Causality in the sciences
By: edited by Phyllis McKay Illari, Frederica Russo, Jon Williamson
Publisher: Oxford University Press
Published: 2011
Place of publication: Oxford; New York
Language: eng
Number of pages: 938
ISBN-13: 9780199574131
Subjects: Science; Causation; Philosophy; Causality
Description: There is a need for integrated thinking about causality, probability, and mechanism in scientific methodology. A panoply of disciplines, ranging from epidemiology and biology through to econometrics and physics, routinely make use of these concepts to infer causal relationships. But each of these disciplines has developed its own 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 progress in understanding the tools of causal inference in some sciences can lead to progress in other sciences, or whether the sciences are really using different concepts.

Causality and probability are long-established central concepts in the sciences, with a corresponding philosophical literature examining their problems. The philosophical literature examining the concept of mechanism, on the other hand, is more recent and there has been no clear account of how mechanisms relate to causality and probability. If we are to understand causal inference in the sciences, we need to develop some account of the relationship between causality, probability, and mechanism. This book represents a joint project by philosophers and scientists to tackle this question, and related issues, as they arise in a wide variety of disciplines across the sciences.
Notes: Includes bibliographical references and index.
Table of contents: title: Machine generated contents note: -- pt. I; title: Introduction -- -- 1.; title: Why look at causality in the sciences? A manifesto  -- Jon Williamson -- pt. II; title: Health sciences -- -- 2.; title: Causality, theories and medicine  -- R. Paul Thompson -- 3.; title: Inferring causation in epidemiology: Mechanisms, black boxes, and contrasts  -- Alex Broadbent -- 4.; title: Causal modeling, mechanism, and probability in epidemiology  -- Harold Kincaid -- 5.; title: The IARC and mechanistic evidence  -- Erik Weber -- 6.; title: The Russo-Williamson thesis and the question of whether smoking causes heart disease  -- Donald Gillies -- pt. III; title: Psychology -- -- 7.; title: Causal thinking  -- David Lagnado -- 8.; title: When and how do people reason about unobserved causes?  -- Christian Luhmann -- 9.; title: Counterfactual and generative accounts of causal attribution  -- Steven A. Sloman -- 10.; title: The autonomy of psychology in the age of neuroscience -- Carl Gillett; title: 11.; title: Turing machines and causal mechanisms in cognitive science  -- Anna-Mari Rusanen -- 12.; title: Real causes and ideal manipulations: Pearl's theory of causal inference from the point of view of psychological research methods  -- Keith A. Markus -- pt. IV; title: Social sciences -- -- 13.; title: Causal mechanisms in the social realm  -- Daniel Little -- 14.; title: Getting past Hume in the philosophy of social science  -- Ruth Groff -- 15.; title: Causal explanation: Recursive decompositions and mechanisms  -- Federica Russo -- 16.; title: Counterfactuals and causal structure  -- Kevin D. Hoover -- 17.; title: The error term and its interpretation in structural models in econometrics  -- Damien Fennell -- 18.; title: A comprehensive causality test based on the singular spectrum analysis  -- Abdol S. Soofi -- pt. V; title: Natural sciences -- -- 19.; title: Mechanism schemas and the relationship between biological theories  -- Tudor M. Baetu -- 20.; title: Chances and causes in evolutionary biology: How many chances become one chance  -- Roberta L. Millstein -- 21.; title: Drift and the causes of evolution  -- Sahotra Sarkar -- 22.; title: In defense of a causal requirement on explanation  -- Garrett Pendergraft -- 23.; title: Epistemological issues raised by research on climate change  -- Paolo Vineis -- 24.; title: Explicating the notion of 'causation' : the role of extensive quantities  -- Antonio Saggion -- 25.; title: Causal completeness of probability theories -- results and open problems  -- Balaza Gyenis -- pt. VI Computer science, probability, and statistics -- 26.; title: Causality workbench  -- Alexander Statnikov -- 27.; title: When are graphical causal models not good models?  -- Abdellah Touhafi -- 28.; title: Why making Bayesian networks objectively Bayesian makes sense -- Dawn E. Holmes; title: 29.; title: Probabilistic measures of causal strength  -- Christopher Hitchcock -- 30.; title: A new causal power theory  -- Lucas Hope -- . 31; title: Multiple testing of causal hypotheses  -- Bud Mishra -- 32.; title: Measuring latent causal structure  -- Ricardo Silva -- 33.; title: The structural theory of causation  -- Judea Pearl -- 34.; title: Defining and identifying the effect of treatment on the treated  -- A. Philip Dawid -- 35.; title: Predicting 'it will work for us' : (way) beyond statistics  -- Nancy Cartwright -- pt. VII; title: Causality and mechanisms -- -- 36.; title: The idea of mechanism  -- Stathis Psillos -- 37.; title: Singular and general causal relations : a mechanist perspective  -- Stuart Glennan -- 38.; title: Mechanisms are real and local  -- Jon Williamson -- 39.; title: Mechanistic information and causal continuity  -- Peter Machamer -- 40.; title: The causal-process-model theory of mechanisms  -- Phil Dowe -- 41.; title: Mechanisms in dynamically complex systems  -- Meinard Kuhlmann -- 42.; title: Third time's a charm : Causation, science and Wittgensteinian pluralism -- Julian Reiss.