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Analyzing a claim: racial DISCRIMINATION And inequities

Week 3 (Module 3)

Lecture 3

Prof Rennie Lee

Social Problems SYG 2010

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Analyzing a claim

Claim: “We live in a post-racial society.”

Counterclaim:

1.) Racial discrimination and inequality still plays an important part in an individual’s outcomes

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Hourly wage by race and gender

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Educational Attainment by Race

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High School Dropout Rates by Race

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Percentage 16-24 Year Old High School Drop-outs, NCES 1997

Race, Class, and Education

Correlation between race, class, and education

Minorities tend to be of lower class status and have lower education

Education as mediator for racial inequalities in wages

Educational performance  Educational attainment  Labor market success

Race/ethnicity

Social class

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Earnings by Race and Education

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What accounts for the outcomes among minorities, net of education?

Some mechanisms driving racial/ethnic disparities:

Geography/ residential location

Prejudice and stereotypes

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Residential Segregation in Miami, FL

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Geography: Segregated Schools

Heavily minority schools tend to have fewer resources and be lower SES

Children in schools with large numbers of impoverished children have worse educational outcomes

Lower test scores, fewer students in advanced classes, higher dropout rates

Fewer school resources

Less well-prepared teachers

Low levels of expectation

Little preparation for college

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Networks and Geography

Networks are important aspect for finding a job

But, there are differences in networks by race

Networks also determined by residential location

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Prejudicial attitudes

Discriminatory attitudes by employers

Unclear about exact contribution

Audit studies used to assess this

Public opinion: discrimination is on the decline

Majority of Whites believe that Blacks have same chances of getting a job as Whites

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Abercrombie and Fitch

”All American Look”

Racial discrimination lawsuit

Job positions based on ethnicity

Gonzalez v. Abercrombie and Fitch

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Mail-in Resumes

Betrand and Mullianathan (2004)

Fake resumes with stereotypically white and black names

Emily Walsh and Greg Baker; Lakisha Washington and Jamal Jones

Responded to job ads in newspapers in Chicago and Boston

Similar resumes in labor market experience, skills, etc.

Job applicants with white names needed 10 resumes = 1 callback

Job applicants with black names needed 15 resumes= 1 callback

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Bertrand and Mullainathan (2004) Findings

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Asian Names in North America (US and Canada)

Job applicants in Canada with Asian names (Pakistani, Chinese, or Indian origin) less likely to get called for an interview compared with Anglo names (Banerjee et al. 2017)

Same qualifications

Fictitious resumes

Anglo names and Asian last names still disadvantaged

Asian Candidates in the US more likely to receive callback if whitened their resume

Change names and excluding race-based honors and organizations

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In-person Interviews

Some racial discrimination occurs when employers see job applicants

Send in real people for job interviews

Pairs of individuals that pose as job applicants

Matched on individual characteristics

Whites more likely to receive a callback or job offer compared with blacks even with similar characteristics and qualifications

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Job Discrimination Among Immigrants

Degree devaluation is common among immigrants

Foreign credentials are often not recognized

In Australia and Canada, depends on country where degree was obtained

English-speaking versus non-English-speaking country

English-speaking degree have a higher rates of degrees being recognized

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Discussion

Is race/racial categories an explanatory variable (independent variable) or an outcome to be explained (dependent variable)?

That is, how can race be a cause and outcome of discrimination?

But, how can stereotypes about racial groups shape how others perceive an individual’s race?

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Asian Americans: From Model Minority to Yellow Peril

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Racial identity as a dependent variable

Perception of an individual’s race may be influenced by one’s social characteristics (Penner and Saperstein 2013:336)

Living in an inner city, unemployment, poverty, unmarried parenthood are associated with being a minority

Females receiving welfare support more likely to be perceived to be Black by interviewers

Males who were incarcerated more likely to be perceived to be Black by interviewers

Being married and living in suburban neighborhoods is associated with being white

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Discrimination: Role of Stereotypes

Stereotype Threat

Being at risk of confirming, as self-characteristic, a negative stereotype about one’s group (Steele and Aronson 1995)

African Americans experience psychological response and anxiety

Ex: identifying race before the exam

Stereotype Promise

Asians benefit from positive stereotypes

Positive or Negative, expectations shape behaviors and academic performance

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Sample of death certificate

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Cause of Death and Racial Classification

Cause of death is seemingly ‘race neutral’

Medical examiners and funeral directors use cause of death to classify the race for deceased individuals when race was not known

Native Americans 2.6x more likely to die from chronic liver disease

Blacks were 6.6 more likely to be victims of homicide

Noymer et al. (2011)

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For Thought

How can race can be both an explanatory variable and a dependent variable?

How does this then contribute to our understanding of racial discrimination and racial inequities as a social problem?

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Analyzing a claim

Claim: “We live in a post-racial society”

Counterclaim:

1.) Racial discrimination and inequality still plays an important part in an individual’s outcomes

Racial discrimination occurs in hiring process

Lower returns to education for minorities than Whites

Stereotypes and prejudice around race are still pervasive

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What can be done to address these inequalities?

Anti-discrimination laws

Civil Rights Act of 1964

Title VII

Fair Housing Act

Immigration Reform and Control Act

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Affirmative Action in Higher Education

Affirmative action: broad set of policies to correct systematic racism and discrimination

Government-mandated policies focused on access to education and employment

Special consideration for historically excluded groups like minorities and women

Myths of affirmative action:

Automatic admission

Can be corrected by social class alone

Some still believe that minorities have more advantages in society

Abigail Fisher v. University of Texas

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Changes since protests

Some are more meaningful than others

Companies committing to hiring minority workers or diversity directors or fellows

Companies creating positions to address diversity

Ex: Pull up or Shut up

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Talk to your friends and family

We are all a part of the narrative

Have you had a discussion with your friends and family?

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Vote

As ordinary citizens, one what to engage in the social problems process is to vote

If eligible, are you registered to vote?

https://registertovoteflorida.gov/home

Monday, Oct 5 is the deadline to register to vote in FL

Vote early, mail it in as soon as you can if voting by mail

Do your research on who is running and vote up and down the ballot (presidential election, congressional seats, state seats, local office).

https://ballotpedia.org/Florida_elections,_2020

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Abercrombie and Fitch

• ”All American Look”

• Racial discrimination lawsuit

• Job positions based on ethnicity

• Gonzalez v. Abercrombie and Fitch

12

Abercrombie and Fitch

•”All American Look”

•Racial discrimination lawsuit

•Job positions based on ethnicity

•Gonzalez v. Abercrombie and Fitch

12

employers rarely, if ever, contact applicants via postal mail to set up interviews.

E. Weaknesses of the Experiment

We have already highlighted the strengths of this experiment relative to previous audit stud- ies. We now discuss its weaknesses. First, our outcome measure is crude, even relative to the previous audit studies. Ultimately, one cares about whether an applicant gets the job and about the wage offered conditional on getting the job. Our procedure, however, simply mea- sures callbacks for interviews. To the extent that the search process has even moderate frictions, one would expect that reduced interview rates would translate into reduced job offers. How- ever, we are not able to translate our results into gaps in hiring rates or gaps in earnings. Another weakness is that the resumes do not

directly report race but instead suggest race through personal names. This leads to various sources of concern. First, while the names are chosen to make race salient, some employers may simply not notice the names or not recog- nize their racial content. On a related note, because we are not assigning race but only race-specific names, our results are not repre- sentative of the average African-American (who may not have such a racially distinct

name).28 We return to this issue in Section IV, subsection B. Finally, and this is an issue pervasive in both

our study and the pair-matching audit studies, newspaper ads represent only one channel for job search. As is well known from previous work, social networks are another common means through which people find jobs and one that clearly cannot be studied here. This omis- sion could qualitatively affect our results if African-Americans use social networks more or if employers who rely more on networks differ- entiate less by race.29

III. Results

A. Is There a Racial Gap in Callback?

Table 1 tabulates average callback rates by racial soundingness of names. Included in brackets under each rate is the number of re- sumes sent in that cell. Row 1 presents our results for the full data set. Resumes with White

28 As Appendix Table A1 indicates, the African- American names we use are, however, quite common among African-Americans, making this less of a concern.

29 In fact, there is some evidence that African-Americans may rely less on social networks for their job search (Harry J. Holzer, 1987).

TABLE 1—MEAN CALLBACK RATES BY RACIAL SOUNDINGNESS OF NAMES

Percent callback for White names

Percent callback for African-American names Ratio

Percent difference (p-value)

Sample: All sent resumes 9.65 6.45 1.50 3.20

[2,435] [2,435] (0.0000) Chicago 8.06 5.40 1.49 2.66

[1,352] [1,352] (0.0057) Boston 11.63 7.76 1.50 4.05

[1,083] [1,083] (0.0023) Females 9.89 6.63 1.49 3.26

[1,860] [1,886] (0.0003) Females in administrative jobs 10.46 6.55 1.60 3.91

[1,358] [1,359] (0.0003) Females in sales jobs 8.37 6.83 1.22 1.54

[502] [527] (0.3523) Males 8.87 5.83 1.52 3.04

[575] [549] (0.0513)

Notes: The table reports, for the entire sample and different subsamples of sent resumes, the callback rates for applicants with a White-sounding name (column 1) an an African-American-sounding name (column 2), as well as the ratio (column 3) and difference (column 4) of these callback rates. In brackets in each cell is the number of resumes sent in that cell. Column 4 also reports the p-value for a test of proportion testing the null hypothesis that the callback rates are equal across racial groups.

997VOL. 94 NO. 4 BERTRAND AND MULLAINATHAN: RACE IN THE LABOR MARKET

employersrarely,ifever,contactapplicantsvia

postalmailtosetupinterviews.

E.WeaknessesoftheExperiment

Wehavealreadyhighlightedthestrengthsof

thisexperimentrelativetopreviousauditstud-

ies.Wenowdiscussitsweaknesses.First,our

outcomemeasureiscrude,evenrelativetothe

previousauditstudies.Ultimately,onecares

aboutwhetheranapplicantgetsthejoband

aboutthewageofferedconditionalongetting

thejob.Ourprocedure,however,simplymea-

surescallbacksforinterviews.Totheextentthat

thesearchprocesshasevenmoderatefrictions,

onewouldexpectthatreducedinterviewrates

wouldtranslateintoreducedjoboffers.How-

ever,wearenotabletotranslateourresultsinto

gapsinhiringratesorgapsinearnings.

Anotherweaknessisthattheresumesdonot

directlyreportracebutinsteadsuggestrace

throughpersonalnames.Thisleadstovarious

sourcesofconcern.First,whilethenamesare

chosentomakeracesalient,someemployers

maysimplynotnoticethenamesornotrecog-

nizetheirracialcontent.Onarelatednote,

becausewearenotassigningracebutonly

race-specificnames,ourresultsarenotrepre-

sentativeoftheaverageAfrican-American

(whomaynothavesucharaciallydistinct

name).

28

WereturntothisissueinSectionIV,

subsectionB.

Finally,andthisisanissuepervasiveinboth

ourstudyandthepair-matchingauditstudies,

newspaperadsrepresentonlyonechannelfor

jobsearch.Asiswellknownfromprevious

work,socialnetworksareanothercommon

meansthroughwhichpeoplefindjobsandone

thatclearlycannotbestudiedhere.Thisomis-

sioncouldqualitativelyaffectourresultsif

African-Americans usesocialnetworksmoreor

ifemployerswhorelymoreonnetworksdiffer-

entiatelessbyrace.

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III.Results

A.IsThereaRacialGapinCallback?

Table1tabulatesaveragecallbackratesby

racialsoundingnessofnames.Includedin

bracketsundereachrateisthenumberofre-

sumessentinthatcell.Row1presentsour

resultsforthefulldataset.ResumeswithWhite

28

AsAppendixTableA1indicates,theAfrican-

Americannamesweuseare,however,quitecommon

amongAfrican-Americans,makingthislessofaconcern.

29

Infact,thereissomeevidencethatAfrican-Americans

mayrelylessonsocialnetworksfortheirjobsearch(Harry

J.Holzer,1987).

TABLE1—MEANCALLBACKRATESBYRACIALSOUNDINGNESSOFNAMES

Percentcallback

forWhitenames

Percentcallbackfor

African-AmericannamesRatio

Percentdifference

(p-value)

Sample:

Allsentresumes 9.65 6.451.503.20

[2,435] [2,435] (0.0000)

Chicago 8.06 5.401.492.66

[1,352] [1,352] (0.0057)

Boston 11.63 7.761.504.05

[1,083] [1,083] (0.0023)

Females 9.89 6.631.493.26

[1,860] [1,886] (0.0003)

Femalesinadministrativejobs10.46 6.551.603.91

[1,358] [1,359] (0.0003)

Femalesinsalesjobs 8.37 6.831.221.54

[502] [527] (0.3523)

Males 8.87 5.831.523.04

[575] [549] (0.0513)

Notes:Thetablereports,fortheentiresampleanddifferentsubsamplesofsentresumes,thecallbackratesforapplicantswith

aWhite-soundingname(column1)ananAfrican-American-sounding name(column2),aswellastheratio(column3)and

difference(column4)ofthesecallbackrates.Inbracketsineachcellisthenumberofresumessentinthatcell.Column4

alsoreportsthep-valueforatestofproportiontestingthenullhypothesisthatthecallbackratesareequalacrossracialgroups.

997VOL.94NO.4BERTRANDANDMULLAINATHAN:RACEINTHELABORMARKET