Open Access
Contrasting Computational Models of Mate Preference Integration Across 45 Countries
Daniel Conroy-Beam
1
,
David M. Buss
2
,
Kelly Asao
2
,
Agnieszka Sorokowska
3, 4
,
Piotr Sorokowski
3
,
Toivo Aavik
5
,
Grace Akello
6
,
Mohammad Madallh Alhabahba
7
,
Charlotte Alm
8
,
Naumana Amjad
9
,
Afifa Anjum
9
,
Chiemezie S. Atama
10
,
Derya Atamtürk Duyar
11
,
Richard Ayebare
12
,
Carlota Batres
13
,
Mons Bendixen
14
,
Aicha Bensafia
15
,
Boris Bizumic
16
,
Mahmoud Boussena
17
,
Marina Butovskaya
18, 19
,
Seda Can
20
,
Katarzyna Cantarero
21
,
Antonin Carrier
22
,
Hakan Cetinkaya
23
,
Ilona Croy
24
,
Rosa María Cueto
25
,
Marcin Czub
3
,
Daria Dronova
18
,
Seda Dural
20
,
Izzet Duyar
11
,
Berna Ertugrul
26
,
Agustín Espinosa
25
,
Ignacio Estevan
27
,
Carla Sofia Esteves
28
,
Luxi Fang
29
,
Tomasz Frackowiak
3
,
Jorge Contreras Garduño
30
,
Karina Ugalde González
31
,
Farida Guemaz
32
,
Petra Gyuris
33
,
Mária Halamová
34
,
Iskra Herak
35
,
Marina Horvat
36
,
Ivana Hromatko
37
,
Chin Wai Hui
29
,
Jas Laile Jaafar
38
,
Feng Jiang
39
,
Konstantinos Kafetsios
40
,
Tina Kavčič
41
,
Leif Edward Ottesen Kennair
14
,
Nicolas Kervyn
35
,
Truong Thi Khanh Ha
42
,
Imran Ahmed Khilji
43
,
Nils C. Köbis
44
,
Hoang Moc Lan
42
,
András Láng
33
,
Georgina R. Lennard
16
,
Ernesto León
25
,
Torun Lindholm
8
,
Trinh Thi Linh
42
,
Giulia Lopez
45
,
Nguyen Van Luot
42
,
Alvaro Mailhos
27
,
Zoi Manesi
46
,
Rocio Martinez
47
,
Sarah L. McKerchar
16
,
Norbert Meskó
33
,
Girishwar Misra
48
,
Conal Monaghan
16
,
Emanuel C. Mora
49
,
Alba Moya-Garófano
47
,
Bojan Musil
50
,
Jean C. Natividade
51
,
Agnieszka Niemczyk
3
,
George Nizharadze
52
,
Elisabeth Oberzaucher
53
,
A. Oleszkiewicz
3, 4
,
Mohd Sofian Omar-Fauzee
54
,
Ike E. Onyishi
55
,
Baris Özener
11
,
Ariela F Pagani
45
,
Vilmante Pakalniskiene
56
,
Miriam Parise
45
,
Farid Pazhoohi
57
,
Annette Pisanski
49
,
Katarzyna Pisanski
3, 58
,
Edna Lúcia Tinoco Ponciano
59
,
Camelia Popa
60
,
Pavol Prokop
61, 62
,
Muhammad Rizwan
63
,
Mario Sainz
64
,
Svjetlana Salkičević
37
,
Ruta Sargautyte
56
,
Ivan Sarmány-Schuller
65
,
Susanne Schmehl
53
,
Shivantika Sharad
66
,
Razi Sultan Siddiqui
67
,
Franco Simonetti
68
,
Stanislava Stoyanova
69
,
Meri Tadinac
37
,
Marco Antonio Correa Varella
70
,
Christin-Melanie Vauclair
28
,
Luis Diego Vega
31
,
Dwi Ajeng Widarini
71
,
Gyesook Yoo
72
,
Marta Zaťková
34
,
Maja Zupančič
73
12
North Star Alliance, Kampala, Uganda
|
13
Department of Psychology, Franklin and Marshall College, Lancaster, United States of America
|
14
17
31
Psychology Department, Universidad Latina de Costa Rica, San José, Costa Rica
|
32
38
42
43
Department of Psychology, IMCB, F-10/4, Islamabad, Pakistan
|
51
52
Department of Social Sciences, Free Unviersity of Tbilisi, Tbilisi, Georgia
|
59
Institute of Psychology, University of the State of Rio de Janeiro, Rio de Janeiro, Brazil
|
60
Department of Psychology, Faculty for Humanities and Social Sciences, UNATC-CINETIc, Romanian Academy, Bucharest, Romania
|
63
The Delve Pvt Ltd, Islamabad, Pakistan
|
64
School of Psychology, University of Monterrey, San Pedro Garza Garcia, Mexico
|
71
Department of Communication, University Prof. Dr. Moestopo (Beragama), Jakarta, Indonesia
|
Publication type: Journal Article
Publication date: 2019-11-15
scimago Q1
wos Q1
SJR: 0.874
CiteScore: 6.7
Impact factor: 3.9
ISSN: 20452322
PubMed ID:
31729413
Multidisciplinary
Abstract
Humans express a wide array of ideal mate preferences. Around the world, people desire romantic partners who are intelligent, healthy, kind, physically attractive, wealthy, and more. In order for these ideal preferences to guide the choice of actual romantic partners, human mating psychology must possess a means to integrate information across these many preference dimensions into summaries of the overall mate value of their potential mates. Here we explore the computational design of this mate preference integration process using a large sample of n = 14,487 people from 45 countries around the world. We combine this large cross-cultural sample with agent-based models to compare eight hypothesized models of human mating markets. Across cultures, people higher in mate value appear to experience greater power of choice on the mating market in that they set higher ideal standards, better fulfill their preferences in choice, and pair with higher mate value partners. Furthermore, we find that this cross-culturally universal pattern of mate choice is most consistent with a Euclidean model of mate preference integration.
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Conroy-Beam D. et al. Contrasting Computational Models of Mate Preference Integration Across 45 Countries // Scientific Reports. 2019. Vol. 9. No. 1. 16885
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Conroy-Beam D. et al. Contrasting Computational Models of Mate Preference Integration Across 45 Countries // Scientific Reports. 2019. Vol. 9. No. 1. 16885
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@article{2019_Conroy-Beam,
author = {Daniel Conroy-Beam and David M. Buss and Kelly Asao and Agnieszka Sorokowska and Piotr Sorokowski and Toivo Aavik and Grace Akello and Mohammad Madallh Alhabahba and Charlotte Alm and Naumana Amjad and Afifa Anjum and Chiemezie S. Atama and Derya Atamtürk Duyar and Richard Ayebare and Carlota Batres and Mons Bendixen and Aicha Bensafia and Boris Bizumic and Mahmoud Boussena and Marina Butovskaya and Seda Can and Katarzyna Cantarero and Antonin Carrier and Hakan Cetinkaya and Ilona Croy and Rosa María Cueto and Marcin Czub and Daria Dronova and Seda Dural and Izzet Duyar and Berna Ertugrul and Agustín Espinosa and Ignacio Estevan and Carla Sofia Esteves and Luxi Fang and Tomasz Frackowiak and Jorge Contreras Garduño and Karina Ugalde González and Farida Guemaz and Petra Gyuris and Mária Halamová and Iskra Herak and Marina Horvat and Ivana Hromatko and Chin Wai Hui and Jas Laile Jaafar and Feng Jiang and Konstantinos Kafetsios and Tina Kavčič and Leif Edward Ottesen Kennair and others},
title = {Contrasting Computational Models of Mate Preference Integration Across 45 Countries},
journal = {Scientific Reports},
year = {2019},
volume = {9},
publisher = {Springer Nature},
month = {nov},
url = {https://doi.org/10.1038/s41598-019-52748-8},
number = {1},
pages = {16885},
doi = {10.1038/s41598-019-52748-8}
}