David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
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In Phyllis McKay Illari, Federica Russo & Jon Williamson (eds.), Causality in the Sciences. Oxford University Press. 45--69 (2011)
This chapter explores the idea that causal inference is warranted if and only if the mechanism underlying the inferred causal association is identified. This mechanistic stance is discernible in the epidemiological literature, and in the strategies adopted by epidemiologists seeking to establish causal hypotheses. But the exact opposite methodology is also discernible, the black box stance, which asserts that epidemiologists can and should make causal inferences on the basis of their evidence, without worrying about the mechanisms that might underlie their hypotheses. I argue that the mechanistic stance is indeed a bad methodology for causal inference. However, I detach and defend a mechanistic interpretation of causal generalisations in epidemiology as existence claims about underlying mechanisms.
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Citations of this work BETA
Phyllis Illari & Jon Williamson (2012). What is a Mechanism? Thinking About Mechanisms Across the Sciences. European Journal for Philosophy of Science 2 (1):119-135.
Phyllis McKay Illari (2011). Mechanistic Evidence: Disambiguating the Russo–Williamson Thesis. International Studies in the Philosophy of Science 25 (2):139 - 157.
Phyllis Illari (2011). Why Theories of Causality Need Production : An Information Transmission Account. [REVIEW] Philosophy and Technology 24 (2):95-114.
Brendan Clarke, Donald Gillies, Phyllis Illari, Federica Russo & Jon Williamson (2014). Mechanisms and the Evidence Hierarchy. Topoi 33 (2):339-360.
Michael Joffe (2013). The Concept of Causation in Biology. Erkenntnis 78 (2):179-197.
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