# Measuring Gender Representation in Animated Films

arXiv: https://arxiv.org/abs/2608.21429 · HTML: https://mlsanity.com/paper/2608.21429/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 10 of its 45 references that are in the map.
- First posted on arXiv 17 Aug 2026.

## Builds on (most cited first, 10 of 10)

- [Microsoft COCO: Common Objects in Context](https://mlsanity.com/paper/1405.0312/) (2014)
- [DINOv2: Learning Robust Visual Features without Supervision](https://mlsanity.com/paper/2304.07193/) (2023)
- [YOLOv4: Optimal Speed and Accuracy of Object Detection](https://mlsanity.com/paper/2004.10934/) (2020)
- [WIDER FACE: A Face Detection Benchmark](https://mlsanity.com/paper/1511.06523/) (2015)
- [TransNet V2: An effective deep network architecture for fast shot transition detection](https://mlsanity.com/paper/2008.04838/) (2020)
- [RT-DETRv2: Improved Baseline with Bag-of-Freebies for Real-Time Detection Transformer](https://mlsanity.com/paper/2407.17140/) (2024)
- [Ultralytics YOLO26: Unified Real-Time End-to-End Vision Models](https://mlsanity.com/paper/2606.03748/) (2026)
- [TinaFace: Strong but Simple Baseline for Face Detection](https://mlsanity.com/paper/2011.13183/) (2020)
- [Character-Centric Understanding of Animated Movies](https://mlsanity.com/paper/2509.12204/) (2025)
- [YOLOE-26: Integrating YOLO26 with YOLOE for Real-Time Open-Vocabulary Instance Segmentation](https://mlsanity.com/paper/2602.00168/) (2026)

## Built on by (most cited first, 1 of 1)

- [Measuring the evolution of camera distance across a century of film](https://mlsanity.com/paper/2609.31734/) (2026)

## Abstract (arXiv)

Animated films--often developed with an audience of children in mind--are an important vector for enculturation, and empirical work that has examined the representation of gender at scale in these films has largely focused on counting the gender composition of the cast rather than deploying a more fine-grained instrument (such as assessing the visibility of those characters in overall screentime). In this work, we develop a computational pipeline for recognizing animated characters in these films, and use it to test several hypotheses about gender representation in a corpus of 224 popular animated movies. We find that while the overall representation of female characters in animated films largely tracks with those of live-action films (over the period 1980-2025), we see stark differences between the representation of human characters (much greater representation among women and girls) and non-humans (largely male). Contrary to past work on Disney, we do not see female characters declining in antagonist roles in animated films, and characters who are women and girls are much more likely to share scenes together than their live action contemporaneous counterparts.