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Assessing the accuracy of perceptions of intelligence based on heritable facial features

Anthony J. Lee, Courtney Hibbs, Margaret J. Wright, Nicholas G. Martin, Matthew C. Keller and Brendan P. Zietsch

Intelligence, 2017, vol. 64, issue C, 1-8

Abstract: Perceptions of intelligence based on facial features can have a profound impact on many social situations, but findings have been mixed as to whether these judgements are accurate. Even if such perceptions were accurate, the underlying mechanism is unclear. Several possibilities have been proposed, including evolutionary explanations where certain morphological facial features are associated with fitness-related traits (including cognitive development), or that intelligence judgements are over-generalisation of cues of transitory states that can influence cognition (e.g., tiredness). Here, we attempt to identify the morphological signals that individuals use to make intelligence judgements from facial photographs. In a genetically informative sample of 1660 twins and their siblings, we measured IQ and also perceptions of intelligence based on facial photographs. We found that intelligence judgements were associated with both stable morphological facial traits (face height, interpupillary distance, and nose size) and more transitory facial cues (eyelid openness, and mouth curvature). There was a significant association between perceived intelligence and measured IQ, but of the specific facial attributes only interpupillary distance (i.e., wide-set eyes) significantly mediated this relationship. We also found evidence that perceived intelligence and measured IQ share a familial component, though we could not distinguish between genetic and shared environmental sources.

Keywords: Intelligence perception; IQ; Face perception; Behavioral genetics; Attractiveness; Shape analysis (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:intell:v:64:y:2017:i:c:p:1-8

DOI: 10.1016/j.intell.2017.06.002

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