Euclidean distances discriminatively predict short-term and long-term attraction to potential mates
نویسندگان
چکیده
Article history: Initial receipt 24 August 2016 Final revision received 13 April 2017 We tested the ability of a Euclidean algorithm to predict attraction to potential mates—a relatively upstream domain in the temporal sequence of the mating process. Participants in two studies reported their ideal mate preferences using a 23-item preference instrument. Separately, they rated their attraction to profiles of potential mates that varied on those 23 dimensions. Study 1 (N=522) found that Euclidean distances predicted attraction to potential mates both in terms of (1) overall mate value and (2) unique mate value. Study 2 (N = 411) replicated these effects and further found that Euclidean mate values discriminatively predict between shortand long-term attraction. Across both studies, a Euclidean model outperformed a variety of alternative models for predicting attraction to potential mates. These results suggest that a Euclidean algorithm is a good model for how multiple preferences are integrated in mate choice. © 2017 Elsevier Inc. All rights reserved.
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