Causality, Probability, and Medicine  book cover
1st Edition

Causality, Probability, and Medicine

ISBN 9781138829305
Published August 22, 2018 by Routledge
300 Pages

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Book Description

Why is understanding causation so important in philosophy and the sciences? Should causation be defined in terms of probability? Whilst causation plays a major role in theories and concepts of medicine, little attempt has been made to connect causation and probability with medicine itself.

Causality, Probability, and Medicine is one of the first books to apply philosophical reasoning about causality to important topics and debates in medicine. Donald Gillies provides a thorough introduction to and assessment of competing theories of causality in philosophy, including action-related theories, causality and mechanisms, and causality and probability. Throughout the book he applies them to important discoveries and theories within medicine, such as germ theory; tuberculosis and cholera; smoking and heart disease; the first ever randomized controlled trial designed to test the treatment of tuberculosis; the growing area of philosophy of evidence-based medicine; and philosophy of epidemiology.

This book will be of great interest to students and researchers in philosophy of science and philosophy of medicine, as well as those working in medicine, nursing and related health disciplines where a working knowledge of causality and probability is required.

Table of Contents


Part 1: Causality and Action

1. An action-related theory of causality

2. General discussion of AIM theories of causality

3. An example from medicine. Koch’s work on bacterial diseases and his postulates

Part 2: Causality and Mechanisms

4. Mechanistic theories of causality and causal theories of Mechanism

5. Types of evidence: (i) evidence of mechanism

6. Types of evidence: (ii) statistical evidence in human populations

7. Combining statistical evidence with evidence of mechanism

8. The Russo-Williamson thesis: (i) effects of smoking on health

9. The Russo-Williamson thesis: (ii) the evaluation of streptomycin and thalidomide

10. Objections to the Russo-Williamson thesis

11. Discovering cures in medicine and seeking for deeper explanations

Part 3: Causality and Probability

12. Indeterministic causality

13. Causal networks

14. How should probabilities be interpreted?

15. Pearl’s alternative approach to linking causality and probability

16. Extension of the action-related theory to the indeterministic case

Appendix 1. Example of a simple medical intervention which is not an intervention in Woodward’s sense

Appendix 2. Mathematical Terminology

Appendix 3. Sudbury’s Theorems

Glossary of Medical Terms


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Donald Gillies is Emeritus Professor of Philosophy of Science and Mathematics at University College London, UK.


"...[B]ound to become a must-read for any scholars interested in medical methodology, especially in how notions such as causality, evidence, mechanism, and probability intersect. These intersections have many facets, and Gillies gives us his own story of how they are linked. It is to be hoped that others will contribute to these debates, whether by examining other historical case studies, or exploring other practices in medicine where these issues are at stake." - Federica Russo, Notre Dame Philosophical Reviews

"This book is just what philosophy of medicine needs – careful argumentative analysis of issues that matter to the practice of biomedical science." - Harold Kincaid, University of Cape Town, South Africa

"With his usual clarity, Professor Gillies manages to deal simultaneously with two among the most complex and thorny issues in science and philosophy of science: causality and probability. And he does so in a field – medicine – where their complexity grows exponentially, because of the theoretical and practical challenges of understanding and curing disease. The book is therefore an essential guide to those who want to delve into medicine." - Federica Russo, University of Amsterdam, The Netherlands

"This book develops a philosophical theory of causality in a very engaging and readable way. It sheds light on many historical examples of medical discovery and also on present-day causal modelling methods. Essential reading for anyone interested in causality, probability, or medicine." - Jon Williamson, University of Kent, UK

"Although the book often deals with quite technical and complicated material, it remains accessible throughout because the written expression is characteristically clear and engaging. All of the mathematical details are confined to a couple of appendices, which sit alongside a helpful glossary of medical terms. The book is also an excellent example of an approach in the philosophy of science that draws philosophical conclusions on the basis of a close examination of historical examples from actual scientific practic[....] It is therefore essential reading for anyone working in the history and philosophy of science and in particular the philosophy of medicine." -Daniel Auker‑Howlett & Michael Wilde, University of Kent, Canterbury, UK