ArticleScientific reports2022
Male recognition bias in sex assignment based on visual stimuli.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed, 1 citations in OpenAlex.
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Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
According to previous ethnomethodological and cognitive studies on sex assignment, if a figure has male sexual characteristics people are more likely to think it is a man than they think it is a woman when the figure has female sexual characteristics. This bias in favor of male attribution is strongly reinforced when a penis is apparent in human nude pictures. In our contribution, we reported findings of three experiments aimed at replicating previous studies by administering the Sex/Gender Attribution Test for Adult (SGAT-A) created by digitally morphing the bodies of one human male and one human female model into realistic pictures. We observed the sex attribution and response time of 1706 young adult participants. A cross-cultural comparison was also carried out with a sample of young adult Chinese students. Findings substantially reconfirmed those obtained in previous studies. The male external genitalia overshadow any other features that might rather suggest a female identity. Indeed, when male external genitalia were exposed, the odds of male sex attribution were 5.688 compared to 1.823 female attribution when female external genitalia were shown. Moreover, the shortest response times were observed with masculine stimuli. Evolutionary and cultural determinants of the male sex bias are also discussed.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.