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.
| Keywords: | causation, causal models, causal learning, knowledge, structures, lexical semantics |
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| Subjects: | General Issues: Causation |
| Conferences and Volumes: | [2007] Workshop: Causality, Mechanisms, and Psychology (Pittsburgh, PA; 24 February, 2007) |
| ID Code: | 3177 |
| Deposited By: | Sytsma, Justin |
| Deposited On: | 13 Febuary 2007 |
| Additional Information: | This article has been accepted for publication in the Journal of Experimental Psychology: General. |