Using the IAT to Predict Ethnic and Racial Discrimination: Small Effect Sizes of Unknown Societal Significance
Using the IAT to Predict Ethnic and Racial Discrimination: Small Effect Sizes of Unknown Societal Significance
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DOI：
10.1037/pspa0000023
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发表时间：
2015-04-01
影响因子：
7.6
通讯作者：
Tetlock, Philip E.
中科院分区：
文献类型：
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作者：
Oswald, Frederick L.;Mitchell, Gregory;Tetlock, Philip E.
Greenwald，Banaji和Nosek(2015)对Oswald，Mitchell，Blanton，Jaccard和Tetlock(2013)的元分析进行了重新分析，该分析考察了旨在预测种族和民族歧视的内隐联想测试(IATS)的效果大小。我们讨论了关于合成IAT研究的方法的一致和不同之处，并纠正了Greenwald等人的一个错误。这掩盖了我们的元分析的一个关键贡献。最后，所有的元分析都得出了这样的结论：在不同的编码和分析数据的方法中，IAT分数不是种族或种族歧视的良好预测因子，最多只能解释受控实验室环境中歧视行为的一小部分差异。格林沃尔德等人提出的思维实验。这远远超出了实验室的范畴，声称在嘈杂的现实世界环境中存在系统的IAT效应，但这些假设练习主要依赖于未经测试的、可以说是站不住脚的假设。
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.