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CLOSURE AS IT RELATES TO DEDUCTIVE, INDUCTIVE, AND ABDUCTIVE REASONING.

  • Published In: ETC: A Review of General Semantics, 2024, v. 81, n. 3. P. 366 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: AGOSTINO, JOSEPH N. 3 of 3

Abstract

The present study, which investigated closure as it relates to deductive, inductive, and abductive reasoning, was based on the assumption that closure processes as understood in perception, were the same or similar to closure processes in reasoning. Closure, primarily investigated in perception, is described as the phenomenal completion of incomplete stimuli; closure in reasoning is defined as the completion of open structures inherent in deductive, inductive, and abductive processes. Closure, as understood in deductive reasoning, utilizes syllogism to facilitate the reasoning process. The syllogism is considered an open structure that calls for closure. The fundamental nature of inductive reasoning is that it allows for modification of the original premise based on supportive information. Because it allows for modification, inductive reasoning is considered an open structure that calls for closure. In abductive reasoning, the observed event presents as a problem that is incomplete and calls for closure. Closure is achieved by formulating and testing hypotheses and eliminating hypotheses that do not explain all aspects of the observed event. In the present study, closure in perception provided a fruitful approach to the study of closure in reasoning processes. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:ETC: A Review of General Semantics. 2024/07, Vol. 81, Issue 3, p366
  • Document Type:Article
  • Subject Area:Religion and Philosophy
  • Publication Date:2024
  • ISSN:0014-164X
  • Accession Number:184367092
  • Copyright Statement:Copyright of ETC: A Review of General Semantics is the property of Institute of General Semantics, Inc. 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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