Little is known about implicit evaluations of complex, multiply categorizable social targets. Across five studies (N = 5,204), we investigated implicit evaluations of targets varying in race, gender, social class, and age. Overall, the largest and most consistent evaluative bias was pro-women/anti-men bias, followed by smaller but nonetheless consistent pro-upper-class/anti-lower-class biases. By contrast, we observed less consistent effects of targets' race, no effects of targets' age, and no consistent interactions between target-level categories. An integrative data analysis highlighted a number of moderating factors, but a stable pro-women/anti-men and pro-upper-class/anti-lower-class bias across demographic groups. Overall, these results suggest that implicit biases compound across multiple categories asymmetrically, with a dominant category (here, gender) largely driving evaluations, and ancillary categories (here, social class and race) exerting relatively smaller additional effects. We discuss potential implications of this work for understanding how implicit biases operate in real-world social settings. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

中文翻译：

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交叉隐性偏见：不对称复合偏见和目标性别优势的证据。

对复杂的、可多重分类的社会目标的内隐评估知之甚少。在五项研究 (N = 5,204) 中，我们调查了对因种族、性别、社会阶层和年龄而异的目标的内隐评估。总体而言，最大和最一致的评估偏见是支持女性/反对男性的偏见，其次是较小但仍然一致的支持上层阶级/反对下层阶级的偏见。相比之下，我们观察到目标种族的影响不太一致，目标年龄没有影响，目标级别类别之间没有一致的交互作用。综合数据分析强调了一些调节因素，但在人口群体中存在稳定的支持女性/反男性和支持上层阶级/反下层阶级的偏见。总的来说，这些结果表明隐性偏见不对称地跨多个类别复合，主导类别（此处为性别）主要推动评估，辅助类别（此处为社会阶层和种族）产生相对较小的附加影响。我们讨论了这项工作对理解隐性偏见如何在现实社会环境中运作的潜在影响。（PsycInfo 数据库记录 (c) 2022 APA，保留所有权利）。