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Causation: A User's Guide
Abstract
Causation is at once familiar and mysterious - we can detect its presence in the world, but we cannot agree on the metaphysics of the causal relation. L.A. Paul and Ned Hall guide the reader through the most important philosophical treatments of causation, and develop a broad and sophisticated understanding of the issues under debate.
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Every theory of causation faces challenges under some circumstances.
“This is not to say that counterfactual theories are without problems because every theory of causation faces challenges under some circumstances (Paul and Hall 2013:chap. 2).”
From Check Your Truth Conditions! Clarifying the Relationship between Theories of Causation and Social Science Methods for Causal Inference (2021) · cites this paper as Paul and Hall 2013
Counterfactual dependence between events is not necessarily transitive.
“However, counterfactual dependence between events is not necessarily transitive (e.g., in cases of double prevention; Paul and Hall 2013:chap. 5).”
From Check Your Truth Conditions! Clarifying the Relationship between Theories of Causation and Social Science Methods for Causal Inference (2021) · cites this paper as Paul and Hall 2013
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Metadata
- Authors
- Paul, L. A., & Hall, N.
- ORCID
- Paul, L. A.
- Venue
- Oxford University Press eBooks
- Publisher
- Oxford University Press
- Published
- 2013-04-25
- OpenAlex
- W4231896879
- Cited by
- 259
- References
- 0
- Citations by year
- 2026: 38 · 2025: 40 · 2024: 18 · 2023: 12 · 2022: 20 · 2021: 18 · 2020: 18 · 2019: 28 · 2018: 14 · 2017: 17 · 2016: 21 · 2015: 8 · 2014: 6 · 2013: 1
- FWCI
- 17.55
- Type
- book
- Language
- en
- Open access
- closed
- Locations
- Oxford University Press eBooks (publishedVersion)
- DIAL (Catholic University of Leuven) (submittedVersion)
- Topics
- Social Sciences › Arts and Humanities › History and Philosophy of Science › Philosophy of Biology and Scientific Explanation
- Social Sciences › Arts and Humanities › Philosophy › Epistemology, Ethics, and Metaphysics
- Physical Sciences › Computer Science › Artificial Intelligence › Bayesian Modeling and Causal Inference
- Keywords
- causality, metaphysics of causation, causal relationship, philosophy of causation, causal theories
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