通过在线招聘平台监测招聘歧视
Dominik Hangartner1,2,3, Daniel Kopp4,5, Michael Siegenthaler4,5
1Public Policy Group, ETH Zurich, Zurich, Switzerland. dominik.hangartner@gess.ethz.ch.
Nature
|January 21, 2021
概括
对少数民族和妇女的雇佣歧视仍然存在,招聘人员与她们联系的频率减少了4-19%. 这项研究引入了一种监测和理解招聘偏见的新方法.
科学领域:
- 劳动经济学
- 劳动社会学
- 计算社会科学
背景情况:
- 劳动力市场对妇女和少数民族的不利影响已得到充分证实.
- 雇佣歧视的确切程度和机制尚不清楚.
- 传统的对应性测试在范围和同时分析方面存在局限性.
研究的目的:
- 开发和应用一种用于量化招聘歧视的新方法.
- 调查在线招聘中基于种族和性别的歧视.
- 提供一个持续监测雇佣偏见的工具.
主要方法:
- 在就业网站上对招聘者搜索行为进行综合追踪.
- 使用监督机器学习来控制可观察到的求职者特征.
- 将该方法应用于瑞士公共就业服务的在线平台.
主要成果:
- 对于来自移民和少数民族的个人来说,招聘人员接触率降低了4-19%.
- 女性在男性占主导地位的职业中面临7%的接触处罚,而男性在女性占主导地位的职业中面临相反的情况.
- 没有证据表明招聘人员花费更少的时间来评估少数民族的个人资料.
结论:
- 开发的方法提供了一种可扩展,非侵入性和成本高效的方法来检测招聘歧视.
- 调查结果显示,在招聘人员接触率方面,存在显著的种族和性别差异.
- 该工具可以为旨在减少招聘歧视的政策干预提供信息.
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