| 来源类型 | Discussion paper |
| 规范类型 | 论文 |
| 来源ID | DP16960 |
| DP16960 Gender Differences in Reference Letters: Evidence from the Economics Job Market | |
| Markus Eberhardt; Giovanni Facchini; Valeria Rueda | |
| 发表日期 | 2022-01-28 |
| 出版年 | 2022 |
| 语种 | 英语 |
| 摘要 | Academia, and economics in particular, faces increased scrutiny because of gender imbalance. This paper studies the job market for entry-level faculty positions. We employ machine learning methods to analyze gendered patterns in the text of 9,000 reference letters written in support of 2,800 candidates. Using both supervised and unsupervised techniques, we document widespread differences in the attributes emphasized. Women are systematically more likely to be described using "grindstone" terms and at times less likely to be praised for their ability. Given the time and effort letter writers devote to supporting their students, this gender stereotyping is likely due to unconscious biases. |
| 主题 | Labour Economics ; Public Economics |
| 关键词 | Gender Natural language processing Gender stereotypes Diversity |
| URL | https://cepr.org/publications/dp16960 |
| 来源智库 | Centre for Economic Policy Research (United Kingdom) |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/545903 |
| 推荐引用方式 GB/T 7714 | Markus Eberhardt,Giovanni Facchini,Valeria Rueda. DP16960 Gender Differences in Reference Letters: Evidence from the Economics Job Market. 2022. |
| 条目包含的文件 | 条目无相关文件。 | |||||
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