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Cited by 37

The DOI matches its Crossref record; 95 of the 95 references it cites were found in a registry or an index.

A Meta-Analysis of Hiring Discrimination Against Muslims and Arabs

Bartkoski, Timothy, Lynch, Ellen, Witt, Chelsea, Rudolph, Cort·2018·Personnel Assessment and Decisions

Abstract

Muslim and Arab individuals are discriminated against in almost all domains. Recently, there has been a focus on examining the treatment of these groups in the work setting. Despite the great number of primary studies examining this issue, there has not yet been a quantitative review of the research literature. To fill this gap, this meta-analysis examined the presence and magnitude of hiring discrimination against Muslim and Arab individuals. Using 46 independent effect sizes from 26 sources, we found evidence of discrimination against Muslim and Arab people in employment judgments, behaviors, and decisions across multiple countries. Moderator analyses revealed that discrimination is stronger in field settings, when actual employment decisions are made, and when experimental studies used “Arab” (vs. “Muslim”) targets. However, primary studies provide inconsistent and inaccurate distinctions between Arabs and Muslims, therefore future work should be cautious in categorizing the exact aspect of identity being studied.

Overview

Integrity signals

Registry

Crossref · 10.25035/pad.2018.02.001

Cites

95 of 95 references verified0 citation errors · 0 not checkable

Statistics

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Verification

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Citations

Cites

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Metadata

Authors
Bartkoski, T., Lynch, E., Witt, C., & Rudolph, C.
Venue
Personnel Assessment and Decisions
Published
2018-12
Volume
4
Issue
2
ISSN
2377-8822
Cited by
37
References
95

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.

Statistics and arithmetic are recomputed, not judged.

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Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.