City Research Online

Abstract

An influential argument is that mental processes can be explained at three different levels of analysis: the functional, algorithmic, and implementation level. Identity attribution (the process whereby an identity is attributed to another individual or to the self) has been rarely explored at the functional level. To address this, here I propose a theory of identity attribution grounded on Bayesian inference, being the latter a well-established functional perspective in cognitive science. The theory posits that an identity is inferred based on observations about a target’s features, about the context, and about motivational factors. This inference can be made based upon multiple sources of observations, with prior beliefs becoming more prominent when observations are fewer in number. The theory offers an interpretation of key processes driving identity attribution, potentially providing a platform for integrating different perspectives on identity in psychology and sociology.

Publication Type:	Article
Additional Information:	© 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.
Publisher Keywords:	Identity; identity attribution; Bayesian; context; computational; inference
Subjects:	B Philosophy. Psychology. Religion > BF Psychology Q Science > QA Mathematics R Medicine > RC Internal medicine > RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry
Departments:	School of Health & Psychological Sciences > Psychology
SWORD Depositor:	Symplectic Administrator

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