National Academies Press: OpenBook

Measuring Racial Discrimination (2004)

Chapter:Index

« Previous: Appendix B: Biographical Sketches
Suggested Citation:"Index." National Research Council. 2004. Measuring Racial Discrimination. Washington, DC: The National Academies Press. doi: 10.17226/10887.
×

Index

A

Accuracy issue, 109

Across-domains cumulative effects studies, 251–253

cumulative disadvantage and racial discrimination, 224

Across-generations cumulative effects studies

cumulative disadvantage and racial discrimination, 223–224

Adarand Constructors, Inc. v. Peña, 53

Administrative records

indicators of discrimination from, 9–10

and the reporting on multiple races, 220

Adverse impact discrimination, detecting, 160–161

African Americans, 15

Agencies

program, 248–251

research, 251–253

Ambiguity

of prejudice, 60

of race, 33–34

Ambivalent attitudes about race, 60, 183–185

Anti-Defamation League, 174

Assessment

of racial discrimination causal inference, 77–89

of traffic-violating behaviors, 193–194

Attacks, physical, 58

Attitudes Toward Blacks Scale, 100

Attitudinal indicators of discrimination, 9–10, 162–185

black and white Americans’ perceptions of discrimination and ambivalent attitudes about race, 182–185

challenge of direct measurement of discrimination, 163–165

imperfect relationship to behaviors, 168–169

scale measures used in surveys, 175–180

sources of observational data, 165–175

Audit studies

accuracy issue, 109

combining features of laboratory and audit studies, 110–112

limits of, 108–114

methodology, 104–105

validity issue, 109–114

Auditor heterogeneity, 113–114

Automatic discrimination, 58–61

Avenues through which cumulative discrimination may occur

cumulative disadvantage and racial discrimination, 227–233

Avoidance, 57

Suggested Citation:"Index." National Research Council. 2004. Measuring Racial Discrimination. Washington, DC: The National Academies Press. doi: 10.17226/10887.
×

B

Behavior

discriminating, effect of psychological mechanisms on measures of, 100–101

Behavioral indicators of discrimination, 9–10, 162–185

black and white Americans’ perceptions of discrimination and ambivalent attitudes about race, 182–185

challenge of direct measurement of discrimination, 163–165

scale measures used in surveys, 175–180

sources of observational data, 165–175

Behaviors

assessment of traffic-violating, 193–194

imperfect relationship of attitudes to, 168–169

Benefits of profiling, 200–201

Biases, reporting, 170–171

Biological definition of race, 25–26

Black Like Me, 78n

Blacks’ perceptions of discrimination, 182

BLS. See Bureau of Labor Statistics

Brookings Institution, 48

Brown v. Board of Education, 152

Bureau of Labor Statistics (BLS), 45, 173, 209, 216, 253

C

Causal inferences

counterfactuals and potential outcomes, 78–81

drawing, 78–88

illustrating causality, 80–81

roles of randomization and manipulation, 83–85

smoking and lung cancer, 86–87

study design and statistical methods, 81–83

weighing evidence from multiple studies, 85–88

Causation, not prediction, 199–200

Census data, 191–192

Citizen surveys, 194

Civil Rights Act of 1964, 16, 48, 87

Title VI, 152

Title VII, 50–51, 64, 244–245

Civil Rights Act of 1968, 106

Civil Rights Act of 1991, 52

Civil rights cases, rules for combining multiracial data for, 218

Civil War, 228

Combining features of laboratory and audit studies, 110–112

Combining multiracial data for civil rights cases

rules for, 218

Commissioned papers, 19

Committee on National Statistics, 16, 210

Comparisons, internal departmental, 194

Concept of cumulative discrimination, 225–227

cumulative disadvantage and racial discrimination, 225–227

current legal standards, 226

defining, 225

episodic discrimination, 226

transmission of, 226

See also Cumulative discrimination

Concepts, 23–70

defining discrimination, 4–5, 39–54

defining race, 2–3, 25–38

theories of discrimination, 55–70

Consequences of a racially biased society

cumulative disadvantage and racial discrimination, 231–233

Constitutional Convention of 1787, 27

Contexts in which cumulative discrimination may occur

cumulative disadvantage and racial discrimination, 227–233

Costs of profiling, 200–201

Counterfactuals and potential outcomes, 78–81

CPS. See Current Population Survey

Criminal justice, 46–47

life-course theory of cumulative disadvantage, 233–234

Cumulative disadvantage, 68–69

across domains, 224, 229–231

across generations, 223–224

across processes within a domain, 224

avenues through which cumulative discrimination may occur, 227–233

broader consequences of a racially biased society, 231–233

concept of cumulative discrimination, 225–227

Suggested Citation:"Index." National Research Council. 2004. Measuring Racial Discrimination. Washington, DC: The National Academies Press. doi: 10.17226/10887.
×

cumulative discrimination across generations, 227–228

discrimination across processes within a domain, 228–229

effects cumulating across generations and through history, 68

effects cumulating through an individual’s life across different domains, 68–69

effects cumulating through an individual’s life sequentially within any one domain, 69

life-course theory of, 233–234

measuring cumulative discrimination, 238–245

models and theories of cumulative disadvantage, 233–238

and racial discrimination, 11–12, 223–246

Cumulative discrimination, 11–12

across generations, 227–228

Cumulative effects

across generations and through history, 68

through an individual’s life across different domains, 68–69

through an individual’s life sequentially within any one domain, 69

within-domain and across-domain, 251–253

Current outcomes estimating from past events, 243–244

Current Population Survey (CPS), 8, 210, 220

D

Data access and use, facilitating, 250–251

Data collection and research, 203–253

cumulative disadvantage and racial discrimination, 11–12, 223–246

measurement of race by the U.S. government, 5–11, 205–222

research—next steps, 12–13, 247–253

sources on racial profiling, 189–191

Decennial census, 30

Decomposition as racial discrimination, 128

Definitions of discrimination, 4–5

movement from episodic to dynamic, 68–69

role of cumulative disadvantage in, 68–69

Departmental comparisons, internal, 194

Desert Palace v. Costa [No. 02-679], 120

Designs, 92–93, 103

experimental, 82–83

Differences-in-differences approach, 149

Differential outcomes by race, 44–49

criminal justice, 46–47

education, 44–45

employment and income, 45–46

health care and health outcomes, 47–48

housing markets and mortgage lending, 47

interpreting, 48–49

Direct measurement of discrimination, 163–165

Disadvantaged racial groups, 4n, 17, 42

Discriminating behavior effect of psychological mechanisms on measures of, 100–101

Discriminating firms, model of, 134

Discrimination

across domains, 229–231

across processes within a domain, 228–229

blacks’ perceptions of, 182

classic laboratory experiment on, 96–97

disparate impact, 51–52

versus disparities, 195–196

domains operating in, 66–68

episodic, 226

examples of natural experiments to study, 149–153

intentional and explicit, 56–58

organizational processes of, 63–65

statistical discrimination and profiling, 61–63

structural, 63

subtle, unconscious and automatic, 58–61

theories of, 55–70

types of, 56–65

whites’ perceptions of, 183

See also Racial discrimination

Discrimination defined, 4–5, 39–54

differential outcomes by race, 44–49

legal definition, 49–53

limiting the discussion, 42–44

Discrimination in Elementary and Secondary Education, 21

Discrimination law regarding governmental actions, 52–53

Suggested Citation:"Index." National Research Council. 2004. Measuring Racial Discrimination. Washington, DC: The National Academies Press. doi: 10.17226/10887.
×

Disparate impact discrimination, 4, 40, 51–52

Disparate outcomes

data sources on racial profiling, 189–191

establishing in profiling situations, 189–195

Disparate selection rates, methods for estimating, 191–195

Disparate treatment discrimination, 4, 40, 50–51

Disparities versus discrimination, 195–196

Domains in which discrimination operates, 66–68

map of potential points of discrimination within five domains, 67

See also Cumulative effects

Dynamic definitions of discrimination, role of cumulative disadvantage in, 68–69

E

Eastern European Jews, 2

Ecosocial theory of cumulative disadvantage in public health, 234–236

Education, 44–45

example of a natural experiment to study discrimination, 152–153

EEOC. See Equal Employment Opportunity Commission

Effective profiles, 197–200

developing, 197–200

inadequate data, 198–199

prediction, not causation, 199–200

Effectiveness, standards for, 200

Embodied social signification, 26

Employment and income, 45–46

Episodic definitions of discrimination, role of cumulative disadvantage in, 68–69

Episodic discrimination, 226

Equal Employment Opportunity Commission (EEOC), 153

Estimating an effect of discrimination, inferential target, 109–113

Estimating current outcomes from past events, 243–244

Estimating disparate selection rates

assessment of traffic-violating behaviors, 193–194

census data, 191–192

citizen surveys, 194

internal departmental comparisons, 194

methods for, 191–195

observational data, 192–193

Ethnicity in 2000 (C2SS), household data on, 215

Evidence from multiple studies, 85–88

Experimental designs, 82–83, 90–91

Experimental effects, translating, 102

Experimental methods for assessing discrimination, 90–117

field experiments, 7, 103–115

laboratory experiments, 6, 92–102

in surveys about race, 168

Experiments using to measure racial discrimination, 91–92

Explicit discrimination, 56–58

Explicit racism, measures of, 179–180

Exposure to discrimination, identifying over time, 241–242

Extermination, 58

External validity, 82

F

Facilitating data access and use, 250–251

Fair Housing Act of 1968, 47–48, 106

FBI, 46n

Federal classification standards, 30–33

Federal Executive Order 11246, 48

Federal statistics, racial categories in, 29–33

Feedback models of cumulative

disadvantage, labor market, 237–238

Field experiments, 7, 103–115

audit or paired-testing methodology, 104–105

design, 103

housing audits, 106–107

key examples, 105–108

limits of audit studies, 108–114

Firms

discriminating, 134

nondiscriminating, 134

Fisher, R.A., 84

G

Gallup Organization, 182

Gender segregation of jobs, 136

General Social Survey (GSS), 9, 162, 168, 173, 180

Suggested Citation:"Index." National Research Council. 2004. Measuring Racial Discrimination. Washington, DC: The National Academies Press. doi: 10.17226/10887.
×

Generations. See Cumulative effects

Government data on race and ethnicity, 213–217

2000 census, 213–216

ongoing research, 216–217

race in other U.S. government surveys, 216

Governmental actions, discrimination law regarding, 52–53

Governmental administrative data, 173–174

Griffin, John Howard, 78n

Griggs v. Duke Power Co., 40n

GSS. See General Social Survey

H

HDS. See Housing Discrimination Study of 2000

Health care

example of a natural experiment to study discrimination, 151–152

and health outcomes, 47–48

Health Interview Survey (HIS), 216, 219

High School and Beyond data, 239

Hiring decisions in the labor market, 130–137

model of a discriminating firm, 134

model of a nondiscriminating firm, 134

HIS. See Health Interview Survey

“Hispanic,” 30

Hispanic origin population

in the United States in 2000, 213

History. See Cumulative effects

“Honorary” whites, 29n

Household data on race and ethnicity in 2000 (C2SS), 215

Housing audits, 106–107

Housing Discrimination Study of 2000 (HDS), 105

Housing markets and mortgage lending, 47

HUD. See U.S. Department of Housing and Urban Development

I

Identification. See Self-identification of race

Illustrating causality, 80–81

Improving survey measures, 171–173

methodological improvements, 171–172

other improvements, 172–173

In-depth interviews, 175

Inadequate data, 198–199

Income and employment, 45–46

Inconsistent reporting, 34–36

Indicators of discrimination from surveys and administrative records, 9–10

Indirect prejudice, 59

Individual rights, 197n

Inferential targets estimating an effect of discrimination, 109–113

Inferring discrimination from statisticalanalysis of observational data, 128–137

Information on the occurrence of discrimination, using identifying, 244–245

Institute of Medicine, 48

Institute on Race and Poverty, 190n

Intentional discrimination, 56–58

Internal departmental comparisons, 194

Internal validity, 82

Interpersonal relations surveys, 165–173

Interpreting decomposition, 123–125

Italians, 2

J

Jews, Eastern European, 2

Jobs, gender segregation of, 136

L

Labor markets

example of a natural experiment to study discrimination, 149–151

feedback models of cumulative disadvantage, 237–238

hiring decisions in, 130–137

See also Past labor market discrimination

Laboratory experiments, 6, 92–102

classic laboratory experiment on discrimination, 96–97

design, 92–93

key examples, 95–99

limitations of laboratory experiments, 99–102

measuring racial discrimination, 94–95

strengths of, 93–94

translating experimental effects, 102

Suggested Citation:"Index." National Research Council. 2004. Measuring Racial Discrimination. Washington, DC: The National Academies Press. doi: 10.17226/10887.
×

Legal definition of discrimination, 49–53

discrimination law regarding governmental actions, 52–53

disparate impact discrimination, 51–52

disparate treatment discrimination, 50–51

Legal standards

comparison with the four types of discrimination, 65–66

current, 226

Life-course theory of cumulative disadvantage, criminal justice, 233–234

Limitations

of audit studies, 108–114

effect of psychological mechanisms on measures of discriminating behavior, 100–101

of laboratory experiments, 99–102

of natural experiments, 153–154

Litigation, statistical analysis for, 119–120

Longitudinal data used to draw inferences about discrimination, 148–154

Lung cancer and smoking, 86–87

M

Manipulation, role of, 83–85

Mass killings, 58

Matching score methods, 146–147

Matrix of race, 37

Measurement of race, 33–37, 189–196

ambiguity of race, 33–34

disparities versus discrimination, 195–196

establishing disparate outcomes in profiling situations, 189–195

of explicit racism, 179–180

inconsistent reporting, 34–36

of modern racism, 176–179

multiple indicators of racial identification, 36–37

regarding race, 33–37

self-identification of race, 36

Measurement of race by the U.S. government, 5–11, 205–222

government data on race and ethnicity, 213–217

history, 206–208

issues in the reporting of data on multiple races, 217–221

standards for the collection of race and ethnicity data, 208–213

Measuring cumulative discrimination, 238–245

cumulative disadvantage and racial discrimination, 238–245

difficulties measuring cumulative discrimination, 239–240

estimating current outcomes from past events, 243–244

identifying exposure to discrimination over time, 241–242

tabulating outcomes over time, 240–241

using identifying information on the occurrence of discrimination, 244–245

Measuring racial discrimination, 5–11, 94–95

field experiments, 7

indicators of discrimination from surveys and administrative records, 9–10

laboratory experiments, 6

racial profiling as an illustrative example, 10–11

statistical analysis of observational data and natural experiment, 7–9

Methodological factors, 71–202, 169–170

attitudinal and behavioral indicators of discrimination, 9–10, 162–185

causal inference and the assessment of racial discrimination, 77–89

experimental methods for assessing discrimination, 90–117

illustration of methodological complexity—racial profiling, 10–11, 186–202

improving, 171–172

measurement issues, 189–196

profiling in the context of terrorism, 196–202

racial profiling as an illustration of, 10–11, 186–202

statistical analysis of observational data, 7–9, 118–161

“Mexican,” 30

Mexican-American Legal Defense and Educational Fund, 174

Minority groups, 4n, 42

Models of cumulative disadvantage, 233–238

criminal justice—life-course theory of cumulative disadvantage, 233–234

Suggested Citation:"Index." National Research Council. 2004. Measuring Racial Discrimination. Washington, DC: The National Academies Press. doi: 10.17226/10887.
×

labor market—feedback models, 237–238

public health—ecosocial theory, 234–236

Moderator variables, 93

Modern racism, measures of, 176–179

Modern Racism Scale, 176–178

Mortgage lending and housing markets, 47

Moving to Opportunity studies, 230

Multi-City Study of Urban Inequality, 135n, 185

Multiple indicators of racial identification, 36–37

Multiple races, reporting data on, 217–221

Multiple studies, weighing evidence from, 85–88

Multiracial survey data publication, 219

Murphy, Susan, 242

N

National Center for Education Statistics (NCES), 210, 212

National Center for Health Statistics (NCHS), 210, 216, 219–220

National Conference of State Legislatures, 187n, 190n

National Content Survey, 210–211

National Fair Housing Alliance (NFHA), 173

National Institutes of Health, 5, 89, 251

National Longitudinal Survey of Youth, 10, 12, 181, 239, 246

National Longitudinal Surveys of Labor Market Behavior, 253

National Race and Politics Study, 168

National Research Council, 210

National Science Foundation, 5, 88–89, 251

Natural experiments to study discrimination, 148–154

education, 152–153

health care, 151–152

labor market, 149–151

limitations of, 153–154

statistical analysis of, 7–9

NCES. See National Center for Education Statistics

NCHS. See National Center for Health Statistics

Next steps, 12–13

NFHA. See National Fair Housing Alliance

Nondiscriminating firms, model of, 134

Nongovernmental data, 174–175

Nonwhite groups, 42, 49

O

Observational data, 192–193

detecting adverse impact discrimination, 160–161

effects of discrimination in other domains, 156–15

effects of past labor market discrimination on factors in hiring, 155–156

governmental administrative data, 173–174

in-depth interviews, 175

inferring discrimination from statistical analysis of, 128–137

nongovernmental data, 174–175

possible solutions to problems of using statistical models to infer discrimination, 141–154

problems with measuring discrimination by fitting statistical models to, 137–141

sources of, 165–175

statistical analysis for research and litigation, 119–120

statistical analysis of, 7–9, 118–161

statistical decompositions of racial differences, 121–128

surveys of interpersonal relations and racial discrimination, 165–173

Observational studies, 83

Office of Civil Rights, 248

OMB. See U.S. Office of Management and Budget

OMB revised standards of 1997 for the collection of race and ethnicity data, 212–213

OMB standards of 1977 for the collection of race and ethnicity data, 208–209

Omitted variables bias, 8, 137–140

using an indicator of productivity to address, 142–145

Organizational processes, 63–65

Outcomes tabulating over time, 240–241

Suggested Citation:"Index." National Research Council. 2004. Measuring Racial Discrimination. Washington, DC: The National Academies Press. doi: 10.17226/10887.
×

P

Paired-testing methodology, 104–105

Panel data, 251–253

methods for assessing, 147–148

Panel Study of Income Dynamics, 10, 12,181, 239, 246

Panel tasks, 1–2, 16

Papers commissioned, 19

Past labor market discrimination, effects on factors in hiring, 155–156

Physical attacks, 58

Pitfalls in statistical decomposition, 125–128

Points of discrimination within five domains, map of potential, 67

Police Foundation, 190n

Population controls, reporting data on multiple races, 220–221

Possible solutions to problems using statistical models to infer discrimination, 141–154

Potential outcomes and counterfactuals, 78–81

Prediction, not causation, 199–200

Princeton Survey Research Associates, 182

Priority research topics, 248–250

Problems, measuring cumulative discrimination, 239–240

Problems, measuring discrimination by fitting statistical models to observational data, 137–141

omitted variables bias, 137–140

sample selection bias, 140–141

Simpson’s paradox, 138–139

Processes within a domain, cumulative disadvantage and racial discrimination, 224

Profiling in the context of terrorism, 61–63, 196–202

costs and benefits of profiling, 200–201

data sources on, 189–191

developing effective profiles, 197–200

establishing disparate outcomes in specific situations, 189–195

illustration of methodological complexity, 10–11, 186–202

as an illustrative example, 10–11

trade-offs, 201–202

Program agencies, 248–251

facilitating data access and use, 250–251

priority research topics, 248–250

Propensity score methods, 104, 146–147

Psychological mechanisms, effect on measures of discriminating behavior, 100–101

Public health, ecosocial theory of cumulative disadvantage, 234–236

Publication and release of data on multiple races, 218–219

R

Race

in 2000 (C2SS), household data on, 215

ambivalent attitudes about, 183–185

differential outcomes by, 44–49

and Hispanic origin population in the United States in 2000, 213

matrix of, 37

self-identification of, 36

social construction of, 26–27

in U.S. government surveys, 216

in the United States, 27–29

Race and Ethnic Targeted Test, 210, 212

Race defined, 2–3, 23, 25–38

biological definition, 25–26

measurement issues, 33–37

race in the United States, 27–29

social construction of race, 26–27

Race-specific intercepts with regression models, 121–123

Racial categories in federal statistics, 29–33

decennial census, 30

federal classification standards, 30–33

in U.S. census, 31

Racial classifications

objective, 26

subjective, 27

Racial differences, statistical decompositions of, 121–128

Racial differentials in compensation, case of professional athletes, 145

Racial discrimination, 11–12, 39–42, 223–246

across domains, 224, 229–231

across generations, 223–224

across processes within a domain, 224, 228–229

broader consequences of a racially biased society, 231–233

cumulative discrimination across generations, 227–228

Suggested Citation:"Index." National Research Council. 2004. Measuring Racial Discrimination. Washington, DC: The National Academies Press. doi: 10.17226/10887.
×

decomposition and residual “effects” as, 128

measuring, 5–11

surveys of, 165–173

Racial profiling. See Profiling in the context of terrorism

Racially biased society, broader consequences of, 231–233

Racism

measures of explicit, 179–180

measures of modern, 176–179

Randomization, role of, 83–85

Recommendations, 3, 6–7, 9–10, 12, 116–117, 160, 181, 222, 246

Regression models

race-specific, 122–123

with race-specific intercepts, 121–122

used to decompose racial differences, 124

Reporting biases, 170–171

Reporting of data on multiple races, 217–221

administrative data, 220

population controls, 220–221

publication and release of data, 218

publication of multiracial survey data, 219

rules for combining multiracial data for civil rights cases, 218

time-series data, 220

Research agencies, 251–253

panel data, 251–253

within-domain and across-domain cumulative effects studies, 251–253

Research on race and ethnicity

cumulative disadvantage and racial discrimination, 11–12, 223–246

by federal statistical agencies, 209–212

measurement of race by the U.S. government, 5–11, 205–222

next steps, 12–13, 247–253

priority topics, 248–250

program agencies, 248–251

statistical analysis for, 119–120

See also Data collection and research

Residual “effects” as racial discrimination, 128

Roper Center, 168

Rules for combining multiracial data for civil rights cases, 218

S

Sample selection bias, 8, 140–141

Scale measures used in surveys, 175–180

measures of explicit racism, 179–180

measures of modern racism, 176–179

Score methods matching and propensity, 146–147

Segregation, 57–58

Self-identification of race, 36

Seniority issues, 64

Sequential effects. See Cumulative effects

Seuss, Dr., 77–78

Simpson’s paradox, 137–139

Smith, Thomas, 162–173

Smoking and lung cancer, 86–87

Sneetches, The, 77–78

Social-cognitive approach, 26

Social construction of race, 26–27

Social Security Act of 1935, 152

Social signification embodied, 26

Solutions to problems of using statistical models to infer discrimination, 141–154

matching and propensity score methods, 146–147

natural experiments, 148–154

panel data methods, 147–148

racial differentials in compensation—case of professional athletes, 145

use of longitudinal data to draw inferences about discrimination, 148–154

using an indicator of productivity to address the omitted variables problem, 142–145

Sources of observational data, 165–175

Standards for effectiveness, 200

Standards for Maintaining, Collecting and Presenting Federal Data on Race and Ethnicity, 212

Standards for the collection of race and ethnicity data, 208–213

OMB revised standards of 1997, 212–213

OMB standards of 1977, 208–209

research by federal statistical agencies on race and ethnicity, 209–212

See also Legal standards

Statistical analysis of observational data, 7–9

Suggested Citation:"Index." National Research Council. 2004. Measuring Racial Discrimination. Washington, DC: The National Academies Press. doi: 10.17226/10887.
×

developing statistical models, 129–130

examples—hiring decisions in the labor market, 130–137

gender segregation of jobs, 136

inferring discrimination from, 128–137

for research and litigation, 119–120

Statistical decompositions of racial differences, 121–128

decomposition and residual “effects” as racial discrimination, 128

interpreting the decomposition, 123–125

over time, 126–127

race-specific regression models, 122–123

regression models with race-specific intercepts, 121–122

statistical decompositions over time, 126–127

two pitfalls in statistical decomposition, 125–128

use of regression models to decompose racial differences, 124

Statistical Directive Number 15, 208

Statistical discrimination, 61–63

Statistical methods, 81–83

Statistical models, developing, 129–130

Structural discrimination, 63

Study design and statistical methods, 81–83

experimental designs, 82–83

observational studies, 83

Subtle discrimination, 58–61

Survey limitations, 169–171

methodological factors, 169–170

reporting biases, 170–171

Survey measures, means of improving, 171–173

Surveys

citizen, 194

indicators of discrimination from, 9–10

key examples of, 166–168

Surveys of interpersonal relations and racial discrimination, 165–173

design and strengths, 165–166

experiments in, 168

imperfect relationship of attitudes to behaviors, 168–169

key examples of surveys, 166–168

means of improving survey measures, 171–173

survey limitations, 169–171

T

2000 census, 213–216

household data on race and ethnicity in 2000 (C2SS), 215

household data on race and ethnicity in 2000 (C2SS—long form), 214, 215

race and Hispanic origin population in the United States in 2000, 213

Tabulating outcomes

over time, 240–241

Targets

inferential, 109–113

Teacher’s College Record, 19

Terrorism

costs and benefits of profiling, 200–201

developing effective profiles, 197–200

profiling in the context of, 196–202

trade-offs, 201–202

Theories of cumulative disadvantage, 233–238

criminal justice—life-course theory of cumulative disadvantage, 233–234

labor market—feedback models, 237–238

public health—ecosocial theory, 234–236

Theories of discrimination, 55–70

comparison of legal standards with the four types of discrimination, 65–66

domains in which discrimination operates, 66–68

moving from episodic to dynamic definitions of discrimination—role of cumulative disadvantage, 68–69

types of discrimination, 56–65

Time-series data and the reporting on multiple races, 220

Trade-offs in profiling, 201–202

Traffic-violating behaviors assessment, 193–194

Translating experimental effects, 102

Transmission

of cumulative discrimination, 226

Types of discrimination, 56–65

comparison of legal standards with, 65–66

Suggested Citation:"Index." National Research Council. 2004. Measuring Racial Discrimination. Washington, DC: The National Academies Press. doi: 10.17226/10887.
×

U

Unconscious discrimination, 58–61

Uniform Crime Reports, 46n

U.S. census racial categories, 31–33, 209

U.S. Constitution, 27, 40, 206–207

Fifth Amendment, 52

Fourteenth Amendment, 52, 207

U.S. Department of Education, 19, 32, 45, 248

U.S. Department of Housing and Urban Development (HUD), 16, 105–107, 115, 117, 173, 230, 250

U.S. Department of Justice, 106, 173

U.S. Equal Employment Opportunity Commission, 248

U.S. government surveys, race in, 216

U.S. Office of Management and Budget (OMB), 30–32, 36, 206, 208–209, 212, 218–219, 220–221

U.S. Supreme Court, 51, 53, 64, 120

V

Validity issues, 109–114

auditor heterogeneity, 113–114

external, 82

inferential target—estimating an effect of discrimination, 109–113

internal, 82

Variables

moderator, 93

See also Omitted variables bias

Verbal antagonism, 56–57

Voting Rights Act of 1965, 48

W

Washington Post, 182

“Whiteness,” 29, 33n

Whites, “honorary,” 29n

Whites’ perceptions of discrimination, 183

Within-domain and across-domain cumulative effects studies, 251–253

Within-domain cumulative effects studies, 251–25

Workshop on Measuring Racial Disparities, 21

Suggested Citation:"Index." National Research Council. 2004. Measuring Racial Discrimination. Washington, DC: The National Academies Press. doi: 10.17226/10887.
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Suggested Citation:"Index." National Research Council. 2004. Measuring Racial Discrimination. Washington, DC: The National Academies Press. doi: 10.17226/10887.
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Measuring Racial Discrimination Get This Book
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Many racial and ethnic groups in the United States, including blacks, Hispanics, Asians, American Indians, and others, have historically faced severe discrimination—pervasive and open denial of civil, social, political, educational, and economic opportunities. Today, large differences among racial and ethnic groups continue to exist in employment, income and wealth, housing, education, criminal justice, health, and other areas. While many factors may contribute to such differences, their size and extent suggest that various forms of discriminatory treatment persist in U.S. society and serve to undercut the achievement of equal opportunity.

Measuring Racial Discrimination considers the definition of race and racial discrimination, reviews the existing techniques used to measure racial discrimination, and identifies new tools and areas for future research. The book conducts a thorough evaluation of current methodologies for a wide range of circumstances in which racial discrimination may occur, and makes recommendations on how to better assess the presence and effects of discrimination.

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