Department of Psychological and Brain Sciences, Indiana University, Bloomington, Indiana, United States of America.
Department of Psychology, University of California, Davis, Davis, California, United States of America.
PLoS One. 2024 Jul 24;19(7):e0306872. doi: 10.1371/journal.pone.0306872. eCollection 2024.
We used a reverse-correlation image-classification paradigm to visualize facial representations of immigrants and citizens in the United States. Visualizations of immigrants' faces were judged by independent raters as less trustworthy and less competent and were more likely to be categorized as a non-White race/ethnicity than were visualizations of citizens' faces. Additionally, image generators' personal characteristics (e.g., implicit and explicit evaluations of immigrants, nativity status) did not reliably track with independent judges' ratings of image generators' representations of immigrants. These findings suggest that anti-immigrant sentiment and racial/ethnic assumptions characterize facial representations of immigrants in the United States, even among people who harbor positivity toward immigrants.
我们使用反向相关图像分类范式来可视化美国移民和公民的面部特征。独立评审员认为，移民的面部图像看起来不太值得信赖，能力也较低，并且更有可能被归类为非白种人/族裔，而公民的面部图像则不然。此外，图像生成器的个人特征（例如，对移民的内隐和外显评价、出生地身份）并不能可靠地反映独立评审员对图像生成器对移民的代表性评价。这些发现表明，即使是那些对移民持有积极态度的人，也会对美国移民的面部特征产生反移民情绪和种族/族裔假设。
