The accurate and swift decoding of emotional expressions from faces is fundamental for social communication. Yet, emotion perception is prone to error. For example, the ease with which emotions are perceived is affected by stereotypes (Bijlstra, Holland, & Wigboldus, 2010). Moreover, the introduction of face masks mandates in response to the Covid-19 pandemic additionally impedes accurate emotion perception by introducing ambiguity to the emotion perception process. Predictive coding frameworks of visual perception predict that in such situations of increased ambiguity of the sensory input (i.e., faces with masks), people increasingly rely on their prior beliefs (i.e., their stereotypes). Using specification curve analysis, we tested this prediction across two experiments, featuring different social categories (Study 1: Gender; Study 2: Ethnicity) and corresponding emotion stereotypes. We found no evidence that face masks increase reliance on prior stereotypes. In contrast, in Study 1 (but not in Study 2), we found preliminary evidence that face masks decrease reliance on prior stereotypes. We discuss these findings in relation to predictive coding frameworks and dual process models and emphasize the need for up-to-date analytic methods in social cognition research.

准确快速地解码面部表情是社交交流的基础。然而，情绪感知容易出错。例如，情绪被感知的难易程度受刻板印象的影响（Bijlstra, Holland, & Wigboldus, 2010）。此外，为应对 Covid-19 大流行而引入的口罩命令还通过在情绪感知过程中引入歧义来阻碍准确的情绪感知。视觉感知的预测编码框架预测，在这种感觉输入的模糊性增加的情况下（即，戴着面具的面孔），人们越来越依赖于他们先前的信念（即，他们的刻板印象）。使用规格曲线分析，我们在两个具有不同社会类别的实验中测试了这一预测（研究 1：性别；研究 2：种族）和相应的情感刻板印象。我们没有发现任何证据表明口罩会增加对先前刻板印象的依赖。相比之下，在研究 1（但不是在研究 2）中，我们发现初步证据表明口罩减少了对先前刻板印象的依赖。我们讨论了与预测编码框架和双重过程模型相关的这些发现，并强调在社会认知研究中需要最新的分析方法。