Book Chapter


Universal cognitive biases as the basis for supernatural beliefs : evidence and critiques

Abstract

What explains the ubiquity of religions across time and space, and why do these supernatural belief systems seem to have so much in common? Many cognitive scientists of religion have proposed that cross-cultural patterns in religious belief are, at least in part, the indirect result of reliably developing and otherwise adaptive features of the human mind. These ‘cognitive bias’ theories propose that religion is a by-product of universal mental architecture. Similar beliefs recur in unrelated cultural and historical contexts because of biases in how we perceive and interpret the word, and how we remember concepts. This chapter reviews the evidence, merits, and limitations of such theories. In so doing, the chapter addresses the most influential of the cognitive bias theories: the proposed relationships between various religious beliefs and Theory of Mind, anthropomorphism, dualism, teleological reasoning, and minimally counterintuitive concepts. Both the strengths and shortcomings of these theories in explaining religious belief are addressed and the chapter suggests future directions.



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Authors

Willard, Aiyana K.
Turpin, Hugh
Baimel, Adam

Oxford Brookes departments

Department of Psychology, Health and Professional Development

Dates

Year of publication: 2023
Date of RADAR deposit: 2023-06-02



All rights reserved. "This material was originally published in The Oxford Handbook of Cultural Evolution / edited by Jamshid J. Tehrani, Jeremy Kendal, and Rachel Kendal, and has been reproduced by permission of Oxford University Press at https://doi.org/10.1093/oxfordhb/9780198869252.001.0001. For permission to reuse this material, please visit http://global.oup.com/academic/rights."


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This RADAR resource is Identical to Universal Cognitive Biases as the Basis for Supernatural Beliefs: Evidence and Critiques
This RADAR resource is Part of The Oxford Handbook of Cultural Evolution [ISBN: 9780198869252] / edited by Jamshid J. Tehrani, Jeremy Kendal, Rachel Kendal (Oxford University Press, 2023).

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