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Quantifying behavior-based gender discrimination on collaborative platforms
Orsolya Vásárhelyi1,2,3, Balázs Vedres3,4,5
1Center for Collective Learning, Corvinus Institute for Advanced Studies, Corvinus University of Budapest, Fővám tér 8., Budapest 1093, Hungary.
Abstract:
Digital collaborative platforms have become crucial venues of career advancement and individual success in many creative fields, from engineering to the arts. Gender discrimination related to behavioral choices of users is a key component to gendered disadvantage on platforms. Such platforms carried the promise of opening avenues of advancement to previously discriminated groups, such as women, as platforms lack managerial gatekeepers with conventional prejudice. We analyzed the extent of behavior-based gender discrimination on two digital platforms, GitHub and Behance, focused on software development and fine arts and design. We found that the main cause of women's disadvantage in attention, success, and survival is largely due to the gender typicality of their behavior that varies between 60 and 90% of the total disadvantage of women. Men and women are penalized if they follow highly female-like behavior, while categorical gender is no longer significant. As platforms employ algorithmic tools and AI systems to manage users' activity and visibility, and recommend new projects to collaborate, stereotypes associated with behavior can have long-lasting consequences.
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