RESEARCH ARTICLE


Causal Representation and Behavior: The Integration of Mechanism and Covariation



Jose C. Perales1, *, David R. Shanks2, David Lagnado2
1 Department of Experimental Psychology Faculty of Psychology University of Granada, Granada, Spain
2 Division of Psychology and Language Sciences University College London, London, England

Article Information


Identifiers and Pagination:

Year: 2010
Volume: 3
First Page: 174
Last Page: 183
Publisher ID: TOPSYJ-3-174
DOI: 10.2174/1874350101003010174

Article History:

Received Date: 02/10/2009
Revision Received Date: 07/01/2010
Acceptance Date: 08/01/2010
Electronic publication date: 13/7/2010
Collection year: 2010

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Creative Commons License
© 2010 Perales et al.

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: (https://creativecommons.org/licenses/by/4.0/legalcode). This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

* Address correspondence to this author at the Departamento de Psicología Experimental y Fisiología del Comportamiento, Universidad de Granada, Campus de Cartuja, s/n, 18071 Granada, Spain; Tel: +34 958 249609; Fax: +34 958 246239; E-mail: jcesar@ugr.es


Abstract

Causal knowledge can be based on acquired information about the statistical relationship (covariation) between a cause and effect or on knowledge of the mechanism by which causal power is transmitted between the cause and effect. A key issue is the functional significance of this distinction. In this article, we review recent research in which the influence of covariational evidence on prior beliefs was analyzed. We argue that the way in which covariation influences prior beliefs is independent of whether those beliefs are based on covariation or mechanism information, and that convincing demonstrations of the dissociability of the two types of causal knowledge have not been obtained. We argue that although there are several ways in which causal knowledge can be acquired, that knowledge shares a common representational basis.

Keywords: Causation, contingency, causal reasoning, human learning.