essay COURSE CITIATIONS ARE ATTACHED
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.
29
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