Toward a Meaningful Metric of Implicit Prejudice
Toward a Meaningful Metric of Implicit Prejudice
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DOI：
10.1037/a0038379
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发表时间：
2015-09-01
影响因子：
9.9
通讯作者：
Tetlock, Philip E.
中科院分区：
文献类型：
--
作者：
Blanton, Hart;Jaccard, James;Tetlock, Philip E.
内隐联想测验（IAT）的模态分布通常被解释为美国人中存在高水平的内隐偏见。这些解释推动了对组织和法律的实践的变革，但这种应用是有问题的，因为IAT是根据一个任意的心理度量来评分的。本研究旨在通过确定与可观察到的种族或民族偏见相关的IAT措施分数，使IAT指标不那么随意。通过重新检查已发表的研究数据，我们发现IAT指标是“右偏”的证据，例如行为中立的个体往往具有积极的IAT分数。目前的评分惯例没有考虑到这些动态，并可能导致错误的推断隐含的偏见的流行。
The modal distribution of the Implicit Association Test (IAT) is commonly interpreted as showing high levels of implicit prejudice among Americans. These interpretations have fueled calls for changes in organizational and legal practices, but such applications are problematic because the IAT is scored on an arbitrary psychological metric. The present research was designed to make the IAT metric less arbitrary by determining the scores on IAT measures that are associated with observable racial or ethnic bias. By reexamining data from published studies, we found evidence that the IAT metric is "right biased," such that individuals who are behaviorally neutral tend to have positive IAT scores. Current scoring conventions fail to take into account these dynamics and can lead to faulty inferences about the prevalence of implicit prejudice.