Literature DB >> 17324086

Representing causation.

Phillip Wolff1.   

Abstract

The dynamics model, which is based on L. Talmy's (1988) theory of force dynamics, characterizes causation as a pattern of forces and a position vector. In contrast to counterfactual and probabilistic models, the dynamics model naturally distinguishes between different cause-related concepts and explains the induction of causal relationships from single observations. Support for the model is provided in experiments in which participants categorized 3-D animations of realistically rendered objects with trajectories that were wholly determined by the force vectors entered into a physics simulator. Experiments 1-3 showed that causal judgments are based on several forces, not just one. Experiment 4 demonstrated that people compute the resultant of forces using a qualitative decision rule. Experiments 5 and 6 showed that a dynamics approach extends to the representation of social causation. Implications for the relationship between causation and time are discussed. ((c) 2007 APA, all rights reserved).

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Year:  2007        PMID: 17324086     DOI: 10.1037/0096-3445.136.1.82

Source DB:  PubMed          Journal:  J Exp Psychol Gen        ISSN: 0022-1015


  25 in total

Review 1.  Motion as manipulation: implementation of force-motion analogies by event-file binding and action planning.

Authors:  Chris Fields
Journal:  Cogn Process       Date:  2012-02-14

2.  Implementation of structure-mapping inference by event-file binding and action planning: a model of tool-improvisation analogies.

Authors:  Chris Fields
Journal:  Psychol Res       Date:  2010-06-05

Review 3.  Carving the world for language: how neuroscientific research can enrich the study of first and second language learning.

Authors:  Nathan R George; Tilbe Göksun; Kathy Hirsh-Pasek; Roberta Michnick Golinkoff
Journal:  Dev Neuropsychol       Date:  2014       Impact factor: 2.253

4.  Space, time, and causality in the human brain.

Authors:  Adam J Woods; Roy H Hamilton; Alexander Kranjec; Preet Minhaus; Marom Bikson; Jonathan Yu; Anjan Chatterjee
Journal:  Neuroimage       Date:  2014-02-19       Impact factor: 6.556

5.  Causal inference and the hierarchical structure of experience.

Authors:  Samuel G B Johnson; Frank C Keil
Journal:  J Exp Psychol Gen       Date:  2014-10-27

6.  Failures of explaining away and screening off in described versus experienced causal learning scenarios.

Authors:  Bob Rehder; Michael R Waldmann
Journal:  Mem Cognit       Date:  2017-02

7.  How do preschoolers express cause in gesture and speech?

Authors:  Tilbe Göksun; Kathy Hirsh-Pasek; Roberta Michnick Golinkoff
Journal:  Cogn Dev       Date:  2010

8.  Expectations and interpretations during causal learning.

Authors:  Christian C Luhmann; Woo-Kyoung Ahn
Journal:  J Exp Psychol Learn Mem Cogn       Date:  2011-05       Impact factor: 3.051

9.  Linking language with embodied and teleological representations of action for humanoid cognition.

Authors:  Stephane Lallee; Carol Madden; Michel Hoen; Peter Ford Dominey
Journal:  Front Neurorobot       Date:  2010-06-03       Impact factor: 2.650

10.  Space-The Primal Frontier? Spatial Cognition and the Origins of Concepts.

Authors:  Frank C Keil
Journal:  Philos Psychol       Date:  2008-04-01
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