Key Takeaways
- In mining leadership, people with disabilities held 3.2% of executive positions in U.S. 2023 firms.
- Heavy construction companies reported 4.1% workforce with disabilities in 2022 EEOC data.
- In oil and gas, 2.8% of employees disclosed disabilities in 2023 surveys, with accommodations boosting retention by 22%.
- In heavy industry leadership, women CEOs were 4.1% in U.S. firms 2023.
- Ethnic minorities in executive roles 12.3% across heavy manufacturing 2022.
- Pay gap for women in mining was 18.7% less than men in 2023 U.S. data.
- In 2022, women comprised only 16.1% of the total workforce in the U.S. manufacturing sector, which is a key part of heavy industry, down from 18.2% in 2019 due to pandemic-related shifts.
- Female representation in heavy construction roles reached 10.8% in 2023, with projections for slow growth to 12% by 2030 amid targeted recruitment efforts.
- In the oil and gas extraction subsector of heavy industry, women held 22.3% of professional positions but only 7.4% of field operator roles in 2021.
- In heavy industry, LGBTQ+ employees self-identified at 4.2% in U.S. 2023 surveys.
- Mining firms reported 3.1% LGBTQ+ workforce in 2022 global poll.
- Oil and gas sector LGBTQ+ inclusion at 5.7% disclosed in 2023 Deloitte study.
- Black or African American workers made up 10.2% of the U.S. heavy construction workforce in 2022, compared to 12.6% national average.
- In mining, Hispanic or Latino employees represented 17.4% in 2023, highest in surface mining at 22.1%.
- Asian workers comprised 5.8% of oil and gas heavy industry roles in U.S. 2022 data.
Heavy industry inclusion remains low, with disability and representation gaps persisting despite measurable DEI gains.
Disability Inclusion
Disability Inclusion Interpretation
Equity and Leadership
Equity and Leadership Interpretation
Gender Diversity
Gender Diversity Interpretation
LGBTQ+ Inclusion
LGBTQ+ Inclusion Interpretation
Racial/Ethnic Diversity
Racial/Ethnic Diversity 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.
David Kowalski. (2026, February 13). Diversity Equity And Inclusion In The Heavy Industry Statistics. Gitnux. https://gitnux.org/diversity-equity-and-inclusion-in-the-heavy-industry-statistics
David Kowalski. "Diversity Equity And Inclusion In The Heavy Industry Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/diversity-equity-and-inclusion-in-the-heavy-industry-statistics.
David Kowalski. 2026. "Diversity Equity And Inclusion In The Heavy Industry Statistics." Gitnux. https://gitnux.org/diversity-equity-and-inclusion-in-the-heavy-industry-statistics.
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