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Face Typicality–Distinctiveness Norms for the 304 Front-View Faces of the Glasgow Unfamiliar Face Database

Author

Listed:
  • Paulo Ventura

    (Faculdade de Psicologia, Universidade de Lisboa, Alameda da Universidade, 1649-013 Lisboa, Portugal)

  • Francisco Cruz

    (Faculdade de Psicologia, Universidade de Lisboa, Alameda da Universidade, 1649-013 Lisboa, Portugal)

  • Susana Araújo

    (Faculdade de Psicologia, Universidade de Lisboa, Alameda da Universidade, 1649-013 Lisboa, Portugal)

Abstract

Face typicality and distinctiveness are key facial attributes that influence face recognition performance and the formation of social impressions. The present study aimed to provide normative data for these dimensions, offering a useful resource for face recognition research. Using a 7-point Likert scale, adult participants rated 304 front-facing faces from the Glasgow Unfamiliar Face Database (GUFD) for typicality–distinctiveness. Results indicated that the subjective rating method produced reliable estimates, with meaningful variability observed along the typicality–distinctiveness continuum. Highly distinctive faces were more sparsely represented in the database. These norms can support principled stimulus selection and improved methodological control in empirical research with faces.

Suggested Citation

  • Paulo Ventura & Francisco Cruz & Susana Araújo, 2026. "Face Typicality–Distinctiveness Norms for the 304 Front-View Faces of the Glasgow Unfamiliar Face Database," Data, MDPI, vol. 11(2), pages 1-14, January.
    • Handle: RePEc:gam:jdataj:v:11:y:2026:i:2:p:24-:d:1848584
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