Scholars debate the extent to which implicit bias is a stable individual attitude versus a feature of social contexts. The primary evidence for the social context view is that group averages are more stable, and more strongly associated with disparate outcomes, than individual scores. Group averages, however, depend on aggregating many observations, raising the question of whether their apparently superior reliability and validity may be a statistical artefact of aggregation. Would individual difference correlations be as large as context-based correlations if we only aggregated more measures per person? We report two studies testing the effects of aggregating repeated implicit tests. We find that aggregating up to six tests increases test-retest reliability somewhat, but increases validity correlations only slightly, and has no benefit after three tests. Results suggest that large correlations at the level of contexts cannot be reduced to the statistical effects of aggregating multiple tests.

学者们争论隐性偏见在多大程度上是一种稳定的个人态度与社会背景的特征。社会背景观点的主要证据是，与个人分数相比，群体平均数更稳定，并且与不同结果的相关性更强。然而，组平均值取决于汇总许多观察结果，提出了一个问题，即它们明显优越的可靠性和有效性是否可能是汇总的统计假象。如果我们只汇总每个人的更多测量值，个体差异相关性会与基于上下文的相关性一样大吗？我们报告了两项测试聚合重复内隐测试效果的研究。我们发现聚合多达六个测试在一定程度上增加了重测信度，但仅略微增加了效度相关性，并且经过三个测试没有任何好处。结果表明，上下文级别的大相关性不能简化为聚合多个测试的统计效果。