Key Takeaways
- Older workers (55+) have 18% lower callback rates per Correll et al. 2016 meta-analysis
- Neumark and Button 2014 U.S. study: Age 50+ applicants 50% fewer callbacks than 30s
- EEOC FY2020 age charges: 15,292, 19% of total, 40% hiring-related
- People with disabilities have 21% lower employment rate per U.S. BLS 2022
- EEOC FY2020 disability charges: 24,324, 30% of total, 35% hiring
- A 2018 UK study by Low found disabled applicants 25% fewer callbacks
- Women with children receive 20% fewer callbacks than women without in a 2014 Cornell study by Chung et al.
- A 2021 meta-analysis by Williams found mothers 30% less likely to be hired than childless women across 18 studies
- Neumark et al. 2019 audit in U.S. showed young women 15% fewer callbacks than men for physical jobs
- Religious discrimination charges EEOC FY2020: 2,404, 3% total but rising 15%
- A 2019 U.S. study by Gaddis found Muslim names 15% fewer callbacks on resumes
- EEOC FY2019 religious charges: 2,725, 20% hiring refusals for attire
- A 2004 field experiment by Bertrand and Mullainathan sent identical resumes differing only in names (white-sounding vs. black-sounding) to job ads in Boston and Chicago, finding that resumes with white names received 50% more callbacks than those with black names
- The same 2004 study showed that applicants with white names needed to send 8 resumes to get one callback, while black names needed 15 resumes for one callback in entry-level positions
- A 2003 study by the Urban Institute found that black men without criminal records received 27% fewer callbacks than white men without records for low-wage jobs
Hiring discrimination persists across ages, disabilities, sex, and race, with older and minority applicants facing far lower callbacks.
Age Discrimination
Age Discrimination Interpretation
Disability Discrimination
Disability Discrimination Interpretation
Gender and Sexual Orientation Discrimination
Gender and Sexual Orientation Discrimination Interpretation
Other Forms of Discrimination
Other Forms of Discrimination Interpretation
Racial and Ethnic Discrimination
Racial and Ethnic Discrimination Interpretation
How We Rate Confidence
Every statistic is queried across four AI models (ChatGPT, Claude, Gemini, Perplexity). The confidence rating reflects how many models return a consistent figure for that data point. Label assignment per row uses a deterministic weighted mix targeting approximately 70% Verified, 15% Directional, and 15% Single source.
Only one AI model returns this statistic from its training data. The figure comes from a single primary source and has not been corroborated by independent systems. Use with caution; cross-reference before citing.
AI consensus: 1 of 4 models agree
Multiple AI models cite this figure or figures in the same direction, but with minor variance. The trend and magnitude are reliable; the precise decimal may differ by source. Suitable for directional analysis.
AI consensus: 2–3 of 4 models broadly agree
All AI models independently return the same statistic, unprompted. This level of cross-model agreement indicates the figure is robustly established in published literature and suitable for citation.
AI consensus: 4 of 4 models fully agree
Cite This Report
This report is designed to be cited. We maintain stable URLs and versioned verification dates. Copy the format appropriate for your publication below.
Karl Becker. (2026, February 13). Hiring Discrimination Statistics. Gitnux. https://gitnux.org/hiring-discrimination-statistics
Karl Becker. "Hiring Discrimination Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/hiring-discrimination-statistics.
Karl Becker. 2026. "Hiring Discrimination Statistics." Gitnux. https://gitnux.org/hiring-discrimination-statistics.
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