|
|
FORCE DYNAMICS AND THE SEMANTICS
OF NEGATIVE CAUSATION
Phillip Wolff Emory University Wednesday, November 14, 5:30pm, MJH Rm 126 According to process theories of causation, people represent causation by modeling the physical and social processes that bring about causation in the world. These theories usually require that causal relations involve an uninterrupted chain of influences from the cause to the effect. A key problem for this view is the phenomenon of "negative causation." Negative causation is present when causation occurs in the absence of a cause. We say, for example, "The absence of nicotine causes withdrawal" or "Lack of water causes thirst." It is also present in cases of so-called "double prevention," or, situations where preventions are prevented, as when, for example, rescuers prevent guards from preventing an escape and thereby cause or allow the escape. In all cases of negative causation, there is a gap in the chain of influences from the cause to the effect. In my talk I show that negative causation is not, in fact, a problem for process theories based on force dynamics. Indeed, several patterns in the meaning of causal expressions encoding negative causation may provide support for process approaches over competing approaches. According to statistical, counterfactual, and logical approaches to causation, expressions of causation involving negation and positive causation are symmetric: for example, NOT-CAUSE --> PREVENT and PREVENT --> NOT-CAUSE. In contrast, from a force dynamic perspective these different expressions are often related to each other asymmetrically: for example, NOT-CAUSE --> PREVENT, but not PREVENT --> NOT-CAUSE. The predictions of the force dynamic approach were supported in several experiments in which people re-expressed causal expressions taken from the internet and described animations depicting complex causal interactions. Because these asymmetries cannot be explained by statistical or logical approaches, the results support the view that causal reasoning involves simulating the actual processes that bring about causation in the world. 
|