Sacco Joshua M, Scheu Christine R, Ryan Ann Marie, Schmitt Neal
Aon Consulting, Southfield, MI 90017, USA.
J Appl Psychol. 2003 Oct;88(5):852-65. doi: 10.1037/0021-9010.88.5.852.
This research studied the effects of race and sex similarity on ratings in one-on-one highly structured college recruiting interviews (N = 708 interviewers and 12203 applicants for 7 different job families). A series of hierarchical linear models provided no evidence for similarity effects, although the commonly used D-score and analysis-of-variance-based interaction approaches conducted at the individual level of analysis yielded different results. The disparate results demonstrate the importance of attending to nested data structures and levels of analysis issues more broadly. Practically, the results suggest that organizations using carefully administered highly structured interviews may not need to be concerned about bias due to the mismatch between interviewer and applicant race or sex.
本研究考察了种族和性别相似性对一对一高度结构化的大学招聘面试评分的影响(涉及7个不同工作类别,共708名面试官和12203名申请者)。一系列分层线性模型未发现相似性效应的证据,尽管在个体分析层面常用的D分数法和基于方差分析的交互作用方法得出了不同结果。这些不同的结果更广泛地证明了关注嵌套数据结构和分析层面问题的重要性。实际上,研究结果表明,采用精心管理的高度结构化面试的组织可能无需担心面试官与申请者在种族或性别上不匹配所导致的偏见。