Key Takeaways
- 67% of women in construction report discrimination as a major barrier in 2023
- Work-life balance challenges cited by 54% of female workers
- Lack of mentorship affects 49% of women advancing in trades
- In 2022, women made up 11.2% of the total construction industry workforce in the United States, totaling approximately 1.01 million women workers
- As of 2023, female representation in construction grew by 14.5% from 2020 levels, reaching 1.2 million women
- Women comprise 10.9% of construction laborers specifically, with 95,000 women in this role in 2022
- Women in fatality rates 8.2 per 100,000 workers vs. 12.1 for men in 2022
- Nonfatal injury rate for women: 2.8 cases per 100 full-time workers, lower than men's 3.5 in 2023
- 22% of women report harassment as safety concern in 2023 surveys
- 45% of women in construction have completed vocational training programs by 2023
- Women apprentices in construction programs: 14.2% enrollment increase since 2020
- 62% of female construction workers have some postsecondary education, vs. 48% men 2022
- Women construction workers earn a median weekly wage of $1,050 in 2022, 92% of men's $1,142
- Female construction managers earn $102,000 annually on average vs. $118,000 for men in 2023
- Women in carpentry earn 15% less than male counterparts, median $48,200 vs. $56,700 in 2022
In 2023, most women in construction face discrimination, harassment, and advancement gaps alongside significant wage inequality.
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Barriers
Barriers Interpretation
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Representation
Representation Interpretation
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Safety
Safety Interpretation
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Training
Training Interpretation
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Wages
Wages 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.
Felix Zimmermann. (2026, February 13). Women In Construction Statistics. Gitnux. https://gitnux.org/women-in-construction-statistics
Felix Zimmermann. "Women In Construction Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/women-in-construction-statistics.
Felix Zimmermann. 2026. "Women In Construction Statistics." Gitnux. https://gitnux.org/women-in-construction-statistics.
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