Key Takeaways
- In the US, women receive 87% fewer callbacks for jobs than men with identical resumes in male-dominated fields 2023 study
- UK blind recruitment trials show women 15% less likely to be shortlisted in STEM
- India 2022: Women 30% less likely to be hired for tech roles per resume audit
- Globally, women CEOs in Fortune 500 are only 10.6% in 2023
- US S&P 500 boards have 33% women in 2023, up from 17% in 2010
- UK FTSE 100 has 38% women on boards in 2023
- In the United States, women earn 84% of what men earn on average in 2023, with the gap widening to 76% for women without children compared to men with children
- Globally, the gender pay gap stands at 20% in 2023, meaning women earn 80 cents for every dollar men earn for similar work
- In the UK, full-time working women earned 7.3% less per hour than men in 2023, rising to 14.9% when including part-time workers
- Globally, women in managerial roles earn 23% less than men in 2022
- In the US, women are 48% less likely to be promoted to manager than men in 2023
- UK women hold only 29% of senior management positions despite being 47% of the workforce in 2023
- 85% of US women report experiencing sexual harassment at work in their lifetime
- In India, 53% of women face workplace sexual harassment per 2022 survey
- UK 2021 survey found 68% of women experienced harassment at work
Hiring, pay, and promotion still disadvantage women, with bias and harassment driving worse outcomes.
Hiring and Recruitment Discrimination
Hiring and Recruitment Discrimination Interpretation
Leadership and Representation Gaps
Leadership and Representation Gaps Interpretation
Pay and Wage Disparity
Pay and Wage Disparity Interpretation
Promotion and Career Advancement
Promotion and Career Advancement Interpretation
Sexual Harassment and Hostile Work Environment
Sexual Harassment and Hostile Work Environment 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.
Christopher Morgan. (2026, February 13). Gender Discrimination In Workplace Statistics. Gitnux. https://gitnux.org/gender-discrimination-in-workplace-statistics
Christopher Morgan. "Gender Discrimination In Workplace Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/gender-discrimination-in-workplace-statistics.
Christopher Morgan. 2026. "Gender Discrimination In Workplace Statistics." Gitnux. https://gitnux.org/gender-discrimination-in-workplace-statistics.
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