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Differences in how people judge face attractiveness can be reliably measured
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Individual face preferences are primarily explained by differences in environments
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In contrast, face identity recognition is explained primarily by genetic variation
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Different domains of social judgment/face perception have distinct etiologies
[cf. SSC, 2007, et al 2017/ et al 2020, et al 2020, et al 2022, et al 2000; 2006/ et al 2007/2016; OKCupid on variance] Although certain characteristics of human faces are broadly considered more attractive (eg. symmetry, averageness), people also routinely disagree with each other on the relative attractiveness of faces. That is, to some important degree, beauty is in the “eye of the beholder.”
Here, we investigate the origins of these individual differences in face preferences using a twin design, allowing us to estimate the relative contributions of genetic and environmental variation to individual face attractiveness judgments or face preferences.
We first show that individual face preferences (IP) can be reliably measured and are readily dissociable from other types of attractiveness judgments (eg. judgments of scenes, objects). Next, we show that individual face preferences result primarily from environments that are unique to each individual. This is in striking contrast to individual differences in face identity recognition, which result primarily from variations in genes1.
We thus complete an etiological double dissociation between 2 core domains of social perception (judgments of identity versus attractiveness) within the same visual stimulus (the face). At the same time, we provide an example, rare in behavioral genetics, of a reliably and objectively measured behavioral characteristic where variations are shaped mostly by the environment.
The large impact of experience on individual face preferences provides a novel window into the evolution and architecture of the social brain, while lending new empirical support to the long-standing claim that environments shape individual notions of what is attractive.
…Next, we estimated the contributions of genetic and environmental factors to face IP by comparing the correlation of face IP scores among MZ twins with the correlation of face IP scores among DZ twins. Although MZ and DZ twins share family environment to a similar extent, MZ twins share, on average, twice as much of their genetic variation as DZ twins. The correlations for face IP scores between MZ twins and between DZ twins can thus be used to estimate the proportion of variation in face IP that can be explained by variations in genes, shared environments, and unshared environments.
We calculated a maximum likelihood correlation of 0.22 (95% CI: 0.14–0.29) for MZ twins and 0.09 (95% CI: −0.06–0.24) for DZ twins. These 2 correlations did not statistically-significantly differ (Fisher r-to-z transformation; p = 0.1), indicating that most of the variance in face IP is likely attributable to environmental factors.
To obtain a more precise estimate of the contributions of genetic and environmental factors to face IP, we fit a standard ACE twin model that includes additive genetic influences (A), shared environmental influences (C), as well as unshared environmental influences and measurement-error (E) using structural equation modeling techniques…The AE model gave similar point estimates for both A (22%) and E (78%) parameters, but with tighter confidence intervals (see Figure 2C and Table 1).
We conclude that most of the reliable variation in face IP was explained by the influence of unshared or individual environment with a relatively small contribution from genetic variation and little to no contribution from shared environment.
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