Oswald Frederick L, Mitchell Gregory, Blanton Hart, Jaccard James, Tetlock Philip E
Department of Psychology.
School of Law, University of Virginia.
J Pers Soc Psychol. 2015 Apr;108(4):562-71. doi: 10.1037/pspa0000023.
Greenwald, Banaji, and Nosek (2015) present a reanalysis of the meta-analysis by Oswald, Mitchell, Blanton, Jaccard, and Tetlock (2013) that examined the effect sizes of Implicit Association Tests (IATs) designed to predict racial and ethnic discrimination. We discuss points of agreement and disagreement with respect to methods used to synthesize the IAT studies, and we correct an error by Greenwald et al. that obscures a key contribution of our meta-analysis. In the end, all of the meta-analyses converge on the conclusion that, across diverse methods of coding and analyzing the data, IAT scores are not good predictors of ethnic or racial discrimination, and explain, at most, small fractions of the variance in discriminatory behavior in controlled laboratory settings. The thought experiments presented by Greenwald et al. go well beyond the lab to claim systematic IAT effects in noisy real-world settings, but these hypothetical exercises depend crucially on untested and, arguably, untenable assumptions.
格林沃尔德、巴纳吉和诺塞克（2015年）对奥斯瓦尔德、米切尔、布兰顿、雅卡德和泰特洛克（2013年）的荟萃分析进行了重新分析，该荟萃分析考察了旨在预测种族和民族歧视的内隐联想测验（IAT）的效应量。我们讨论了在综合IAT研究时所用方法上的异同点，并且纠正了格林沃尔德等人的一个错误，该错误掩盖了我们荟萃分析的一项关键贡献。最后，所有的荟萃分析都得出这样的结论：在各种不同的数据编码和分析方法中，IAT分数并非种族或民族歧视的良好预测指标，并且在受控实验室环境中，至多只能解释歧视行为中很小一部分的方差。格林沃尔德等人所提出的思想实验远远超出了实验室范畴，声称在嘈杂的现实世界环境中存在系统性的IAT效应，但这些假设性的做法在很大程度上依赖于未经检验且可能站不住脚的假设。
