Facial misfits accelerate stereotype-based associative learning.
Facial typicality
Learning
Person perception
Prediction errors
Stereotyping
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
20 08 2024
20 08 2024
Historique:
received:
12
04
2024
accepted:
15
07
2024
medline:
21
8
2024
pubmed:
21
8
2024
entrez:
20
8
2024
Statut:
epublish
Résumé
Counterstereotypes challenge the deleterious effects that gender-typed beliefs exert on people's occupational aspirations and lifestyle choices. Surprisingly, however, the critical issue of how readily unexpected person-related knowledge can be acquired remains poorly understood. Accordingly, in two experiments in which the facial appearance of targets was varied to manipulate goodness-of-stereotype-fit (i.e., high vs. low femininity/masculinity), here we used a probabilistic selection task to probe the rate at which counter-stereotypic and stereotypic individuals can be learned. Whether occupational (Expt. 1) or trait-related (Expt. 2) gender stereotypes were explored, a computational analysis yielded consistent results. Underscoring the potency of surprising information (i.e., facial misfits), knowledge acquisition was accelerated for unexpected compared to expected persons, both in counter-stereotypic and stereotypic learning contexts. These findings affirm predictive accounts of social perception and speak to the optimal characteristics of interventions designed to reduce stereotyping outside the laboratory.
Identifiants
pubmed: 39164271
doi: 10.1038/s41598-024-67770-8
pii: 10.1038/s41598-024-67770-8
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
19320Informations de copyright
© 2024. The Author(s).
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