ERIC Number: EJ1204225
Record Type: Journal
Publication Date: 2019-Feb
Pages: 4
Abstractor: As Provided
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ISSN: ISSN-0278-7393
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How to Infer Possibilities: A Reply to Oaksford et al. (2018)
Hinterecker, Thomas; Knauff, Markus; Johnson-Laird, P. N.
Journal of Experimental Psychology: Learning, Memory, and Cognition, v45 n2 p298-301 Feb 2019
Individuals draw conclusions about possibilities from assertions that make no explicit reference to them. The model theory postulates that assertions such as disjunctions refer to possibilities. Hence, a disjunction of the sort, "A or B or both," where "A" and "B" are sensible clauses, yields mental models of an exhaustive conjunction of "possibly A," "possibly B," and "possibly both A and B," which each hold in default of information to the contrary. Oaksford, Over, and Cruz (this issue) are critical of the model theory and defend a probabilistic approach to reasoning. In this reply, we deal with their three main claims: (a) "Our results concern only the periphery of their probabilistic theory." We show that they refute their theory insofar as it applies to possibilities. (b) "The model theory leads to logical absurdities." We rebut this criticism as it applies to the model theory in Hinterecker, Knauff, and Johnson-Laird (2016), and explain why standard modal logics, which concern possibilities, do not set appropriate norms for inferences about them. (c) "The algorithm for reasoning based on models needs a normative theory." In fact, it has such a theory, but the demand for "a specification of a sound, complete, and decidable normative system" is chimerical for everyday reasoning. [For the article by Oaksford et al., "Paradigms, Possibilities, and Probabilities: Comment on Hinterecker, Knauff, and Johnson-Laird (2016)," see EJ1204226.]
Descriptors: Logical Thinking, Abstract Reasoning, Inferences, Probability, Models, Theories, Criticism, Prediction, Bayesian Statistics
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Publication Type: Journal Articles; Reports - Evaluative; Opinion Papers
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Language: English
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