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Physiognomy: Difference between revisions
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* A twin study in 2017 found a weak but significant relationship between [[IPD]], namely wider eyes, and actual measured [[IQ]].<ref>https://www.sciencedirect.com/science/article/abs/pii/S0160289617300843</ref> An earlier study found that people were able to accurately gauge measured IQ from a photograph, but this only held true in the case of men's IQ, and not women's.<ref>https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0081237</ref> | * A twin study in 2017 found a weak but significant relationship between [[IPD]], namely wider eyes, and actual measured [[IQ]].<ref>https://www.sciencedirect.com/science/article/abs/pii/S0160289617300843</ref> An earlier study found that people were able to accurately gauge measured IQ from a photograph, but this only held true in the case of men's IQ, and not women's.<ref>https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0081237</ref> | ||
* Studies conducted in 2013 found that people were able to accurately predict the outcomes of fights based on facial features, above chance. The fighters with faces rated as more aggressive were more likely to win their bouts, but they was also confounded by weight, thus it only held true for heavyweight fighters. The facial features associated with aggressiveness were an overall broader face, broader chin, darker eyebrows and [[hunter eyes|horizontally narrowed eyes]].<ref>https://journals.sagepub.com/doi/abs/10.1177/0956797613477117</ref> | * Studies conducted in 2013 found that people were able to accurately predict the outcomes of fights based on facial features, above chance. The fighters with faces rated as more aggressive were more likely to win their bouts, but they was also confounded by weight, thus it only held true for heavyweight fighters. The facial features associated with aggressiveness were an overall broader face, broader chin, darker eyebrows and [[hunter eyes|horizontally narrowed eyes]].<ref>https://journals.sagepub.com/doi/abs/10.1177/0956797613477117</ref> | ||
* Wang & Kosinski (2017) used a deep neural network that, analyzing 35,326 'selfie' images, 81% of cases, and in 74% of cases for women.<ref>https://osf.io/zn79k/</ref> This was compared to human judges, who could distinguish a man's homosexuality in 61% of cases and women's in 54% of cases (slightly above chance). This study has been heavily criticized, however, for being confounded by differences in facial expression, grooming, clothing, camera angle and other contextual factors unrelated to facial structure. | |||
==See Also== | ==See Also== | ||