A Probabilistic Analysis of Causation

The starting point in the development of probabilistic analyses of token causation has usually been the naïve intuition that, in some relevant sense, a cause raises the probability of its effect. But there are well-known examples both of non-probability-raising causation and of probability-raising non-causation. Sophisticated extant probabilistic analyses treat many such cases correctly, but only at the cost of excluding the possibilities of direct non-probability-raising causation, failures of causal transitivity, action-at-a-distance, prevention, and causation by absence and omission. I show that an examination of the structure of these problem cases suggests a different treatment, one which avoids the costs of extant probabilistic analyses. 1 Introduction 2 A Naïve Probabilistic Analysis, Two Objections and a Refinement 3 Non-probability-raising Causation 4 Graphical Representation of Cases of Non-probability-raising Causation 5 Probability-raising Non-causation 6 Graphical Representation of Cases of Probability-raising Non-causation 7 Completing the Probabilistic Analysis of Causation 8 Problem Cases for Extant Probabilistic Analyses  8.1 Causation by omission  8.2 Direct non-probability-raising causation  8.3 Failures of transitivity 9 Conclusion 1 Introduction 2 A Naïve Probabilistic Analysis, Two Objections and a Refinement 3 Non-probability-raising Causation 4 Graphical Representation of Cases of Non-probability-raising Causation 5 Probability-raising Non-causation 6 Graphical Representation of Cases of Probability-raising Non-causation 7 Completing the Probabilistic Analysis of Causation 8 Problem Cases for Extant Probabilistic Analyses  8.1 Causation by omission  8.2 Direct non-probability-raising causation  8.3 Failures of transitivity  8.1 Causation by omission  8.2 Direct non-probability-raising causation  8.3 Failures of transitivity 9 Conclusion

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