David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Ezio Di Nucci
Jack Alan Reynolds
Learn more about PhilPapers
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.
|Keywords||No keywords specified (fix it)|
|Categories||categorize this paper)|
Setup an account with your affiliations in order to access resources via your University's proxy server
Configure custom proxy (use this if your affiliation does not provide a proxy)
|Through your library|
References found in this work BETA
No references found.
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.
Brendan Clarke, Donald Gillies, Phyllis Illari, Federica Russo & Jon Williamson (2014). Mechanisms and the Evidence Hierarchy. Topoi 33 (2):339-360.
Phyllis McKay Illari (2011). Mechanistic Evidence: Disambiguating the Russo–Williamson Thesis. International Studies in the Philosophy of Science 25 (2):139 - 157.
Barbara Osimani (2014). Hunting Side Effects and Explaining Them: Should We Reverse Evidence Hierarchies Upside Down? Topoi 33 (2):295-312.
Anya Plutynski (2013). Cancer and the Goals of Integration. Studies in History and Philosophy of Science Part C (4):466-476.
Similar books and articles
Paul Thagard (1998). Explaining Disease: Correlations, Causes, and Mechanisms. [REVIEW] Minds and Machines 8 (1):61-78.
Federica Russo (2009). Variational Causal Claims in Epidemiology. Perspectives in Biology and Medicine 52 (4):540-554.
Phyllis McKay Illari, Federica Russo & Jon Williamson (eds.) (2011). Causality in the Sciences. Oxford University Press.
Erik Weber (2007). Social Mechanisms, Causal Inference, and the Policy Relevance of Social Science. Philosophy of the Social Sciences 37 (3):348-359.
Daniel Steel (2004). Social Mechanisms and Causal Inference. Philosophy of the Social Sciences 34 (1):55-78.
Holly Andersen (2012). The Case for Regularity in Mechanistic Causal Explanation. Synthese 189 (3):415-432.
D. Benjamin Barros (2013). Negative Causation in Causal and Mechanistic Explanation. Synthese 190 (3):449-469.
Max Kistler (2010). Mechanisms and Downward Causation. Philosophical Psychology 22 (5):595-609.
Karl-Dieter Opp (2005). Explanations by Mechanisms in the Social Sciences. Problems, Advantages and Alternatives. Mind and Society 4 (2):163-178.
Johannes Persson (2010). Activity-Based Accounts of Mechanism and the Threat of Polygenic Effects. Erkenntnis 72 (1):135 - 149.
Alison Gopnik & Laura Schulz (eds.) (2007). Causal Learning: Psychology, Philosophy, and Computation. Oxford University Press.
Daniel Steel (2007). With or Without Mechanisms A Reply to Weber. Philosophy of the Social Sciences 37 (3):360-365.
Added to index2011-05-24
Total downloads427 ( #2,571 of 1,790,408 )
Recent downloads (6 months)119 ( #4,069 of 1,790,408 )
How can I increase my downloads?