Abstract
How ought we learn causal relationships? While Popper advocated a hypothetico-deductive logic of causal discovery, inductive accounts are currently in vogue. Many inductive approaches depend on the causal Markov condition as a fundamental assumption. This condition, I maintain, is not universally valid, though it is justifiable as a default assumption. In which case the results of the inductive causal learning procedure must be tested before they can be accepted. This yields a synthesis of the hypothetico-deductive and inductive accounts, which forms the focus of this paper. I discuss the justification of this synthesis and draw an analogy between objective Bayesianism and the account of causal learning presented here.
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Interpreting Causality in the Health Sciences.Federica Russo & Jon Williamson - 2007 - International Studies in the Philosophy of Science 21 (2):157 – 170.
Generic Versus Single-Case Causality: The Case of Autopsy. [REVIEW]Jon Williamson - 2011 - European Journal for Philosophy of Science 1 (1):47-69.
Response to Glymour. [REVIEW]Jon Williamson - 2009 - British Journal for the Philosophy of Science 60 (4):857-860.

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