Human preferences for sexually dimorphic faces may be evolutionarily novel

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Publikace nespadá pod Ústav výpočetní techniky, ale pod Filozofickou fakultu. Oficiální stránka publikace je na webu muni.cz.
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SCOTT Isabel M. CLARK Andrew P. JOSEPHSON Steven C. BOYETTE Adam H. CUTHILL Innes C. FRIED Ruby L. GIBSON Mhairi A. HEWLETT Barry S. JAMIESON Mark JANKOWIAK William LIEBERT Melissa A. PURZYCKI Benjamin G. SHAVER John Hayward SNODGRASS J. Josh SOSIS Richard SUGIYAMA Lawrence S. SWAMI Viren YU Douglas W. ZHAO Yangke PENTON-VOAK Ian S. HONEY P. L. HUANG Z.

Rok publikování 2014
Druh Článek v odborném periodiku
Časopis / Zdroj Proceedings of the National Academy of Sciences of the United States of America
Fakulta / Pracoviště MU

Filozofická fakulta

Citace
Doi http://dx.doi.org/10.1073/pnas.1409643111
Obor Filosofie a náboženství
Klíčová slova aggression; cross-cultural; evolution; facial attractiveness; stereotyping
Popis A large literature proposes that preferences for exaggerated sex typicality in human faces (masculinity/femininity) reflect a long evolutionary history of sexual and social selection. This proposal implies that dimorphism was important to judgments of attractiveness and personality in ancestral environments. It is difficult to evaluate, however, because most available data come from large-scale, industrialized, urban populations. Here, we report the results for 12 populations with very diverse levels of economic development. Surprisingly, preferences for exaggerated sex-specific traits are only found in the novel, highly developed environments. Similarly, perceptions that masculine males look aggressive increase strongly with development and, specifically, urbanization. These data challenge the hypothesis that facial dimorphism was an important ancestral signal of heritable mate value. One possibility is that highly developed environments provide novel opportunities to discern relationships between facial traits and behavior by exposing individuals to large numbers of unfamiliar faces, revealing patterns too subtle to detect with smaller samples.
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