Please use this identifier to cite or link to this item: http://hdl.handle.net/10071/28212
Author(s): Ferreira, M. B.
Garcia-Marques, L.
Sherman, S. J.
Garrido, M.
Date: 2006
Title: Automatic and controlled components of judgment under uncertainty
Volume: 28
Book title/volume: Proceedings of the Annual Meeting of the Cognitive Science Society
Pages: 1293 - 1298
Event title: CogSci2006 - 28th Annual Meeting of the Cognitive Science Society
Reference: Ferreira, M. B., Garcia-Marques, L., Sherman, S. J., & Garrido, M. (2006). Automatic and controlled components of judgment under uncertainty. Proceedings of the Annual Meeting of the Cognitive Science Society, 28, 1293-1298. http://hdl.handle.net/10071/28212
ISSN: 1069-7977
Keywords: Heuristics
Dual process models
Automatic processes
Controlled processes
Judgment under uncertainty
Abstract: The categorization of inductive reasoning into largely automatic processes (heuristic reasoning) and controlled analytical processes (rule-based reasoning) put forward by dual-process approaches of judgment under uncertainty (e.g., Stanovich & West, 2000) has been primarily a matter of assumption with a scarcity of direct empirical findings supporting it. We used the process dissociation procedure (Jacoby, 1991) to provide convergent evidence validating a dual-process perspective to judgment under uncertainty based on the independent contributions of heuristic and rule-based reasoning. Process dissociations based on experimental manipulation of variables were derived from relevant theoretical properties typically used to contrast the two forms of reasoning. These included processing goals (Experiment 1) and priming (Experiment 2). Results consistently supported the present perspective. We conclude that judgment under uncertainty is not either an automatic or controlled process, but that it reflects both processes, with each making independent contributions.
Peerreviewed: yes
Access type: Open Access
Appears in Collections:CIS-CRI - Comunicações a conferências internacionais

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