Although different organizations have defined policies towards diversity in academia, many argue that minorities are still disadvantaged in university admissions due to biases. Extensive research has been conducted on detecting partiality patterns in the academic community. However, in the last few decades, limited research has focused on assessing gender and nationality biases in graduate admission results of universities. In this study, we collected a novel and comprehensive dataset containing information on approximately 14,000 graduate students majoring in computer science (CS) at the top 25 North American universities. We used statistical hypothesis tests to determine whether there is a preference for students’ gender and nationality in the admission processes. In addition to partiality patterns, we discuss the relationship between gender/nationality diversity and the scientific achievements of research teams. Consistent with previous studies, our findings show that there is no gender bias in the admission of graduate students to research groups, but we observed bias based on students’ nationality.

尽管不同的组织制定了学术界多元化政策，但许多人认为，由于偏见，少数族裔在大学招生中仍然处于不利地位。学术界已经对检测偏向模式进行了广泛的研究。然而，在过去的几十年里，有限的研究集中在评估大学研究生录取结果中的性别和国籍偏见。在这项研究中，我们收集了一个新颖且全面的数据集，其中包含北美 25 所顶尖大学的大约 14,000 名计算机科学 (CS) 专业研究生的信息。我们使用统计假设检验来确定录取过程中是否存在对学生性别和国籍的偏好。除了偏爱模式之外，我们讨论性别/国籍多样性与研究团队的科学成就之间的关系。与之前的研究一致，我们的研究结果表明，研究小组录取研究生时不存在性别偏见，但我们观察到基于学生国籍的偏见。