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Rational argument, rational inference

Hahn, Ulrike, Oaksford, M. and Harris, Adam J. L. 2013. Rational argument, rational inference. Argument and Computation 4 (1) , pp. 21-35. 10.1080/19462166.2012.689327

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Abstract

Reasoning researchers within cognitive psychology have spent decades examining the extent to which human inference measures up to normative standards. Work here has been dominated by logic, but logic has little to say about most everyday, informal arguments. Empirical work on argumentation within psychology and education has studied the development and improvement of argumentation skills, but has been theoretically limited to broad structural characteristics. Using the catalogue of informal reasoning fallacies established over the centuries within the realms of philosophy, Hahn and Oaksford (2007a32. Hahn, U. and Oaksford, M. 2007a. The Rationality of Informal Argumentation: A Bayesian Approach to Reasoning Fallacies. Psychological Review, 114: 704–732. (doi:10.1037/0033-295X.114.3.704) View all references) recently demonstrated how Bayesian probability can provide a normative standard by which to evaluate quantitatively the strength of a wide range of everyday arguments. This broadens greatly the potential scope of reasoning research beyond the rather narrow set of logical and inductive arguments that have been studied; it also provides a framework for the normative assessment of argument content that has been lacking in argumentation research. The Bayesian framework enables both qualitative and quantitative experimental predictions about what arguments people should consider to be weak and strong, against which people's actual judgements can be compared. This allows the different traditions of reasoning and argumentation research to be brought together both theoretically and in empirical research.

Item Type: Article
Date Type: Submission
Status: Published
Schools: Psychology
Subjects: B Philosophy. Psychology. Religion > BF Psychology
Uncontrolled Keywords: formal models of argumentation, argument & automated reasoning, cognitive science, interdisciplinary links with computational argument, conditionals, interdisciplinary links with computational argument, Bayesian probability
Publisher: Taylor & Francis
ISSN: 1946-2166
Last Modified: 08 Mar 2020 16:55
URI: http://orca-mwe.cf.ac.uk/id/eprint/30690

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