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Naive causality: a mental model theory of causal meaning and reasoning
Author(s) -
Goldvarg Eugenia,
JohnsonLaird P.N.
Publication year - 2001
Publication title -
cognitive science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.498
H-Index - 114
eISSN - 1551-6709
pISSN - 0364-0213
DOI - 10.1207/s15516709cog2504_3
Subject(s) - causality (physics) , causation , meaning (existential) , causal reasoning , constraint (computer aided design) , causal model , relation (database) , causal theory of reference , epistemology , probabilistic logic , psychology , mental representation , causal structure , cognitive psychology , cognitive science , cognition , computer science , mathematics , philosophy , statistics , physics , geometry , quantum mechanics , database , neuroscience
This paper outlines a theory and computer implementation of causal meanings and reasoning. The meanings depend on possibilities, and there are four weak causal relations: A causes B, A prevents B, A allows B , and A allows not‐B , and two stronger relations of cause and prevention. Thus, A causes B corresponds to three possibilities: A and B, not‐A and B, and not‐A and not‐B, with the temporal constraint that B does not precede A; and the stronger relation conveys only the first and last of these possibilities. Individuals represent these relations in mental models of what is true in the various possibilities. The theory predicts a number of phenomena, and, contrary to many accounts, it implies that the meaning of causation is not probabilistic, differs from the meaning of enabling conditions, and does not depend on causal powers or mechanisms. The theory also implies that causal deductions do not depend on schemas or rules.