Key Takeaways
- 11% of global GDP is lost due to gender inequality, per estimates referenced in the 2023 World Economic Forum gender report
- In OECD countries, women spend 2.4x more time than men on unpaid care work (OECD 2023 gender equality indicators)
- In 2023, the median weekly earnings for women were $1,001 compared with $1,136 for men in the U.S., a gap of $135
- Women are 25% less likely than men to be employed in managerial roles in some OECD economies, per OECD labor gender gap analyses summarized in 2023
- Women held 49.6% of total employment in the EU-27 in 2023 (Eurostat employment by sex)
- Female unemployment rate was 6.0% and male unemployment rate 6.1% in the EU-27 in 2023 (Eurostat harmonized unemployment rate by sex)
- 47% of women worldwide report experiencing gender-based violence at least once in their lifetime (WHO 2021 global estimate)
- 31% of women in the U.S. report experiencing stalking (lifetime prevalence), per the 2023 National Crime Victimization Survey (NCVS) report.
- Women received 61% of undergraduate degrees in 2019 in the U.S. (NCES), indicating educational attainment parity with varying persistence into labor force
- In 2022, women earned 58% of bachelor’s degrees in the U.S., per NCES Education Digest
- In the WEF Global Gender Gap Report 2023, the estimated time to close the overall gap is 131 years (2023 projection)
- The WEF Global Gender Gap Report 2024 ranks gender inequality as largest in economic participation with the lowest parity score among subindices
- In the U.S., women’s share of STEM degrees is 35% for computer science and 44% for biological sciences (NCES/NSF compilation for recent years)
- Women represent 29% of engineering professionals in the U.S. labor force (U.S. BLS/NSF-reported STEM workforce breakdown, 2022)
- Women account for 36% of data scientists worldwide in 2023 Stack Overflow Developer Survey gender breakdown
Gender inequality costs the world 11 percent of GDP and still takes 131 years to close.
Economic Impact
Economic Impact Interpretation
Pay And Earnings
Pay And Earnings Interpretation
Workforce Participation
Workforce Participation Interpretation
Workplace Safety
Workplace Safety Interpretation
Education To Employment
Education To Employment Interpretation
Policy And Indices
Policy And Indices Interpretation
Stem Representation
Stem Representation Interpretation
Labor Market
Labor Market Interpretation
Leadership Representation
Leadership Representation Interpretation
Education & Skills
Education & Skills Interpretation
Health & Safety
Health & Safety Interpretation
Gender Income & Wealth
Gender Income & Wealth 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.
Henrik Dahl. (2026, February 13). Gender Gap Statistics. Gitnux. https://gitnux.org/gender-gap-statistics
Henrik Dahl. "Gender Gap Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/gender-gap-statistics.
Henrik Dahl. 2026. "Gender Gap Statistics." Gitnux. https://gitnux.org/gender-gap-statistics.
References
- 1weforum.org/publications/global-gender-gap-report-2023/
- 2oecd.org/gender/data/unpaid-time.htm
- 4oecd.org/gender/data/oecd-gender-data-portal.htm
- 21oecd.org/employment/work-life-balance.htm
- 29oecd.org/financial/education/global-financial-literacy-excel-data/
- 3census.gov/library/publications/2024/demo/p60-284.html
- 5ec.europa.eu/eurostat/databrowser/view/lfsi_emp_a__custom_1015758/default/table?lang=en
- 6ec.europa.eu/eurostat/databrowser/view/une_rt_m/default/table?lang=en
- 18ec.europa.eu/eurostat/databrowser/view/tesem010/default/table?lang=en
- 19ec.europa.eu/eurostat/databrowser/view/tespm030/default/table?lang=en
- 20ec.europa.eu/eurostat/databrowser/view/tespm060/default/table?lang=en
- 7bls.gov/cps/cpsaat01.htm
- 8who.int/news-room/fact-sheets/detail/violence-against-women
- 9bjs.ojp.gov/library/publications/criminal-victimization-2023
- 10nces.ed.gov/programs/digest/d21/tables/dt21_318.20.asp
- 11nces.ed.gov/programs/digest/d23/tables/dt23_318.10.asp
- 12www3.weforum.org/docs/WEF_GGGR_2023.pdf
- 13www3.weforum.org/docs/WEF_GGGR_2024.pdf
- 14ncses.nsf.gov/pubs/nsf24318/report
- 15ncses.nsf.gov/pubs/nsf22313/report
- 16survey.stackoverflow.co/2023/
- 17oecd-ilibrary.org/employment/discrimination-at-work-and-gender-equality-in-oecd-countries_0c8b3a5d-en
- 22www2.deloitte.com/us/en/insights/focus/human-capital-trends.html
- 23nap.nationalacademies.org/catalog/26042/the-innovations-and-impacts-of-diversity-equity-and-inclusion-in-stem
- 24thelancet.com/journals/lanpub/article/PIIS2468-2667(21)00318-3/fulltext
- 25ncbi.nlm.nih.gov/pmc/articles/PMC8791460/
- 26unicef-irc.org/publications/1333-what-women-and-girls-need-to-survive.html
- 27worldbank.org/en/publication/globalfindex
- 28wid.world/data/







