81 97.5 448 80.4 88 97.7

1/10/02 1 555 86.7% 74 95.9% 555 86.5% 75 93.3%

Percent

matched

Race and ethnicity classified*Percent of

drivers

Total number

of vehicles

Percent

matched

Race and ethnicity classified*Percent of

drivers

Total number

Session of vehicles

Observation set 1 Observation set 2

Table 2. Race and ethnicity observations of drivers and passengers at a Border Patrol checkpoint, 2002

4

3,534

0

0

2

183

0

60

0

159

0

77

1

540

0

17

0

86

1

653

0

1,759

Missing

Total

Unknown 28 7 4 0 11 1 3 0 56 0 110

Asian female 2 10 0 2 2 13 2 44 3 0 78

Asian male 26 3 2 0 45 0 109 4 12 0 201

Hispanic female 0 16 0 1 3 27 1 3 1 0 52

Hispanic male 102 7 8 1 287 2 29 0 21 0 457

Black female 1 5 0 11 1 1 0 1 1 0 21

Black male 9 3 62 1 12 0 1 0 3 0 91

White female 33 565 6 1 9 32 4 7 14 0 671

White male 1,558 36 4 0 169 1 10 1 70 0 1,849

observer A wm wf bm bf hm hf am af u m Total

used by Categories used by observer B

Categories

Table 3. Inter-rater agreement on observations of gender, race, and Hispanic

origin, at a Border Patrol checkpoint during 12 periods
Materials

All data were recorded on a survey

collection form (appendix B) containing

columns for date, time, sampling location, passenger race/ethnicity, gender,

age (adult/ child), type and number of

carry-ons, whether she/he was traveling alone, and an indicator of observational certainty. The race/ethnicity

classifications were in accordance with

the OMB government standards. An

additional classification of "unknown"

was also used. 

Observation sessions (Thursday,

January 31, 2002, through Saturday,

February 2, 2002)

The enumerators conducted four sessions on the first day of the study. Due

to adverse winter weather conditions,

more than half of the day's flights were

canceled and passenger traffic through

the security checkpoints was sporadic.

As weather conditions improved, the

enumerators conducted 30-minute

observation sessions during the morning, afternoon, and early evening. After

the first 5 minutes of session 1 observations, it was apparent that the close

viewing range made identification

certainty "high" and this category was

ignored in subsequent recordings.

Three observation sessions were conducted in the main terminal and one

session was conducted in the international departure terminal. Three additional observation sessions were

conducted on each of the second and

third days in the main terminal. 

Results 

All observational data for each session

and each enumerator were compiled

resulting in 10 sessions representing

1,928 pairs of departing passenger

observations. The gender, race/ethnicity, and carry-on classifications were

recoded into numeric values for further

analyses. 

The frequencies and percents of the

total observations for each race/ethnicity and gender classification made by

each observer were summarized for

each session. The majority of departing

passengers observed in all 10 sessions

were classified as white (from approximately 78% to 94% of the total observations). The majority of departing

passengers across 9 of the 10

sessions were white males (from

approximately 41% to 58% of the total

observations (table 4)). White females

were observed more frequently than

other male or female classifications

across all 10 sessions (from approximately 33% to 49% of the total observations). More white females than

white males were observed during

session 8. Across all sessions, only two

passengers were classified as American Indian/Alaska Native, and none

was classified as Native Hawaiian/

Pacific Islander. 

6 Assessing Measurement Techniques for Identifying Race Ethnicity and Gender 

Note: Session 1 occurred on Thursday 11:00-11:32 a.m.; session 2, Thursday, 1:40-2:10 p.m.; session 3, Thursday, 3:35-4:10

p.m.; session 4, Thursday, 6:27-6:57 p.m.; session 5, Friday, 10:40-11:10 a.m.; session 6, Friday, 12:40-1:12 p.m.; session 7,

Friday, 5:17-5:47 p.m.; session 8, Saturday, 10:10-10:40 p.m.; session 9, Saturday, 12:55-1:35 p.m.; session 10, Saturday,

3:55-4:25 p.m. 

Detail may not add to 100% due to rounding.

*Session 1 included two Native American females who were omitted from the table.

Total number 234 198 216 144 126

Missing 0.0 1.3 0.0 1.5 0.0 0.0 0.0 0.7 0.0 0.0

Unknown 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Asian female 0.0 0 2.5 2.5 0.5 0.5 4.2 4.2 4.8 4.8

Asian male 4.7 4.7 2.0 2.0 0.9 0.9 4.2 4.2 7.1 7.1

Hispanic female 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Hispanic male 0.9 0.9 0.5 1.5 1.4 2.3 0.7 1.4 0.8 0.8

Black female 3.0 2.6 3.0 2.5 0.9 0.9 2.1 4.2 5.6 5.6

Black male 2.1 1.7 0.5 0.5 2.3 2.3 2.8 2.1 4.0 3.2

White female 35.5 35.0 40.9 39.4 49.1 49.1 38.2 35.4 35.7 37.3

White male 53.8% 53.8% 50.5% 50.0% 44.9% 44.0% 47.9% 47.9% 42.1% 41.3%

One Two One Two One Two One Two One Two

Session 6 Session 7 Session 8 Session 9 Session 10

Total number 286 234 148 180 162

Missing 0.0 2.1 0.0 0.9 2.7 2.0 1.1 0.0 0.0 0.0

Unknown 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Asian female 1.0 0.3 1.7 2.1 0.7 0.7 1.1 1.7 0.6 0.6

Asian male 2.1 2.1 1.7 1.7 2.7 2.7 2.2 2.2 3.1 3.1

Hispanic female 0.3 2.4 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Hispanic male 1.4 2.1 0.0 0.0 0.0 0.0 0.0 0.0 0.6 1.2

Black female 1.7 1.7 4.3 3.4 2.7 2.7 0.0 0.0 1.2 1.2

Black male 0.7 0.7 5.6 5.6 4.7 4.7 2.8 2.8 2.5 2.5

White female 39.5 35.7 33.3 32.9 33.8 33.1 36.7 35.6 42.6 42.6

White male 53.1% 52.8% 53.4% 53.4% 52.7% 54.1% 56.1% 57.8% 49.4% 48.8%

One Two One Two One Two One Two One Two

Session 1* Session 2 Session 3 Session 4 Session 5

Table 4. Observations at an airport, 2002
Discussion

The 10 sessions conducted over 3

days in this pilot observational study

allowed the observer to assess the

inter-rater reliability of race/ethnicity

and gender identification. Given the

proximity of the observers to the

passengers, race/ethnicity, gender, and

age identifications were fairly easy to

determine and the inter-rater agreement was good (table 5). In the airport

the paired observers agreed with their

race and ethnicity categorization of

persons in 97% of the cases

(1,862/1,928). 

Recommendations for future 

observational studies

Gaining access to sites and viewing

areas with the best proximity for observational studies was the most difficult

aspect of this project. To assess the

validity of these observational classifications, sessions would also require

additional data based on the subjects

self-reports of their race/ethnicity. 

An actual border crossing, where each

car is stopped, would be more suitable

than a checkpoint. Using such a

location would allow interviews of a

random sample of drivers concerning

their demographic characteristics and

a comparison of the results to

enumerators' classifications.

A comprehensive airport study requires

access to all areas (gates, security

checkpoints [from both sides], concourses, entrances, and so on).

Airports with various designs and open

or less restricted access need to be

selected for future studies to provide

an opportunity to undertake a comparison of sampling designs, and to allow

for the collection of demographic data

from airport users. 

 Assessing Measurement Techniques for Identifying Race Ethnicity and Gender 7

4

1,928

0

18

0

0

0

29

0

55

0

7

0

21

0

45

0

48

2

725

4

980

Missing

Total

Unknown 0 0 0 0 0 0 0 0 0 0 0

Asian female 0 0 0 0 0 1 0 27 0 1 29

Asian male 0 0 0 0 1 0 54 0 0 0 55

Hispanic female 0 0 0 0 0 1 0 0 0 0 1

Hispanic male 2 0 0 0 10 0 1 0 0 0 13

Black female 0 2 0 42 1 0 0 1 0 0 46

Black male 0 0 48 0 2 0 0 0 0 1 51

White female 10 716 0 3 2 4 0 1 0 10 746

White male 964 5 0 0 5 1 0 0 0 6 981

observer A wm wf bm bf hm hf am af u m Total

used by Categories used by observer B

Categories

Table 5. Inter-rater agreement on observations of gender, race, and Hispanic

origin, at an airport during 10 periods

Appendix A. Survey collection form for recording observations at checkpoint.

Appendix B. Survey collection form for recording observations at airport.

Race Code A=Asian B=Black/African American H=Native Hawaiian/Pacific Islander L=Hispanic/Latino 

N=Native American/Alaska Native W=White U=Unknown

Y N YN / L M H L M H

Y N YN / L M H L M H

Y N YN / L M H L M H

Y N YN / L M H L M H

Y N YN / L M H L M H

Y N YN / L M H L M H

Y N YN / L M H L M H

Y N YN / L M H L M H

Y N YN / L M H L M H

Y N YN / L M H L M H

Y N YN / L M H L M H

Y N YN / L M H L M H

Y N YN / L M H L M H

Y N YN / L M H L M H

Y N YN / L M H L M H

Y N YN / L M H L M H

Y N YN / L M H L M H

Y N YN / L M H L M H

Pass. Sure? Comments

Race

Child 

Sex/#

Adult 

Sex/#

# of 

Pass.

Driver Sure?

S &R?

Window

Tint?

Vehicle

US?

Vehicle

ID

Date Time

Race Code A=Asian B=Black/African American H=Native Hawaiian/Pacific Islander L=Hispanic/Latino N=Native

American/Alaska Native W=White U=Unknown Carry on Code BC=Briefcase BP=Backpack CB=Clothes Bag CP=Computer

HB=Handbag L=Luggage Piece O=Other (Explain in Comments) SB=Shopping Bag

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Travel Comments

Alone

Age Carry-ons

Group

Passenger Sure?

Race/Sex

Sampling

Location

Observation

Point

Date Time
Sources for further information

Final Report of the New Jersey State

Review Team Regarding Allegations of

Racial Profiling, July 1999.

General Accounting Office (GAO). Racial

profiling: Limited data available on motorist

stops. March 2000. (Report to the Honorable James E. Clyburn, Chairman,

Congressional Black Caucus.)

Harris, David. “Stories, the Statistics, and

the Law: ‘Why Driving While Black’

Matters, Minnesota Law Review. Volume

84, Issue 2. December 1999: 265-325.

Lamberth, John. 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. November 11, 1994.

<http://www.lamberthconsulting.com/

research_articles.asp>.

Montgomery County, Maryland Department

of Police. Traffic Stop Data Collection Analysis: First Report Covering the Period October 2000 through March 2001. October

31, 2001.

. Traffic Stop Data Collection

Analysis: Second Report Covering the

Period April 2001 through September

2001. January 30, 2002.

. Traffic Stop Data Collection

Analysis: Third Report Covering the Period

October 2001 through March 2002. May

31, 2002.

Office of the Attorney General. Speed

Violation Survey of the New Jersey

Turnpike: Final Report. Trenton, NJ.

December 2001.

San Diego Police Department. Vehicle

Stop Study: Mid-Year Report. September

21, 2000. 

San Jose Police Department. Vehicle Stop

Demographic Study. December 1, 2000.

(for the period June 1999 to July 2000).

8 Assessing Measurement Techniques for Identifying Race Ethnicity and Gender 

The Bureau of Justice Statistics 

is the statistical agency of the 

U.S. Department of Justice. 

Lawrence A. Greenfeld is director.

Humanalysis Inc. collected the data

and provided the information for this

report. At BJS, Steven K. Smith and

Carol J. DeFrances prepared this

report. Carolyn C. Williams produced

and edited the report. 

The following individuals provided

assistance to Humanalysis personnel

as they conducted the border checkpoint and airport observational

studies: James St. Hilaire from INS,

Stephen Gonzales from INS, Wes

Knippler from INS, and Delphine

Fairbanks from the Detroit Municipal

Airport.

January 2003, NCJ 196855