Publication Type

Journal Article

Version

publishedVersion

Publication Date

10-2018

Abstract

Social thermoregulation theory posits that modern human relationships are pleisiomorphically organized around body temperature regulation. In two studies (N = 1755) designed to test the principles from this theory, we used supervised machine learning to identify social and non-social factors that relate to core body temperature. This data-driven analysis found that complex social integration (CSI), defined as the number of high-contact roles one engages in, is a critical predictor of core body temperature. We further used a cross-validation approach to show that colder climates relate to higher levels of CSI, which in turn relates to higher CBT (when climates get colder). These results suggest that despite modern affordances for regulating body temperature, people still rely on social warmth to buffer their bodies against the cold.

Keywords

Social Integration, Social Thermoregulation Theory, Attachment Theory, Embodiment, Machine Learning

Discipline

Organizational Behavior and Theory | Social Psychology and Interaction

Publication

Collabra: Psychology

Volume

4

Issue

1

First Page

1

Last Page

18

ISSN

2474-7394

Identifier

10.1525/collabra.165

Publisher

University of California Press

Copyright Owner and License

Authors CC-BY

Creative Commons License

Creative Commons Attribution 3.0 License
This work is licensed under a Creative Commons Attribution 3.0 License.

Comments

Full author list: IJzerman, H.; Lindenberg, S.; Dalgar, I.; Weissgerber, S.S.C.; Vergara, R.C.; Cairo, A.H.; Colic, M.V.; Dursun, P.; Frankowska, N.; Hadi, R.; Hall, C.J.; Hong, Y.; Hu, C.P.; Joy-Gaba, J.;, Lazarevic D, Lazarevic LB, Parzuchowski M, Ratner KG, Rothman D, Sim S, Simao C, Song M, Stojilovic D, Blomster JK, Brito R, Hennecke M, Jaume-Guazzini F, Schubert TW, Schutz A, Seibt B, Zickfeld JH

Additional URL

https://doi.org/10.1525/collabra.165

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