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date: 27 September 2020

Abstract and Keywords

In its simplest form, a causal model of explanation maintains that to explain some phenomenon is to give some information about its causes. This prompts four questions that will structure the discussion to follow. The first is whether all explanations are causal. The second is whether all causes are explanatory. The answer to both of these questions turns out to be negative, and seeing why this is so helps to clarify the relationship between causation and explanation. The third question is itself a request for an explanation: Why do causes explain, when they do? Why, for example, do causes explain their effects but effects not explain their causes? Finally, the article considers how explanation can illuminate the process of causal inference.

Keywords: model of explanation, causal model, causation, causal inference, reward and punishment, efficient causation

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