David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
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European Journal for Philosophy of Science 2 (3):435-452 (2012)
Probabilistic phenomena are often perceived as being problematic targets for contrastive explanation. It is usually thought that the possibility of contrastive explanation hinges on whether or not the probabilistic behaviour is irreducibly indeterministic, and that the possible remaining contrastive explananda are token event probabilities or complete probability distributions over such token outcomes. This paper uses the invariance-under-interventions account of contrastive explanation to argue against both ideas. First, the problem of contrastive explanation also arises in cases in which the probabilistic behaviour of the explanandum is due to unobserved causal heterogeneity. Second, it turns out that, in contrast to the case of pure indeterminism, the plausible contrastive explananda under causal heterogeneity are not token event probabilities, but population-level statistical facts
|Keywords||Contrastive explanation Statistics Heterogeneity Indeterminism Invariance|
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References found in this work BETA
Judea Pearl (2000). Causality: Models, Reasoning, and Inference. Cambridge University Press.
James Woodward (2003). Making Things Happen: A Theory of Causal Explanation. Oxford University Press.
Wesley Salmon (1984). Scientific Explanation and the Causal Structure of the World. Princeton University Press.
Nancy Cartwright (1989). Nature's Capacities and Their Measurement. Oxford University Press.
David Lewis (1986). Philosophical Papers Vol. II. Oxford University Press.
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