Key Takeaways
- In the top 100 grossing films of 2022, women comprised only 28.5% of speaking or named characters
- Female directors helmed just 16% of the top 250 films in 2022, down from 18% in 2021
- Women made up 22.7% of directors, 26.2% of producers, and 21.6% of writers on the 2022 top-grossing films
- In top 100 films 2021, Black actors were 13.4% of leads despite being 13.6% of U.S. population
- Latinos comprised only 5.7% of speaking roles in top films 2022
- Asian actors in speaking roles: 7.5% in 2022 top 100 films, up from 4.1% in 2019
- In 2022 top films, LGBTQ+ characters were only 1.1% of speaking roles
- GLAAD report 2023: 28% of top films had LGBTQ characters, up from 20% 2021
- Transgender characters: 0.3% across 1000+ films 2019-2022
- In 2022, characters with disabilities were 2.3% of speaking roles in top films
- Visible disabilities on screen: 1.2% leads 2022
- Autistic characters: 0.1% accurate rep 2015-2022
- In 2022, actors over 50 were 28% of speaking roles despite 35% workforce age
- Directors over 60: 45% of top 250 in 2022
- Under 40 leads: 55% in top films 2022
Hollywood's diversity statistics reveal persistent inequity behind and in front of the camera.
Age Diversity
Age Diversity Interpretation
Disability Representation
Disability Representation Interpretation
Gender Diversity
Gender Diversity Interpretation
LGBTQ+ Representation
LGBTQ+ Representation 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.
Alexander Schmidt. (2026, February 13). Diversity Equity And Inclusion In The Movie Industry Statistics. Gitnux. https://gitnux.org/diversity-equity-and-inclusion-in-the-movie-industry-statistics
Alexander Schmidt. "Diversity Equity And Inclusion In The Movie Industry Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/diversity-equity-and-inclusion-in-the-movie-industry-statistics.
Alexander Schmidt. 2026. "Diversity Equity And Inclusion In The Movie Industry Statistics." Gitnux. https://gitnux.org/diversity-equity-and-inclusion-in-the-movie-industry-statistics.
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