five

Descriptive sample statistics.

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NIAID Data Ecosystem2026-05-02 收录
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https://figshare.com/articles/dataset/Descriptive_sample_statistics_/26834621
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资源简介:
Selection interviews have long been integral to medical school admissions, yet their limited predictive validity and susceptibility to bias raise concerns. This study delves into potential interviewer bias within the dynamics of interviewee and interviewer gender. We analyze a dataset of 5,200 applicants and over 370 selection committees engaged in semi-structured interviews from 2006 to 2019 at a large German medical school with multiple linear and non-linear regression analyses. Our findings reveal that all-female committees tended to award male candidates, on average, one point more than their female counterparts, significantly enhancing the chances of submission for male applicants despite lower academic grades, which constituted 51% of the selection process points. All-male and mixed-gender committees exhibited similar ratings for both genders. The role of valuing voluntary services emerged prominently: all-male and mixed committees acknowledged women’s volunteer work but not men’s, while all-female committees demonstrated the opposite pattern. Our results attribute variations in interview outcomes to the absence of standardization, such as insufficient interviewer training, divergent rating strategies, variations in interviewer experience, and imbalances in candidate allocation to selection committees, rather than to a “gender bias”, for example by favoritism of males because of their gender.
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2024-08-26
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