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



The National Academies | 500 Fifth St. N.W. | Washington, D.C. 20001
Copyright © National Academy of Sciences. All rights reserved.
Terms of Use and Privacy Statement



Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.

OCR for page 307
Measuring Racial Discrimination 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

OCR for page 307
Measuring Racial Discrimination 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

OCR for page 307
Measuring Racial Discrimination 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

OCR for page 307
Measuring Racial Discrimination 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

OCR for page 307
Measuring Racial Discrimination 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

OCR for page 307
Measuring Racial Discrimination 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

OCR for page 307
Measuring Racial Discrimination 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

OCR for page 307
Measuring Racial Discrimination 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

OCR for page 307
Measuring Racial Discrimination 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

OCR for page 307
Measuring Racial Discrimination 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

OCR for page 307
Measuring Racial Discrimination 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

OCR for page 307
Measuring Racial Discrimination This page intentionally left blank.