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A mathematical analysis of the evolution of human mate choice traits

Implications for evolutionary psychologists

Bibliographic Data

ID12938871
AuthorsNed Kock (0000-0002-5791-5434, Texas A&M International University, corresponding author)
Year2011
Volume9
Issue3
Pages219-247
Publication date2011-05-04
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueJournal of Evolutionary Psychology (JOURNAL)
Journal identifiersISSN: 1789-2082 • E-ISSN: 2060-5587
PublisherAkadémiai Kiadó (PUBLISHER • HU)
DOI10.1556/jep.9.2011.3.1
OpenAlexW2156496017
LanguageEN
Citations received3
References cited59

Sexually reproducing organisms often rely on various traits to judge the attractiveness of potential mates. Many mate choice preferences and traits have evolved through selection by those organisms' ancestors, with traits having been either costly (detrimental to survival) or noncostly in the environment of their evolutionary adaptation. A general mathematical analysis of the evolution of traits used in mate choice is presented. The analysis builds on a combination of Price's covariance equation and Wright's method of path analysis, and includes a set of Monte Carlo simulations. The usefulness of the mathematical analysis is demonstrated through the development of a small but important set of hypotheses and implications for the human species: (1) costly traits used in mate choice by humans should be generally less common and more attractive to the other sex than non-costly traits; (2) costly traits should be disproportionately less common in human females than in males; and (3) some harmful human mental disorders, such as schizophrenia, may have co-evolved as costs of attractive mental traits. It is also shown that similar analyses can be easily employed by evolutionary psychologists to theorize about the evolution of complex mate choice traits, and to test the resulting theories with modern humans through the method of path analysis

Adaptation (eye · Biology · Evolutionary biology · Evolutionary psychology · Machine learning · Mate choice · Mating · Path analysis (statistics · Set (abstract data type · Computer Science · Evolutionary Game Theory and Cooperation · Evolutionary Psychology and Human Behavior · Plant and animal studies · Psychology · Ecology

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Unique citing works3
Citations per year0,27
Citation span2015 - 2025 (11)
Citation velocityrecent
Highly citedNo
Citation typesNeutral: 3
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