JOURNAL ARTICLE

Logical exceptionalism: Development and predicaments.

  • Published In: Theoria: A Swedish Journal of Philosophy, 2024, v. 90, n. 3. P. 295 1 of 3

  • Database: Humanities Source Ultimate 2 of 3

  • Authored By: Chen, Bo 3 of 3

Abstract

This paper examines the conceptions of logic from Leibniz, Hume, Kant, Frege, Wittgenstein and Ayer, and regards the six philosophers as the representatives of logical exceptionalism. From their standpoints, this paper refines the tenets of logical exceptionalism as follows: logic is exceptional to all other sciences because of four reasons: (i) logic is formal, neutral to any domain and any entities, and general; (ii) logical truths are made true by the meanings of logical constants they contain or by logicians' rational insight to consequence relations; (iii) logical truths are analytical, a prior and necessary, so not‐revisable; and (iv) logical laws are normative for how to correctly think. However, logical exceptionalism has encountered difficult open problems: What are logical constants? How to justify basic laws of logic? How are logical laws accessible to us? How to explain the reasonability of rival logics and select from them? How to explain the universal applicability of logical laws? How to explain the normativity of logical laws for correct thinking? This paper concludes that logical anti‐exceptionalism is more hopeful to successfully answer these questions than logical exceptionalism. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Theoria: A Swedish Journal of Philosophy. 2024/06, Vol. 90, Issue 3, p295
  • Document Type:Article
  • Subject Area:Literature and Writing
  • Publication Date:2024
  • ISSN:00405825
  • DOI:10.1111/theo.12533
  • Accession Number:177929573
  • Copyright Statement:Copyright of Theoria: A Swedish Journal of Philosophy 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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