量化协作平台上的间接性别歧视
Quantifying Indirect Gender Discrimination on Collaborative Platforms
AI总结：
该研究量化了 GitHub 和 Behance 平台上的间接性别歧视，发现女性劣势的 60% 至 90% 源于行为刻板印象驱动的间接歧视，揭示了算法管理下性别不平等的形成机制。
摘要：
数字协作平台已成为许多创意领域（从工程到艺术）职业发展和个人成功的关键场所。间接性别歧视是平台上性别劣势的一个关键组成部分。这类平台曾承诺为先前受歧视的群体（如女性）开辟晋升途径，因为平台缺乏带有传统偏见的管理把关者。我们分析了两个不同平台——GitHub 和 Behance——上间接性别歧视的程度，这两个平台分别专注于软件开发和美术与设计。我们发现，女性在关注度、成功和留存方面的劣势主要源于间接歧视，其占女性总劣势的 60% 至 90%。如果男性和女性表现出高度女性化的行为，他们都会受到惩罚，而类别性别的影响因结果和领域而异。由于平台采用算法工具和 AI 系统来管理用户活动、可见性并推荐新项目进行协作，根植于行为的刻板印象可能会产生长期后果。
英文摘要：
Digital collaborative platforms have become crucial venues of career advancement and individual success in many creative fields, from engineering to the arts. Indirect gender discrimination 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 indirect gender discriminatory on two diverse 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 indirect discrimination that varies between 60-90\% of total female disadvantage. Men and women are penalized if they follow highly female-like behavior, while categorical gender's impact varies by outcome and field. As platforms employ algorithmic tools and AI systems to manage users' activity, visibility and recommend new projects to collaborate, stereotypes rooted in behavior can have long-lasting consequences.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
