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Direct and Indirect Causes

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Part of the Boston Studies in the Philosophy of Science book series (BSPS, volume 256)

This paper presents my fullest account of probabilistic causation. After introducing the formal framework in section 2.2, it suggests splitting the explicatory task into two steps (in order to circumvent circularity objections) and then proceeds with an analysis of direct causation in section 2.3. Section 2.4 examines the various notions of the circumstances of a given causal relation suggested by this analysis. Section 2.5 discusses three approaches to extend the analysis to indirect causation: the structural approach requiring transitivity of causation, the Markovian approach characterizing causal chains by the Markov property, and the positive relevance approach generalizing the idea that a cause is positively relevant to its effect given the obtaining circumstances from direct to indirect causation. The paper shows that the three approaches are mutually incompatible, an observation that might explain many problems and confusions concerning probabilistic causation. Section 2.6 finally resolves the conflict by arguing that the structural approach assuming transitivity yields the most general theory of causation and by showing under which conditions causal chains conform to the other approaches.

Keywords

Markov Chain Causal Chain Transitive Closure Chain Condition Direct Causation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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© Springer Science + Business Media B.V 2009

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