Key Takeaways
- 40% of speaking characters in 2023 top-grossing movies were from underrepresented racial/ethnic groups
- 15.9% of characters in 2022-23 broadcast TV were from underrepresented racial/ethnic groups
- 19.4% of characters in 2022-23 broadcast TV were from underrepresented racial/ethnic groups that are not Black
- 30% of speaking characters in 2023 top-grossing movies were LGBTQ+
- 12.2% of characters in 2022-23 broadcast TV were LGBTQ+
- 4% of characters in 2022-23 broadcast TV were transgender
- 24% of speaking characters in 2023 top-grossing movies were women
- 41.6% of female leads in 2023 films were women
- 21% of speaking characters in 2023 top-grossing movies were women
- 10% of characters were disabled in 2023 top-grossing movies
- 4.3% of characters in top films were portrayed with a disability
- 34% of US adults with disabilities report being underrepresented in media
- 19.3% of surveyed producers said they have difficulty hiring diverse talent for major roles
- 58% of respondents in a 2022 study said they believe media stereotypes affect social attitudes
- 29% of media representations of underrepresented groups were stereotypical in a content analysis
Representation remains limited and often stereotyped across film, TV, gaming, and advertising, especially for disability, LGBTQ+, and minorities.
Racial and Ethnic Representation
Racial and Ethnic Representation Interpretation
LGBTQ+ Representation
LGBTQ+ Representation Interpretation
Gender Representation
Gender Representation Interpretation
Disability and Neurodiversity Representation
Disability and Neurodiversity Representation Interpretation
Underrepresentation and Bias
Underrepresentation and Bias 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). Representation In Media Statistics. Gitnux. https://gitnux.org/representation-in-media-statistics
Henrik Dahl. "Representation In Media Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/representation-in-media-statistics.
Henrik Dahl. 2026. "Representation In Media Statistics." Gitnux. https://gitnux.org/representation-in-media-statistics.
References
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