The DOI matches its Crossref record; 43 of the 43 references it cites were found in a registry or an index; none of the 6 sources its claims cite is checked for support yet.
Meta-analysis of field experiments shows no change in racial discrimination in hiring over time
Open accessAbstract
Significance: Many scholars have argued that discrimination in American society has decreased over time, while others point to persisting race and ethnic gaps and subtle forms of prejudice. The question has remained unsettled due to the indirect methods often used to assess levels of discrimination. We assess trends in hiring discrimination against African Americans and Latinos over time by analyzing callback rates from all available field experiments of hiring, capitalizing on the direct measure of discrimination and strong causal validity of these studies. We find no change in the levels of discrimination against African Americans since 1989, although we do find some indication of declining discrimination against Latinos. The results document a striking persistence of racial discrimination in US labor markets.
Overview
AI snapshot
Written from the paper’s full text.
TL;DR
A meta-analysis of all available US field experiments of hiring discrimination found no change over time in discrimination against African Americans since 1989, though there was modest evidence of declining discrimination against Latinos. Whites received substantially more callbacks than equally qualified African American and Latino applicants.
Key findings
- Across studies since 1989, white applicants received on average 36% more callbacks than equally qualified African Americans (95% CI: 25–47% more) and 24% more callbacks than Latinos (95% CI: 15–33% more).
- For African Americans, the paper found no change in hiring discrimination over the past 25 years; the 95% CI of the annual slope from 1989–2015 was −0.007 to 0.015, ruling out all but a slow decline, with the point estimate indicating no decline.
- For Latinos, the trend suggested a possible decline, from whites receiving 30% more callbacks than Latinos in 1990 to 15% more in 2010, but this was only marginally significant (P = 0.099) and based on only 9 Latino field experiments.
- Accounting for applicant education, gender, study method, occupational groups, local labor market conditions, and other controls did little to alter the African American result; including unpublished studies also did little to affect estimates.
Methods
- The authors conducted a meta-analysis of every available US field experiment of hiring discrimination, including resume audits and in-person audits, with fieldwork through December 2015.
- The full search located 28 studies representing 55,842 applications for 26,326 positions; the core analysis since 1989 used 24 studies with 30 estimates, representing 54,318 applications for 25,517 positions.
- They used random-effects meta-regression, regressing the log discrimination ratio—the ratio of white callback rates to African American or Latino callback rates—on year of fieldwork, with controls for study and applicant characteristics.
Limitations
- The paper states that results pertain only to discrimination at the point of hire, not later employment outcomes such as wage setting or termination, and do not address possible declines during the 1960s or early 1970s.
- The paper states that the small number of Latino field experiments (n = 9) limits controls and precision, and that the overall sample of African American studies since 1990 (n = 21) limits the ability to detect statistical significance for covariates.
- The paper notes publication bias as a potential concern but reports that including 11 unpublished field experiments did little to affect estimates; it also states that studies focused on racial discrimination showed no more discrimination than studies where race was secondary.
Model-written summary. Check it against the paper before relying on it.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
33 Own result · 9 Own method · 6 Sources not found · 4 Own interpretation · 3 No basis given
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The 95% confidence interval of the slope 1989-2015 is -0.007 to 0.015.”
§ Meta-analysis of field experiments shows no change in racial discrimination in hiring over time > Results
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The point estimate suggests a decline from whites receiving 30% more callbacks than Latinos in 1990 to 15% more callbacks in 2010 (1.30 vs. 1.15).”
§ Meta-analysis of field experiments shows no change in racial discrimination in hiring over time > Results
hedgedcorrelationaln = 9- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Rests on an assumption: The racial identifiers used in the original field experiments (e.g., racially identifiable names or tester race) validly signal race to employers and do not differ systematically on other employment-relevant characteristics.
- Rests on an assumption: The year in which data were gathered is a valid and comparable indicator of the time trend in hiring discrimination.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Our basic result-no decline in discrimination against African Americans over time-holds using both of the alternative measures, whereas evidence of a decline in discrimination for Latinos appears somewhat stronger with the difference in proportions or the odds ratio.”
§ Meta-analysis of field experiments shows no change in racial discrimination in hiring over time > The Meta-Analysis Model.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- The authors state this as an assumption: The true effect of race on callback rates varies across studies and situations, such as by year, occupation, and applicant skill level.
- The authors state this as an assumption: The true effects of race on callback rate in each situation estimated by each study vary between studies with a normal distribution around a mean effect.
- The authors state this as an assumption: Study-level heterogeneity follows a normal distribution around the linear predictor.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We observe no change in the level of hiring discrimination against African Americans over the past 25 years, although we find modest evidence of a decline in discrimination against Latinos.”
- Also stated in: § Results · hedged
“Here, we see the line slopes downward, indicating a possible decline in discrimination, although this trend is outside of conventional levels of significance (P = 0.099).”
§ Meta-analysis of field experiments shows no change in racial discrimination in hiring over time > Abstract
hedgedcorrelationaln = 9- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Rests on an assumption: The racial identifiers used in the original field experiments (e.g., racially identifiable names or tester race) validly signal race to employers and do not differ systematically on other employment-relevant characteristics.
- Rests on an assumption: The year in which data were gathered is a valid and comparable indicator of the time trend in hiring discrimination.
- Also stated in: § Results · hedged
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We focus on this period because the data are sparse before this period (only four studies before 1989) and because our reading of the early studies indicates key methodological differences among these early studies that may affect their results.”
§ Meta-analysis of field experiments shows no change in racial discrimination in hiring over time > Coding and Selection of Analysis
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Since 1989, whites receive on average 36% more callbacks than African Americans, and 24% more callbacks than Latinos.”
- Also stated in: § Results · plain
“White applicants receive on average 24% more callbacks than Latinos (95% confidence interval of 15-33% more).”
§ Meta-analysis of field experiments shows no change in racial discrimination in hiring over time > Abstract
plaincorrelationaln = 24- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Rests on an assumption: The racial identifiers used in the original field experiments (e.g., racially identifiable names or tester race) validly signal race to employers and do not differ systematically on other employment-relevant characteristics.
- Also stated in: § Results · plain
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Excluding the early studies leaves us with 21 estimates of discrimination against African Americans and nine against Latinos from 24 studies (six studies include estimates of discrimination against both African Americans and Latinos).”
§ Meta-analysis of field experiments shows no change in racial discrimination in hiring over time > Coding and Selection of Analysis
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“As a final check on the influence of covariates, we tested for time trends among our study-level and individual-level characteristics, finding no evidence of systematic change (SI Appendix, section 9 and Table S10).”
§ Meta-analysis of field experiments shows no change in racial discrimination in hiring over time > Results
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Rests on an assumption: The racial identifiers used in the original field experiments (e.g., racially identifiable names or tester race) validly signal race to employers and do not differ systematically on other employment-relevant characteristics.
- Rests on an assumption: The year in which data were gathered is a valid and comparable indicator of the time trend in hiring discrimination.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This produced 24 studies containing 30 estimates of discrimination against African Americans and Latinos since 1989, together representing 54,318 applications submitted for 25,517 positions.”
§ Meta-analysis of field experiments shows no change in racial discrimination in hiring over time > Abstract
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In all models, we see little evidence of a reduction in hiring discrimination against African Americans over time.”
§ Meta-analysis of field experiments shows no change in racial discrimination in hiring over time > Results
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Rests on an assumption: The racial identifiers used in the original field experiments (e.g., racially identifiable names or tester race) validly signal race to employers and do not differ systematically on other employment-relevant characteristics.
- Rests on an assumption: The year in which data were gathered is a valid and comparable indicator of the time trend in hiring discrimination.
- It may state two separate claims as one. 13
- Probably not a substantial claim. 12
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Overall, our search located 34 studies that were US-based field experiments of hiring, included contrasts between white and nonwhite applicant profiles that were on-average equivalent in their labor-market relevant characteristics (e.g., education, experience level in the labor market).”
§ Meta-analysis of field experiments shows no change in racial discrimination in hiring over time > Acknowledgements
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In each case, we see coefficients for the time trend that are close to zero-ranging from an estimated increase of 0.1% per year (0.001) to an increase of 1.3% per year (0.013) -suggesting little change in the level of discrimination facing African Americans over time.”
§ Meta-analysis of field experiments shows no change in racial discrimination in hiring over time > Results
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Rests on an assumption: The racial identifiers used in the original field experiments (e.g., racially identifiable names or tester race) validly signal race to employers and do not differ systematically on other employment-relevant characteristics.
- Rests on an assumption: The year in which data were gathered is a valid and comparable indicator of the time trend in hiring discrimination.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Studies have fieldwork periods range from 1972 to 2015 for African Americans and 1989 to 2015 for Latinos.”
§ Meta-analysis of field experiments shows no change in racial discrimination in hiring over time > Coding and Selection of Analysis
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Our remaining 28 studies yielded 24 estimates of discrimination against African Americans and 9 against Latinos relative to whites.”
§ Meta-analysis of field experiments shows no change in racial discrimination in hiring over time > Acknowledgements
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“With this modification, the trend line for African Americans slants more downward, but is still close to zero (-0.008) and statistically nonsignificant.”
§ Meta-analysis of field experiments shows no change in racial discrimination in hiring over time > Results
plainn = 3- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Rests on an assumption: The racial identifiers used in the original field experiments (e.g., racially identifiable names or tester race) validly signal race to employers and do not differ systematically on other employment-relevant characteristics.
- Rests on an assumption: The year in which data were gathered is a valid and comparable indicator of the time trend in hiring discrimination.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The modified results show the trend line slanting slightly more upward, providing less evidence to support a downward trend than the results including a more heterogeneous set of applicant characteristics.”
§ Meta-analysis of field experiments shows no change in racial discrimination in hiring over time > Results
plaindirectn = 7- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Rests on an assumption: The racial identifiers used in the original field experiments (e.g., racially identifiable names or tester race) validly signal race to employers and do not differ systematically on other employment-relevant characteristics.
- Rests on an assumption: The year in which data were gathered is a valid and comparable indicator of the time trend in hiring discrimination.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“studies in which racial discrimination was the focus of the analysis (and for which there may be more pressure to demonstrate a positive effect) show no more discrimination than studies in which other characteristics were the main focus”
§ Meta-analysis of field experiments shows no change in racial discrimination in hiring over time > Results
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Rests on an assumption: The racial identifiers used in the original field experiments (e.g., racially identifiable names or tester race) validly signal race to employers and do not differ systematically on other employment-relevant characteristics.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“In later models, we include a more extensive set of predictors to control for other factors that might confound the time trend.”
§ Meta-analysis of field experiments shows no change in racial discrimination in hiring over time > The Meta-Analysis Model.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“This formula will slightly overestimate the SE of the effect for studies that are paired but we treat as unpaired due to lack of information about the outcomes at the pair level, underweighting these studies a bit in computing the overall effect, and slightly inflating the overall cross-study SE.”
§ Meta-analysis of field experiments shows no change in racial discrimination in hiring over time > The Meta-Analysis Model.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“Likewise, from an accountability standpoint, discrimination is less easily detected, and therefore less costly to employers, at the point of hire (26).”
§ Meta-analysis of field experiments shows no change in racial discrimination in hiring over time > Discussion
What the sources say
- Not matchedcites [26]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Not matched
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“The field experimental method is a design with high causal (internal) validity because it benefits from aspects of experimental design.”
§ Meta-analysis of field experiments shows no change in racial discrimination in hiring over time > Abstract
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We conclude that this evidence rules out all but a slow decline in discriminationwith the most likely estimate being the point estimate, which indicates no decline in discrimination at all.”
§ Meta-analysis of field experiments shows no change in racial discrimination in hiring over time > Results
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Each study was coded independently by two raters, with disagreement resolved by the first author.”
§ Meta-analysis of field experiments shows no change in racial discrimination in hiring over time > Identifying Relevant Studies.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Social psychological theories would predict hiring to be most vulnerable to the influence of racial bias, given that objective information is limited or unreliable (23)(24)(25).”
§ Meta-analysis of field experiments shows no change in racial discrimination in hiring over time > Discussion
What the sources say
- Not matchedcites (23)(24)(25)
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
In the paper
“Random effects are recommended whenever there is reason to believe that the effect in question is likely to vary as a function of design features of the study, rather than representing a single underlying effect that is constant over the whole population.”
§ Meta-analysis of field experiments shows no change in racial discrimination in hiring over time > The Meta-Analysis Model.
What the sources say
- Not matchedcites [22]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence.
- Not matched
In the paper
“We note that our results do not address the possibility that hiring discrimination may have substantially dropped in the 1960s or early 1970s, during the civil rights era when many forms of direct discrimination were outlawed, as some evidence suggests (1).”
§ Meta-analysis of field experiments shows no change in racial discrimination in hiring over time > Discussion
What the sources say
- Not matchedcites [1]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Contrary to claims of declining discrimination in American society, our estimates suggest that levels of discrimination remain largely unchanged, at least at the point of hire.”
§ Meta-analysis of field experiments shows no change in racial discrimination in hiring over time > Abstract
hedgedn = 28- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Rests on an assumption: The racial identifiers used in the original field experiments (e.g., racially identifiable names or tester race) validly signal race to employers and do not differ systematically on other employment-relevant characteristics.
- Rests on an assumption: The year in which data were gathered is a valid and comparable indicator of the time trend in hiring discrimination.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“We perform a meta-analysis of every available field experiment of hiring discrimination against African Americans or Latinos (n = 28).”
- Also stated in: § Abstract · plain
“Together, these studies represent 55,842 applications submitted for 26,326 positions.”
§ Meta-analysis of field experiments shows no change in racial discrimination in hiring over time > Abstract
plainn = 28- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Also stated in: § Abstract · plain
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“We also required that contrasts of hiring outcomes between race or ethnic groups were made for groups that were on average equivalent in their labor market relevant characteristics, since otherwise discrimination estimates are confounded with the difference in nonracial characteristics.”
§ Meta-analysis of field experiments shows no change in racial discrimination in hiring over time > Identifying Relevant Studies.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“We also required that contrasts of hiring outcomes between race or ethnic groups were made for groups that were on average equivalent in their labor market relevant characteristics, since otherwise discrimination estimates are confounded with the difference in nonracial characteristics.”
§ Meta-analysis of field experiments shows no change in racial discrimination in hiring over time > Identifying Relevant Studies.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“The initial rubric was reviewed and updated by all authors of this study for completeness.It was subsequently refined as coding progressed.”
§ Meta-analysis of field experiments shows no change in racial discrimination in hiring over time > Identifying Relevant Studies.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
The paper relies on this without support.
The racial identifiers used in the original field experiments (e.g., racially identifiable names or tester race) validly signal race to employers and do not differ systematically on other employment-relevant characteristics.
“In the typical resume audit, clues indicating race (such as a racially identifiable name) are randomly assigned to otherwise similar resumes, allowing for treatment and control groups to be equated through randomization.”
The paper relies on this without support.
The year in which data were gathered is a valid and comparable indicator of the time trend in hiring discrimination.
“We analyze the relationship of discrimination ratios to years in which the data were gathered to provide an estimate of the trend in discrimination.”
The authors state this as an assumption.
The true effect of race on callback rates varies across studies and situations, such as by year, occupation, and applicant skill level.
“This is surely the case in our analysis, as we expect that the level of racial discrimination may depend on the year of the study, the situation the study considers (e.g., the occupational categories), the skill level of the applicants, and so on.”
The authors state this as an assumption.
The true effects of race on callback rate in each situation estimated by each study vary between studies with a normal distribution around a mean effect.
“More formally, random-effects meta-analysis allows the true effects of race on the callback rate in each situation estimated by each study, θ i , to vary between studies by assuming that they have a normal distribution around a mean effect, θ.”
The authors state this as an assumption.
Study-level heterogeneity follows a normal distribution around the linear predictor.
“The model assumes the study-level heterogeneity follows a normal distribution around the linear predictor:”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“In Quillian et al. [74]'s résumé audit studies, race-associated names produce callback differentials equivalent to approximately d = 0 . 10˘0 . 30”
From All Public Voices Are Equal, But Are Some More Equal Than Others to LLMs? (2026) · cites this paper as [74]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Quillian et al. (2017) find that there has been no change over the past 25 years in discrimination against African Americans in the United States.”
From Comparative Perspectives on Racial Discrimination in Hiring: The Rise of Field Experiments (2021) · cites this paper as Quillian et al. (2017)
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“Both of these findings align with existing work on the persistence of gender segregation (Zhu and Grusky 2022) and racial inequality (Quillian et al. 2017) in the U.S. labor market.”
From Getting a Foot in the Door: A Meta-Analysis of U.S. Audit Studies of Gender Bias in Hiring (2025) · cites this paper as Quillian et al. 2017
The cited source says what the claim attributes to it.
In the citing paper
“First of all, our research is based on a synthesis of only correspondence experiments, whereas some earlier meta-studies that focused on specific discrimination grounds have also included in-person audits to paint a broader picture of hiring discrimination (e.g.Quillian et al., 2017).”
From The state of hiring discrimination: A meta-analysis of (almost) all recent correspondence experiments (2023) · cites this paper as Quillian et al., 2017
The cited source says what the claim attributes to it.
In the citing paper
“Tests for publication bias discussed in the supplemental material ofQuillian et al. (2017Quillian et al. ( , 2019)), however, find either no evidence of publication bias or that its effects on estimates is small.”
From Comparative Perspectives on Racial Discrimination in Hiring: The Rise of Field Experiments (2021) · cites this paper as Quillian et al. (2017
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ Meta-analysis of field experiments shows no change in racial discrimination in hiring over time > Acknowledgements
“Our remaining 28 studies yielded 24 estimates of discrimination against African Americans and 9 against Latinos relative to whites.”
§ Meta-analysis of field experiments shows no change in racial discrimination in hiring over time > Coding and Selection of Analysis
“Excluding the early studies leaves us with 21 estimates of discrimination against African Americans and nine against Latinos from 24 studies (six studies include estimates of discrimination against both African Americans and Latinos).”
Citations
Cites
Borenstein, M., Hedges, L. V., Higgins, J. P. T., & Rothstein, H. R. (2009) · doi:10.1002/9780470743386 · Cited by 14,225
Borenstein, M., Hedges, L. V., Higgins, J. P. T., & Rothstein, H. R. (2021) · doi:10.1002/9781119558378 · Cited by 9,799
(2004) · Choice Reviews Online · doi:10.5860/choice.41-3182 · Cited by 4,740
The Handbook of Research Synthesis and Meta-Analysis
(2019) · doi:10.7758/9781610448864 · Cited by 4,553
Bertrand, M., & Mullainathan, S. (2004) · American Economic Review · doi:10.1257/0002828042002561 · Cited by 4,504
Racism without racists: color-blind racism and the persistence of racial inequality in America
(2013) · Choice Reviews Online · doi:10.5860/choice.51-2956 · Cited by 2,685
(2010) · Choice Reviews Online · doi:10.5860/choice.47-6626 · Cited by 2,234
Prejudice and politics: Symbolic racism versus racial threats to the good life.
Kinder, D. R., & Sears, D. O. (1981) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.40.3.414 · Cited by 1,965
Racial Attitudes in America: Trends and Interpretations
Bruce, S. E., Schuman, H., Steeh, C., & Bobo, L. D. (1987) · British Journal of Sociology · doi:10.2307/590918 · Cited by 1,919
(1998) · Medical Entomology and Zoology · Cited by 1,773
Research works printed but not linked: 1
- D Wessel Fear of bias suits may be affecting hiring decisions. Wall Street Journal section A p 2. (September 11 2003).
Cited by
Sorted by citations
A Theory of Racialized Organizations
Ray, V. E. (2019) · American Sociological Review · doi:10.1177/0003122418822335 · Cited by 2,182
Mitigating bias in algorithmic hiring: evaluating claims and practices
Raghavan, M., Barocas, S., Kleinberg, J., & Levy, K. (2020) · Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency · doi:10.1145/3351095.3372828 · Cited by 845
The Organizational Reproduction of Inequality
Amis, J., Mair, J., & Munir, K. A. (2019) · Academy of Management Annals · doi:10.5465/annals.2017.0033 · Cited by 548
Experimental research on labor market discrimination
Neumark, D. (2018) · Journal of Economic Literature · doi:10.1257/jel.20161309 · Cited by 529
Krieger, N. (2020) · Annual Review of Public Health · doi:10.1146/annurev-publhealth-040119-094017 · Cited by 411
Inherent Tradeoffs in the Fair Determination of Risk Scores
Raghavan, M. (2023) · ACM eBooks · doi:10.1145/3603195.3603197 · Cited by 350
On the prevalence of racial discrimination in the United States
Lee, R. T., Perez, A. D., Boykin, C. M., & Mendoza-Denton, R. (2019) · PLOS ONE · doi:10.1371/journal.pone.0210698 · Cited by 318
Yearby, R. (2018) · American Journal of Economics and Sociology · doi:10.1111/ajes.12230 · Cited by 336
Principles for the Validation and Use of Personnel Selection Procedures
Anonymous (2018) · Industrial and Organizational Psychology · doi:10.1017/iop.2018.195 · Cited by 316
Mixed Signals: The Unintended Effects of Diversity Initiatives
Dover, T. L., Kaiser, C. R., & Major, B. (2019) · Social Issues and Policy Review · doi:10.1111/sipr.12059 · Cited by 349
Diversity at a Critical Juncture: New Theories for a Complex Phenomenon
Nkomo, S. M., Bell, M. P., Roberts, L. M., Joshi, A., & Thatcher, S. M. B. (2019) · Academy of Management Review · doi:10.5465/amr.2019.0103 · Cited by 281
Quillian, L., Heath, A., Pager, D., Midtbøen, A., Fleischmann, F., & Hexel, O. (2019) · Sociological Science · doi:10.15195/v6.a18 · Cited by 283
Self-citationSystemic Discrimination Among Large U.S. Employers
Kline, P., Rose, E. K., & Walters, C. (2022) · The Quarterly Journal of Economics · doi:10.1093/qje/qjac024 · Cited by 240
Comparative Perspectives on Racial Discrimination in Hiring: The Rise of Field Experiments
Quillian, L., & Midtbøen, A. H. (2021) · Annual Review of Sociology · doi:10.1146/annurev-soc-090420-035144 · Cited by 180
Self-citationQuillian, L., Lee, J. J., & Honoré, B. (2020) · Race and Social Problems · doi:10.1007/s12552-019-09276-x · Cited by 166
Self-citationDavis, J. L., Williams, A. A., & Yang, M. W. (2021) · Big Data & Society · doi:10.1177/20539517211044808 · Cited by 179
Jilke, S., Dooren, W. V., & Rys, S. (2018) · Journal of Public Administration Research and Theory · doi:10.1093/jopart/muy009 · Cited by 168
Poverty in America: New Directions and Debates
Desmond, M., & Western, B. (2018) · Annual Review of Sociology · doi:10.1146/annurev-soc-060116-053411 · Cited by 158
An Introduction to Audit Studies in the Social Sciences
Gaddis, S. M. (2018) · Audit Studies: Behind the Scenes with Theory, Method, and Nuance · doi:10.1007/978-3-319-71153-9_1 · Cited by 157
Job Seeking: The Process and Experience of Looking for a Job
Wanberg, C. R., Ali, A. A., & Csillag, B. (2019) · Annual Review of Organizational Psychology and Organizational Behavior · doi:10.1146/annurev-orgpsych-012119-044939 · Cited by 187
Relative Education and the Advantage of a College Degree
Horowitz, J. T. (2018) · American Sociological Review · doi:10.1177/0003122418785371 · Cited by 154
The American racial divide in fear of the police
Pickett, J. T., Graham, A., & Cullen, F. T. (2022) · Criminology · doi:10.1111/1745-9125.12298 · Cited by 152
Heath, A. F., & Di Stasio, V. (2019) · The British Journal of Sociology · doi:10.1111/1468-4446.12676 · Cited by 167
Building and Auditing Fair Algorithms: A Case Study in Candidate Screening
Wilson, C., Ghosh, A., Jiang, S., Mislove, A., Baker, L., Szary, J., Trindel, K., & Polli, F. (2021) · Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency · doi:10.1145/3442188.3445928 · Cited by 133
Inequities in Employment by Race, Ethnicity, and Sector During COVID-19
Gemelas, J. C., Davison, J. M., Keltner, C. H., & Ing, S. (2021) · Journal of Racial and Ethnic Health Disparities · doi:10.1007/s40615-021-00963-3 · Cited by 128
Statistical Discrimination and the Rationalization of Stereotypes
Tilcsik, A. (2020) · American Sociological Review · doi:10.1177/0003122420969399 · Cited by 139
Algorithmic equity in the hiring of underrepresented IT job candidates
Yarger, L., Cobb Payton, F., & Neupane, B. (2019) · Online Information Review · doi:10.1108/oir-10-2018-0334 · Cited by 122
Fairness and Bias in Algorithmic Hiring: A Multidisciplinary Survey
Fabris, A., Baranowska, N., Dennis, M. J., Graus, D., Hacker, P., Saldivar, J., Zuiderveen Borgesius, F., & Biega, A. J. (2025) · ACM Transactions on Intelligent Systems and Technology · doi:10.1145/3696457 · Cited by 117
Ochmann, J., Michels, L., Tiefenbeck, V., Maier, C., & Laumer, S. (2024) · Information Systems Journal · doi:10.1111/isj.12482 · Cited by 132
Liu, W. M., Liu, R. Z., Garrison, Y. L., Kim, J. Y. C., Chan, L., Ho, Y. C. S., & Yeung, C. W. (2019) · American Psychologist · doi:10.1037/amp0000368 · Cited by 137
Reconsidering the Utility of Race-Specific Lung Function Prediction Equations
Baugh, A. D., Shiboski, S. C., Hansel, N. N., Ortega, V. E., Barjaktarević, I., Barr, R. G., Bowler, R. P., Comellas, A. P., Cooper, C. B., Couper, D. J., et al. (2021) · American Journal of Respiratory and Critical Care Medicine · doi:10.1164/rccm.202105-1246oc · Cited by 114
Prosocial motives underlie scientific censorship by scientists: A perspective and research agenda
Clark, C. J., Jussim, L. J., Frey, K., Stevens, S. T., al‐Gharbi, M., Aquino, K. F., Bailey, J. M., Barbaro, N., Baumeister, R. F., Bleske-Rechek, A. L., et al. (2023) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2301642120 · Cited by 118
Disrupting White Supremacy and Anti-Black Racism in Educational Organizations
Diamond, J. B., & Gomez, L. M. (2023) · Educational Researcher · doi:10.3102/0013189x231161054 · Cited by 129
Koopmans, R., Veit, S., & Yemane, R. (2019) · Ethnic and Racial Studies · doi:10.1080/01419870.2019.1654114 · Cited by 110
Hofeditz, L., Clausen, S., Rieß, A., Mirbabaie, M., & Stieglitz, S. (2022) · Electronic Markets · doi:10.1007/s12525-022-00600-9 · Cited by 124
Racial/Ethnic Perceptions from Hispanic Names: Selecting Names to Test for Discrimination
Gaddis, S. M. (2017) · Socius Sociological Research for a Dynamic World · doi:10.1177/2378023117737193 · Cited by 106
Beliefs about Racial Discrimination and Support for Pro-Black Policies
Haaland, I., & Roth, C. (2021) · The Review of Economics and Statistics · doi:10.1162/rest_a_01036 · Cited by 105
The cost of anti-Asian racism during the COVID-19 pandemic
Huang, J. T., Krupenkin, M., Rothschild, D. M., & Lee, J. (2023) · Nature Human Behaviour · doi:10.1038/s41562-022-01493-6 · Cited by 103
Systemic Discrimination Among Large U.S. Employers
Kline, P., Rose, E. K., & Walters, C. (2021) · National Bureau of Economic Research · doi:10.3386/w29053 · Cited by 107
Lancee, B. (2019) · Journal of Ethnic and Migration Studies · doi:10.1080/1369183x.2019.1622744 · Cited by 115
What Explains Racial/Ethnic Inequality in Job Quality in the Service Sector?
Storer, A., Schneider, D., & Harknett, K. (2020) · American Sociological Review · doi:10.1177/0003122420930018 · Cited by 103
Diversity of artists in major U.S. museums
Topaz, C. M., Klingenberg, B., Turek, D., Heggeseth, B., Harris, P. E., Blackwood, J. C., Chavoya, C. O., Nelson, S., & Murphy, K. (2019) · PLoS ONE · doi:10.1371/journal.pone.0212852 · Cited by 99
Öztürk, M. B., & Berber, A. (2020) · Human Relations · doi:10.1177/0018726720957727 · Cited by 105
Avoiding Post-Treatment Bias in Audit Experiments
Coppock, A. (2018) · Journal of Experimental Political Science · doi:10.1017/xps.2018.9 · Cited by 92
Batruch, A., Autin, F., Bataillard, F., & Butera, F. (2018) · Personality and Social Psychology Bulletin · doi:10.1177/0146167218791804 · Cited by 101
Rynes, S. L., Colbert, A. E., & O’Boyle, E. H. (2018) · Journal of Management · doi:10.1177/0149206318796934 · Cited by 99
Machine learning and genomics: precision medicine versus patient privacy
Azencott, C.-A. (2018) · Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences · doi:10.1098/rsta.2017.0350 · Cited by 89
Toward an economic sociology of race
Hirschman, D., & Garbes, L. (2019) · Socio-Economic Review · doi:10.1093/ser/mwz054 · Cited by 90
Trends in racial and ethnic discrimination in hiring in six Western countries
Quillian, L., & Lee, J. J. (2023) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2212875120 · Cited by 88
Self-citationOpportunity Hoarding and the Maintenance of “White” Educational Space
Diamond, J. B., & Lewis, A. E. (2022) · American Behavioral Scientist · doi:10.1177/00027642211066048 · Cited by 95
Schaerer, M., du Plessis, C., Nguyen, M. H. B., van Aert, R. C. M., Tiokhin, L., Lakens, D., Giulia Clemente, E., Pfeiffer, T., Dreber, A., Johannesson, M., et al. (2023) · Organizational Behavior and Human Decision Processes · doi:10.1016/j.obhdp.2023.104280 · Cited by 87
There is no liberal media bias in which news stories political journalists choose to cover
Hassell, H. J. G., Holbein, J. B., & Miles, M. R. (2020) · Science Advances · doi:10.1126/sciadv.aay9344 · Cited by 94
New Directions in Critical Race Theory and Sociology: Racism, White Supremacy, and Resistance
Christian, M. M., Seamster, L., & Ray, V. E. (2019) · American Behavioral Scientist · doi:10.1177/0002764219842623 · Cited by 102
What is culture? Systems of people, places, and practices
Causadías, J. M. (2020) · Applied Developmental Science · doi:10.1080/10888691.2020.1789360 · Cited by 115
Bias, Fairness, and Validity in Graduate-School Admissions: A Psychometric Perspective
Woo, S. E., LeBreton, J. M., Keith, M. G., & Tay, L. (2022) · Perspectives on Psychological Science · doi:10.1177/17456916211055374 · Cited by 94
Quillian, L., Lee, J. J., & Oliver, M. (2020) · Social Forces · doi:10.1093/sf/soaa026 · Cited by 105
Self-citationBridging Machine Learning and Mechanism Design towards Algorithmic Fairness
Finocchiaro, J., Maio, R., Monachou, F., Patro, G. K., Raghavan, M., Stoica, A.-A., & Tsirtsis, S. (2021) · ACM Conference on Fairness, Accountability, and Transparency (FAccT) · doi:10.1145/3442188.3445912 · Cited by 89
Zwysen, W., Stasio, V. D., & Heath, A. (2020) · Sociology · doi:10.1177/0038038520966947 · Cited by 99
The Civil Rights Revolution at Work: What Went Wrong
Dobbin, F. R., & Kalev, A. (2021) · Annual Review of Sociology · doi:10.1146/annurev-soc-090820-023615 · Cited by 80
Thijssen, L., van Tubergen, F., Coenders, M., Hellpap, R. L., & Jak, S. (2021) · International Migration Review · doi:10.1177/01979183211045044 · Cited by 90
Status Characteristics, Implicit Bias, and the Production of Racial Inequality
Melamed, D., Munn, C. W., Barry, L., Montgomery, B., & Okuwobi, O. F. (2019) · American Sociological Review · doi:10.1177/0003122419879101 · Cited by 80
Bias in Automatic Speech Recognition: The Case of African American Language
Martin, J., & Wright, K. E. (2022) · Applied Linguistics · doi:10.1093/applin/amac066 · Cited by 71
Employment and poverty: Why work matters in understanding poverty.
Thompson, M. N., & Dahling, J. J. (2019) · American Psychologist · doi:10.1037/amp0000468 · Cited by 70
Perry, S. L., Cobb, R. J., Whitehead, A. L., & Grubbs, J. B. (2021) · Social Forces · doi:10.1093/sf/soab134 · Cited by 70
Re-thinking Soft Skills and Student Employability: A New Paradigm for Undergraduate Education
Hora, M. T., Benbow, R. J., & Smolarek, B. B. (2018) · Change The Magazine of Higher Learning · doi:10.1080/00091383.2018.1540819 · Cited by 69
Adamovic, M., & Leibbrandt, A. (2022) · The Leadership Quarterly · doi:10.1016/j.leaqua.2022.101655 · Cited by 76
Microaggressions and Discrimination Relate to Barriers to Care Among Black Women Living with HIV
Dale, S. K., Dean, T., Sharma, R., Reid, R., Saunders, S., & Safren, S. A. (2019) · AIDS Patient Care and STDs · doi:10.1089/apc.2018.0258 · Cited by 67
Mitigating Bias in Algorithmic Hiring: Evaluating Claims and Practices
Raghavan, M. (2023) · ACM eBooks · doi:10.1145/3603195.3603203 · Cited by 67
Bias in Context: Small Biases in Hiring Evaluations Have Big Consequences
Hardy, J. H., Tey, K. S., Cyrus-Lai, W., Martell, R. F., Olstad, A., & Uhlmann, E. L. (2021) · Journal of Management · doi:10.1177/0149206320982654 · Cited by 81
An intersectional analysis of the feminization of homelessness and mothers’ housing precarity
Bullock, H. E., Reppond, H. A., Truong, S. V., & Singh, M. R. (2020) · Journal of Social Issues · doi:10.1111/josi.12406 · Cited by 66
MacInnis, C. C., & Hodson, G. (2018) · Journal of Theoretical Social Psychology · doi:10.1002/jts5.23 · Cited by 65
Veit, S., & Thijsen, L. (2021) · Journal of Ethnic and Migration Studies · doi:10.1080/1369183x.2019.1622825 · Cited by 65
Fibbi, R., Midtbøen, A. H., & Simon, P. (2021) · IMISCOE research series · doi:10.1007/978-3-030-67281-2 · Cited by 72
Self-citationPortocarrero, S., & Carter, J. T. (2022) · Sociology Compass · doi:10.1111/soc4.13001 · Cited by 73
Hora, M. T. (2019) · Higher Education · doi:10.1007/s10734-019-00411-6 · Cited by 75
A post‐liberal theory of stratification
Jackson, M., & Grusky, D. B. (2018) · British Journal of Sociology · doi:10.1111/1468-4446.12505 · Cited by 64
Check the box! How to deal with automation bias in AI-based personnel selection
Kupfer, C., Prassl, R., Fleiß, J., Malin, C., Thalmann, S., & Kubicek, B. (2023) · Frontiers in Psychology · doi:10.3389/fpsyg.2023.1118723 · Cited by 59
“Hence, AI-based systems shall address a well-known challenge in personnel selection, namely the selection of applicants purely based on their qualifications and expected job performance, without (oftentimes unconscious and unintended) discrimination based on personal characteristics such as ethnicity (Quillian et al.,…”
BackgroundOrupabo, J., & Nadim, M. (2019) · Gender Work and Organization · doi:10.1111/gwao.12378 · Cited by 58
Race and workplace discrimination
Daniels, S. R., & Thornton, L. M. (2019) · Equality Diversity and Inclusion An International Journal · doi:10.1108/edi-06-2018-0105 · Cited by 68
Doing hair, doing race: the influence of hairstyle on racial perception across the US
Sims, J. P., Pirtle, W. N. L., & Johnson-Arnold, I. (2019) · Ethnic and Racial Studies · doi:10.1080/01419870.2019.1700296 · Cited by 61
Fiscella, K. A., Epstein, R. M., Griggs, J. J., Marshall, M., & Shields, C. G. (2021) · PLoS ONE · doi:10.1371/journal.pone.0257794 · Cited by 56
Andrus, M., & Villeneuve, S. (2022) · ACM Conference on Fairness, Accountability, and Transparency (FAccT) · doi:10.1145/3531146.3533226 · Cited by 59
Computer says ‘no’: Exploring systemic bias in ChatGPT using an audit approach
Lippens, L. (2024) · Computers in Human Behavior Artificial Humans · doi:10.1016/j.chbah.2024.100054 · Cited by 68
Gaddis, S. M. (2019) · Sociology of Race and Ethnicity · doi:10.1177/2332649219870183 · Cited by 55
What's Wrong with Machine Bias
Castro, C. (2019) · Ergo an Open Access Journal of Philosophy · doi:10.3998/ergo.12405314.0006.015 · Cited by 54
Liaquat, U., Jost, J. T., & Balcetis, E. (2023) · Social Issues and Policy Review · doi:10.1111/sipr.12093 · Cited by 62
Gillispie-Bell, V. (2021) · Obstetrics and Gynecology · doi:10.1097/aog.0000000000004226 · Cited by 54
Mateo, C. M., & Williams, D. R. (2020) · Academic Medicine · doi:10.1097/acm.0000000000003683 · Cited by 56
Mitigating Bias in Algorithmic Employment Screening: Evaluating Claims and Practices
Raghavan, M., Barocas, S., Kleinberg, J., & Levy, K. (2019) · SSRN Electronic Journal · doi:10.2139/ssrn.3408010 · Cited by 51
Research on Anti-Black Racism in Organizations: Insights, Ideas, and Considerations
King, D. D., Hall, A. V., Johnson, L. U., CARTER, J. H., Burrows, D. N., & Samuel, N. N. (2022) · Journal of Business and Psychology · doi:10.1007/s10869-022-09804-4 · Cited by 58
Gaddis, S. M., & Ghoshal, R. (2019) · Socius Sociological Research for a Dynamic World · doi:10.1177/2378023120972287 · Cited by 51
The Enduring Significance of Ethno-Racial Inequalities in Poverty in the U.S., 1993–2017
Baker, R., Brady, D., Parolin, Z., & Williams, D. T. (2021) · Population Research and Policy Review · doi:10.1007/s11113-021-09679-y · Cited by 59
Spencer, R. A., Livingston, M. D., Woods-Jaeger, B. A., Rentmeester, S. T., Sroczynski, N., & Komro, K. A. (2020) · Social Science & Medicine · doi:10.1016/j.socscimed.2020.113355 · Cited by 50
Which Information Matters? Measuring Landlord Assessment of Tenant Screening Reports
So, W. (2022) · Housing Policy Debate · doi:10.1080/10511482.2022.2113815 · Cited by 50
Brown-Iannuzzi, J. L., Cooley, E., McKee, S. E., & Hyden, C. (2018) · Journal of Experimental Social Psychology · doi:10.1016/j.jesp.2018.11.006 · Cited by 50
Colen, C. G., Li, Q., Reczek, C., & Williams, D. R. (2019) · Journal of Health and Social Behavior · doi:10.1177/0022146519887347 · Cited by 50
Long-Run Changes in Underrepresentation After Affirmative Action Bans in Public Universities
Long, M. C., & Bateman, N. A. (2020) · Educational Evaluation and Policy Analysis · doi:10.3102/0162373720904433 · Cited by 54
Racially Distinctive Names Signal Both Race/Ethnicity and Social Class
Crabtree, C. D., Gaddis, S. M., Holbein, J. B., & Larsen, E. N. (2022) · Sociological Science · doi:10.15195/v9.a18 · Cited by 49
Artificial Intelligence in Human Resource Management: Recent Trends and Research Agenda
Mer, A. (2023) · Emerald Group Publishing Limited eBooks · doi:10.1108/s1569-37592023000111b003 · Cited by 59
Raghavan, M. (2023) · ACM eBooks · doi:10.1145/3603195.3603207 · Cited by 49
Metadata
- Authors
- Quillian, L., Pager, D., Hexel, O., & Midtbøen, A. H.
- Affiliations
- Northwestern University (US)
- Harvard University (US)
- Institute for Social Research (NO)
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2017-09-12
- Volume
- 114
- Issue
- 41
- Pages
- 10870-10875
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC5642692
- OpenAlex
- W2756054281
- Cited by
- 887
- References
- 36
- Citations by year
- 2026: 88 · 2025: 121 · 2024: 111 · 2023: 138 · 2022: 130 · 2021: 104 · 2020: 76 · 2019: 79 · 2018: 29 · 2017: 4
- FWCI
- 13.97
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- BIBSYS Brage (BIBSYS (Norway)) (acceptedVersion)
- HAL (submittedVersion, cc-by)
- NORA - Norwegian Open Research Archives (submittedVersion, other-oa)
- Funders
- Russell Sage Foundation (RSF) (88-15-06)
- Northwestern Institute for Policy Research (N/A)
- Topics
- Social Sciences › Sociology and Political Science › Names, Identity, and Discrimination Research
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Experimental Behavioral Economics Studies
- Social Sciences › Sociology and Political Science › Social and Intergroup Psychology
- Keywords
- racial discrimination in hiring, callbacks, African Americans, Hispanic Americans, labor market discrimination, field experiments, applicant gender
- MeSH terms
- Humans, Personnel Selection, Racism, Social Discrimination
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
A language model drew the claims from the paper on 2026-11-04, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
A second model labelled each claim on 2026-11-04 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review