Wolff, Phillip (2007) Representing Causation. In: UNSPECIFIED.

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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 1. 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.

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Item Type:	Conference or Workshop Item (UNSPECIFIED)
Creators:	Creators Email ORCID Wolff, Phillip
Additional Information:	This article has been accepted for publication in the Journal of Experimental Psychology: General.
Keywords:	causation, causal models, causal learning, knowledge, structures, lexical semantics
Subjects:	General Issues > Causation
Depositing User:	Justin Sytsma
Date Deposited:	13 Feb 2007
Last Modified:	07 Oct 2010 15:14
Item ID:	3177
Subjects:	General Issues > Causation
Date:	2007
URI:	https://philsci-archive.pitt.edu/id/eprint/3177

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