Gender categorization and stereotyping can lead to discrimination. Researchers have mostly studied cisgender, gender-conforming individuals as the targets when examining these processes. In two factorial survey experiments, we investigated gender categorization and stereotyping of gender-ambiguous targets based on facial features and behavioral information. We manipulated femininity/masculinity/ambiguity of face, expression, and occupation. Participants completed a gender categorization task, and stereotype and attitude measures. The findings indicated that face was most influential for categorization: When face was unambiguously masculine or feminine, participants mostly categorized targets as male or female, respectively. In these cases, expression and occupation had little influence on categorization. When face was ambiguous, this additional information significantly influenced categorization. Nonbinary categorization was more likely for ambiguous faces, and most likely for ambiguous faces combined with ambiguous expression and ambiguous or feminine occupation. Our findings suggest that categorizing gender-ambiguous targets is more complex compared to clearly gendered targets. Primarily relying on face when it appears clearly gendered likely causes categorization errors when encountering TGNC individuals.

性别分类和陈规定型观念可能导致歧视。研究人员在检查这些过程时大多以顺性别、符合性别的个体为目标。在两项析因调查实验中，我们根据面部特征和行为信息研究了性别模糊目标的性别分类和刻板印象。我们操纵面部、表情和职业的女性气质/男性气质/模糊性。参与者完成了性别分类任务以及刻板印象和态度测量。研究结果表明，面孔对分类影响最大：当面孔明确是男性或女性时，参与者大多将目标分别分类为男性或女性。在这些情况下，表达和职业对分类影响不大。当面部模糊时，这些附加信息会显着影响分类。非二元分类更有可能适用于含糊不清的面孔，并且最有可能适用于含糊不清的面孔与含糊不清的表情和含糊或女性职业相结合的情况。我们的研究结果表明，与明确性别的目标相比，对性别模糊的目标进行分类更为复杂。在遇到 TGNC 个体时，主要依赖于明显具有性别特征的面孔可能会导致分类错误。