JOURNAL ARTICLE

How to Tell a Dualist?

  • Published In: Cognitive Science, 2023, v. 47, n. 11. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Berent, Iris 3 of 3

Abstract

People exhibit conflicting intuitions concerning the mind/body links. Here, I explore a novel explanation for these inconsistencies: Dualism is a violable constraint that interacts with Essentialism. Two experiments probe these interactions. In Experiment 1, participants evaluated the emergence of psychological traits in either a replica of one's body, or in the afterlife—after the body's demise. In line with Dualism, epistemic (i.e., disembodied) traits (e.g., knowing the contrast between good/bad) were considered more likely to emerge (relative to sensorimotor/affective traits) only in the afterlife. However, so were innate traits (in line with Essentialism). To further gauge Essentialism, Experiment 2 presented the same traits to innateness judgments. Here, sensorimotor/affective (i.e., embodied) traits were considered more likely to be innate, suggesting that innateness intuitions are informed by embodiment. Moreover, innateness judgments (in Experiment 2) and embodiment intuitions (in Experiment 1) correlated. These results suggest that Dualism tacitly constrains reasoning about one's innate origins and its persistence after death. But since Dualism is "soft" and interacts with Essentialism, supernatural intuitions are chimeric, not purely ethereal. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Cognitive Science. 2023/11, Vol. 47, Issue 11, p1
  • Document Type:Article
  • Subject Area:Religion and Philosophy
  • Publication Date:2023
  • ISSN:0364-0213
  • DOI:10.1111/cogs.13380
  • Accession Number:173849741
  • Copyright Statement:Copyright of Cognitive Science is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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