Causality in the Sciences
Oxford University Press (2011)
| Abstract | There is a need for integrated thinking about causality, probability and mechanisms in scientific methodology. Causality and probability are long-established central concepts in the sciences, with a corresponding philosophical literature examining their problems. On the other hand, the philosophical literature examining mechanisms is not long-established, and there is no clear idea of how mechanisms relate to causality and probability. But we need some idea if we are to understand causal inference in the sciences: a panoply of disciplines, ranging from epidemiology to biology, from econometrics to physics, routinely make use of probability, statistics, theory and mechanisms to infer causal relationships. These disciplines have developed very different methods, where causality and probability often seem to have different understandings, and where the mechanisms involved often look very different. This variegated situation raises the question of whether the different sciences are really using different concepts, or whether progress in understanding the tools of causal inference in some sciences can lead to progress in other sciences. The book tackles these questions as well as others concerning the use of causality in the sciences. | |||||||||
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| ISBN(s) | 9780199574131 | |||||||||
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Federica Russo & Jon Williamson (2007). Interpreting Causality in the Health Sciences. International Studies in the Philosophy of Science 21 (2):157 – 170.
Phyllis McKay Illari, Federica Russo & Jon Williamson (eds.) (2011). Causality in the Sciences. Oxford University Press.
Alex Broadbent (2011). Inferring Causation in Epidemiology: Mechanisms, Black Boxes, and Contrasts. In Phyllis McKay Illari, Federica Russo & Jon Williamson (eds.), Causality in the Sciences. Oxford University Press.
Daniel Steel (2004). Social Mechanisms and Causal Inference. Philosophy of the Social Sciences 34 (1):55-78.
Bert Leuridan & Erik Weber (2012). Causality and Explanation in the Sciences. Theoria 27 (2):133-136.
Judea Pearl (2000). Causality: Models, Reasoning, and Inference. Cambridge University Press.
Timothy L. Hubbard (forthcoming). Phenomenal Causality II: Integration and Implication. Axiomathes:1-40.
Bert Leuridan (2007). Galton's Blinding Glasses. Modern Statistics Hiding Causal Structure in Early Theories of Inheritance. In Federica Russo & Jon Williamson (eds.), Causality and Probability in the Sciences.
Howard Engelskirchen (2007). Realism About Causality in Social Science. Sociology's Causal Confusion / Douglas Porpora; the Mother of All Isms: Causal Mechanisms in Political Science / Andrew Bennett; Marxisn Crisis Theory and Causality / Robert Albritton; on the Clear Comprehension of Political Economy: Social Kinds and the Significance of Marx's Capital. In Ruth Groff (ed.), Revitalizing Causality: Realism About Causality in Philosophy and Social Science. Routledge.
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