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Index
Cover
Title page
Copyright
Contents
Foreword
Acknowledgements
Part I: Prelude to Causality
1. Problems of Causality in the Sciences
1.1 Why this book on causality?
1.2 Five scientific problems
1.3 The contents of this book
2. A Scientific Toolbox for Philosophy
2.1 Methods for finding causes
2.2 Observational methods
2.3 Experimental methods
2.4 Between observation and experiment
2.5 Beyond observation and experiment
2.6 How to make a study work
2.6.1 The problem of confounding
2.6.2 The problem of validity
3. A Philosophical Toolbox for Science
3.1 Arguments
3.2 Methods
3.3 Levels of abstraction
Part II: Causality: Accounts, Concepts and Methods
4. Necessary and Sufficient Components
4.1 Examples: electrical short-circuit and AIDS
4.2 Component causes
4.3 INUS causes and related concepts
4.4 Rothman’s pie charts
5. Levels of Causation
5.1 Examples: personalized medicine and migration behaviours
5.2 Three parallel literatures
5.2.1 The philosophical literature
5.2.2 The legal literature
5.2.3 The scientific literature
5.3 Bridging the levels—and the terminology!
5.3.1 The terminological gap
5.3.2 The relation between the levels
6. Causality and Evidence
6.1 Examples: effects of radiation and smoking causing heart disease
6.2 What do we want to know?
6.3 Evidence for causal relations
6.3.1 Bradford Hill’s guidelines to evaluating evidence
6.3.2 The Russo-Williamson thesis
6.3.3 What is evidence of mechanism and why is it helpful?
6.3.4 What is evidence of difference-making and why is it helpful?
6.4 Evidence-based approaches
6.4.1 A procedural approach to evidence?
7. Causal Methods: Probing the Data
7.1 Examples: apoptosis and self-rated health
7.2 The need for causal methods
7.2.1 Two aims for causal methods
7.3 The most widespread causal methods
7.5 Key notions in causal methods
8. Difference-making: Probabilistic Causality
8.1 Example: smoking and lung cancer
8.2 Is causality probability-altering?
8.3 Beyond probabilistic causes
8.3.1 Determinism/indeterminism and predictability
8.3.2 Interpretation of probability in probabilistic causality
8.3.3 A development: probabilistic temporal logic
9. Difference-making: Counterfactuals
9.1 Example: mesothelioma and safety at work
9.2 The unbearable imprecision of counterfactual reasoning
9.3 Philosophical views of counterfactuals
9.3.1 Lewis: possible-world semantics for counterfactuals
9.3.2 Problems for Lewis’s account
9.3.3 Rescher’s method of validation
9.4 Counterfactuals in other fields
9.4.1 Counterfactuals in the law
9.4.2 Counterfactuals in psychology
9.4.3 Statistical counterfactuals
10. Difference-making: Manipulation and Invariance
10.1 Example: gene knock-out experiments
10.2 The manipulationists: wiggle the cause, and the effect wiggles too
10.3 What causes can’t we wiggle?
10.3.1 What is an intervention?
10.3.2 Modularity
10.3.3 Conceptual versus methodological manipulationism
10.3.4 Explanation
11. Production Accounts: Processes
11.1 Examples: billiard balls colliding and aeroplanes crossing
11.2 Tracing processes
11.3 How widely does the approach apply?
11.3.1 Motivation for the account
11.3.2 Applicability
11.3.3 Causal relevance
11.3.4 Does the approach apply to all of physics?
11.3.5 Absences
12. Production Accounts: Mechanisms
12.1 Example: how can smoking cause heart disease?
12.2 What is a mechanism? The major mechanists
12.3 Important features of mechanisms and mechanistic explanation
12.3.1 Function
12.3.2 Context
12.3.3 Organization
12.3.4 Applicability
12.4 What is not a mechanism?
13. Production Accounts: Information
13.1 Examples: tracing transmission of waves and of disease
13.2 The path to informational accounts
13.2.1 Information theory and generality
13.2.2 Early views in philosophy: Reichenbach and Salmon
13.2.3 Collier: the first explicitly informational account
13.2.4 Informational approaches to other issues
13.3 Integrating the informational and mechanistic approaches
13.4 Future prospects for an informational account of causality
13.4.1 Applicability
13.4.2 Absences
13.4.3 Vacuity
14. Capacities, Powers, Dispositions
14.1 Examples: systems in physics and biology
14.2 The core idea of capacities, powers and dispositions
14.3 Capacities in science: explanation and evidence
14.3.1 Explanation
14.3.2 Evidence of capacities
14.3.3 Masking
14.3.4 Interactions
15. Regularity
15.1 Examples: natural and social regularities
15.2 Causality as regular patterns
15.3 Updating regularity for current science
15.3.1 What Humean regularity can’t achieve
15.3.2 Where to go?
16. Variation
16.1 Example: mother’s education and child survival
16.2 The idea of variation
16.2.1 Variation for pioneering methodologists
16.2.2 Current variation accounts
16.3 Variation in observational and experimental methods
17. Causality and Action
17.1 Example: symmetry in physics; asymmetry in agency
17.2 Early agency theorists
17.3 Agency and the symmetry problem
17.4 Agency and action
17.5 Problems for agency theories
17.6 Merits of agency theories
18. Causality and Inference
18.1 Example: combatting the spread of AIDS
18.2 Different sorts of inferences
18.2.1 Beebee’s Humean projectivism
18.2.2 Williamson’s epistemic theory
18.2.3 Reiss’ inferentialism
18.2.4 Spohn’s ranking functions
18.3 Does inferentialism lead to anti-realism?
18.4 The heart of inference
Part III: Approaches to Examining Causality
19. How We Got to the Causality in the Sciences Approach (CitS)
19.1 A methodological struggle
19.2 Causality and language
19.3 Causality, intuitions and concepts
19.4 Causality in the sciences
20. Examples and Counterexamples
20.1 Examples of examples!
20.2 Toy examples or scientific examples?
20.2.1 Examples impeding the progress of debate
20.2.2 Examples enhancing progress in debate
20.3 Counterexamples
21. Truth or Models?
21.1 Two approaches to causal assessment
21.2 Causal assessment using models
21.3 Causal assessment identifying truthmakers
21.4 Truth or models?
21.4.1 Wait, what happened to truth?
22. Epistemology, Metaphysics, Method, Semantics, Use
22.1 Fragmented theorizing about causality
22.1.1 Epistemology
22.1.2 Metaphysics
22.1.3 Method
22.1.4 Semantics
22.1.5 Use
22.2 Which question to answer when?
22.3 Which question interests me?
22.4 Should we integrate the fragments?
Part IV: Conclusion: Towards a Causal Mosaic
23. Pluralism
23.1 If pluralism is the solution, what is the problem?
23.2 Various types of causing
23.3 Various concepts of causation
23.4 Various types of inferences
23.5 Various sources of evidence for causal relations
23.6 Various methods for causal inference
23.7 The pluralist mosaic
24. The Causal Mosaic Under Construction: the Example of Exposomics
24.1 Making mosaics
24.2 Preparing materials for the exposomics mosaic
24.2.1 Exposomics, or the science of exposure
24.2.2 Question 1: What scientific problems would it be useful to address?
24.2.3 Question 2: What do the scientists want to know or do, and what problems of diversity do they face?
24.2.4 Question 3: What philosophical questions would it be useful to address?
24.3 Building the exposomics mosaic
24.3.1 Question 4: What accounts might be useful?
24.3.2 Question 5: How can we put together these resources to help us in our thinking?
24.3.3 How many mosaics?
Appendix: Accounts, Concepts and Methods: Summary Tables
A.1 The scientific problems of causality
A.2 The philosophical questions about causality
A.3 The accounts: how they fare with scientific problems
A.4 The accounts: how they fare with philosophical questions
References
Index
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