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Representing Causation

Wolff, Phillip (2007) Representing Causation. In: [2007] Workshop: Causality, Mechanisms, and Psychology (Pittsburgh, PA; 24 February, 2007).

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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)
    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
    Conferences and Volumes: [2007] Workshop: Causality, Mechanisms, and Psychology (Pittsburgh, PA; 24 February, 2007)
    Depositing User: Justin Sytsma
    Date Deposited: 13 Feb 2007
    Last Modified: 07 Oct 2010 11:14
    Item ID: 3177
    URI: http://philsci-archive.pitt.edu/id/eprint/3177

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