Albohn Daniel N, Martinez Joel E, Todorov Alexander
Booth School of Business, University of Chicago.
Department of Psychology, Harvard University.
J Exp Psychol Hum Percept Perform. 2024 Nov;50(11):1117-1130. doi: 10.1037/xhp0001239. Epub 2024 Sep 19.
Recent work has shown that the idiosyncrasies of the observer can contribute more to the variance of social judgments of faces than the features of the faces. However, it is unclear what conditions determine the relative contributions of shared and idiosyncratic variance. Here, we examine two conditions: type of judgment and diversity of face stimuli. First, we show that for simpler, directly observable judgments that are consistent across observers (e.g., masculinity) shared exceeds idiosyncratic variance, whereas for more complex and less directly observable judgments (e.g., trustworthiness), idiosyncratic exceeds shared variance. Second, we show that judgments of more diverse face images increase the amount of shared variance. Finally, using machine-learning methods, we examine how stimulus (e.g., incidental emotion resemblance, skin luminosity) and observer variables (e.g., race, age) contribute to shared and idiosyncratic variance of judgments. Overall, our results indicate that an observer's age is the most consistent and best predictor of idiosyncratic variance contributions to face judgments measured in the current research. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
最近的研究表明，观察者的特质对面部社会判断差异的影响，可能比面部特征更大。然而，目前尚不清楚哪些条件决定了共享差异和特质差异的相对贡献。在此，我们研究了两个条件：判断类型和面部刺激的多样性。首先，我们发现，对于更简单、观察者之间一致的直接可观察判断（例如男性气质），共享差异超过特质差异；而对于更复杂、不太直接可观察的判断（例如可信度），特质差异超过共享差异。其次，我们发现对更多样化面部图像的判断会增加共享差异的量。最后，我们使用机器学习方法，研究刺激因素（例如附带的情绪相似性、皮肤亮度）和观察者变量（例如种族、年龄）如何影响判断的共享差异和特质差异。总体而言，我们的结果表明，在本研究中测量的面部判断中，观察者的年龄是特质差异贡献最一致且最佳的预测指标。（PsycInfo数据库记录（c）2024美国心理学会，保留所有权利）
