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Exploring the Role of Women in Hugging Face Organizations

Published: March 21, 2025 | arXiv ID: 2503.17000v1

By: Maria Tubella Salinas, Alexandra González, Silverio Martínez-Fernández

Potential Business Impact:

Fixes unfairness in computer coding groups.

Business Areas:
Facial Recognition Data and Analytics, Software

Background: Despite its impact on innovation, gender diversity remains far from fully being achieved in open-source projects. Aims: We examine gender diversity in Hugging Face (HF) organizations, investigating its impact on innovation and team dynamics in open-source development projects. Method: We conducted a repository mining study, focusing on ML model development projects on HF, to explore the involvement of women in collaborative processes. Results: Women are highly underrepresented in both organizations and commits distribution, which is also found when analyzing individual developers. Conclusions: Addressing gender disparities is essential to create more equitable, diverse, and inclusive open-source ecosystems.

Country of Origin
🇪🇸 Spain

Repos / Data Links

Page Count
15 pages

Category
Computer Science:
Software Engineering