The aim of the present study was to further understanding of how social categorization influences face recognition. According to the categorization-individuation model, face recognition can either be biased toward categorization or individuation. We hypothesized that the face recognition bias associated with a social category (e.g., the own-age bias) would be larger when faces were initially categorized according to that category. To examine this hypothesis, young adults (N = 63) completed a face recognition task after either making age or sex judgments while encoding child and adult faces. Young adults showed the own-age and own-sex biases in face recognition. Consistent with our hypothesis, the magnitude of the own-age bias in face recognition was larger when individuals made age, rather than sex, judgments at encoding. To probe the mechanisms underlying this effect, we examined ERP responses to child and adult faces across the social categorization conditions. Neither the P1 nor the N170 ERP components were modulated by the social categorization task or the social category membership of the face. However, the P2, which is associated with second-order configural processing, was larger to adult faces than child faces only in the age categorization condition. The N250, which is associated with individuation, was larger (i.e., more negative) to adult than child faces and during age categorization than sex categorization. These results are interpreted within the context of the categorization-individuation model and current research on biases in face recognition.

本研究的目的是进一步了解社会分类如何影响面部识别。根据分类-个体化模型，面部识别可以偏向于分类或个体化。我们假设，当最初根据该类别对面部进行分类时，与社会类别相关联的面部识别偏差（例如，自己的年龄偏差）会更大。为了检验这一假设，年轻人（N = 63）在对孩子和成人的脸部进行编码时，对年龄或性别做出判断后，完成了脸部识别任务。年轻人在面部识别中表现出年龄和性别歧视。与我们的假设一致，当个人在编码时以年龄而不是性别来判断时，面部识别中年龄的偏见会更大。为了探究这种影响的潜在机制，我们研究了ERP在各种社会分类条件下对儿童和成人面孔的反应。P1和N170 ERP组件均未通过社交分类任务或面部社交类别成员身份进行调节。然而，仅在年龄分类条件下，与二阶配置处理相关联的P2对于成人脸比孩子脸大。N250与个性化相关，对成人而言，比儿童面孔更大（即更负面），在年龄分类中比性别分类更大。这些结果是在分类-个体化模型和当前关于面部识别偏差的研究的背景下进行解释的。