David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Ezio Di Nucci
Jonathan Jenkins Ichikawa
Jack Alan Reynolds
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Philosophy of Science 80 (5):660-671 (2013)
The manipulationist account of causation provides a conceptual analysis of cause-effect relationships in terms of hypothetical experiments. It also explains why and how experiments are used for the empirical testing of causal claims. This paper attempts to apply the manipulationist account of causation to a broader range of experiments—a range that extends beyond experiments explicitly designed for the testing of causal claims. I aim to show that the set of causal inferences afforded by an experiment is determined solely on the basis of contrasting case structures that I call “experimental series”, and that the conditions that suffice for causal inference obtain quite commonly, even among “ordinary” experiments that are not explicitly designed for the testing of causal claims
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References found in this work BETA
Jiji Zhang & Peter Spirtes (2008). Detection of Unfaithfulness and Robust Causal Inference. Minds and Machines 18 (2):239-271.
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