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  1. Robert John Ackermann (1989). Wesley C. Salmon., Scientific Explanation and the Causal Structure of the World. International Studies in Philosophy 21 (1):112-113.
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  2. Joseph David Bessie (1991). Theories of Probabilistic Causality. Dissertation, University of Minnesota
    In this dissertation, a foundation is proposed for a coherent theory of non-deterministic causality. This entails the definition of events as spacetime-regions-in-states, and uses a partly formalized possible-worlds semantics for the definition of propensities , which are understood to be intrinsic tendencies of events to evolve as they do. The interpretation is inspired by a series of articles in the 1970s by Giere, and diverges from his work by simplifying and strengthening his characterization of propensities. The idea that propensities are (...)
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  3. Gunnar Björnsson (2007). How Effects Depend on Their Causes, Why Causal Transitivity Fails, and Why We Care About Causation. Philosophical Studies 133 (3):349-390.
    Despite recent efforts to improve on counterfactual theories of causation, failures to explain how effects depend on their causes are still manifest in a variety of cases. In particular, theories that do a decent job explaining cases of causal preemption have problems accounting for cases of causal intransitivity. Moreover, the increasing complexity of the counterfactual accounts makes it difficult to see why the concept of causation would be such a central part of our cognition. In this paper, I propose an (...)
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  4. Richard N. Burnor (1993). Rethinking Objective Homogeneity: Statistical Versus Ontic Approaches. Philosophical Studies 71 (3):307 - 325.
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  5. Esteban Céspedes (2011). Book Review: M. Suárez, Probabilities, Causes and Propensities in Physics. [REVIEW] Physics and Philosophy 2011.
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  6. L. Jonathan Cohen (1992). Probabilistic Causality. Philosophical Books 33 (2):86-88.
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  7. Wayne A. Davis & Ellery Eells (1993). Probabilistic Causality. Philosophical Review 102 (3):410.
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  8. A. P. Dawid (2007). Counterfactuals, Hypotheticals and Potential Responses: A Philosophical Examination of Statistical Causality. In Federica Russo & Jon Williamson (eds.), Causality and Probability in the Sciences. pp. 503--532.
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  9. Phil Dowe (1993). On the Reduction of Process Causality to Statistical Relations. British Journal for the Philosophy of Science 44 (2):325-327.
  10. John Dupre (1990). Probabilistic Causality: A Rejoinder to Ellery Eells. Philosophy of Science 57 (4):690 - 698.
    In an earlier paper (Dupré 1984), I criticized a thesis sometimes defended by theorists of probabilistic causality, namely, that a probabilistic cause must raise the probability of its effect in every possible set of causally relevant background conditions (the "contextual unanimity thesis"). I also suggested that a more promising analysis of probabilistic causality might be sought in terms of statistical relevance in a fair sample. Ellery Eells (1987) has defended the contextual unanimity thesis against my objections, and also raised objections (...)
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  11. John Dupré (1984). Probabilistic Causality Emancipated. Midwest Studies in Philosophy 9 (1):169-175.
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  12. Frederick Eberhardt (2013). Experimental Indistinguishability of Causal Structures. Philosophy of Science 80 (5):684-696.
    Using a variety of different results from the literature, I show how causal discovery with experiments is limited unless substantive assumptions about the underlying causal structure are made. These results undermine the view that experiments, such as randomized controlled trials, can independently provide a gold standard for causal discovery. Moreover, I present a concrete example in which causal underdetermination persists despite exhaustive experimentation and argue that such cases undermine the appeal of an interventionist account of causation as its dependence on (...)
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  13. Dorothy Edgington (1997). Mellor on Chance and Causation. [REVIEW] British Journal for the Philosophy of Science 48 (3):411-433.
    Mellor's subject is singular causation between facts, expressed ‘E because C’. His central requirement for causation is that the chance that E if C be greater than the chance that E if C: chc(E)>chc(E). The book is as much about chance as it is about causation. I show that his way of distinguishing chc (E) from the traditional notion of conditional chance leaves than him with a problem about the existence of chQ(P) when Q is false (Section 3); and also (...)
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  14. Ellery Eells (1991). Probabilistic Causality. Cambridge University Press.
    In this important book, Ellery Eells explores and refines philosophical conceptions of probabilistic causality. In a probabilistic theory of causation, causes increase the probability of their effects rather than necessitate their effects in the ways traditional deterministic theories have specified. Philosophical interest in this subject arises from attempts to understand population sciences as well as indeterminism in physics. Taking into account issues involving spurious correlation, probabilistic causal interaction, disjunctive causal factors, and temporal ideas, Professor Eells advances the analysis of what (...)
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  15. Ellery Eells (1987). Cartwright and Otte on Simpson's Paradox. Philosophy of Science 54 (2):233-243.
    Richard Otte (1985) has recently criticized the resolution of Simpson's paradox given by Nancy Cartwright (1979). He argues that there are difficulties with the version of the theory of probabilistic causality that Cartwright has developed, and that there is a way in which Simpson's paradox can arise that Cartwright's theory cannot handle. And Otte develops his own theory of probabilistic causality. I defend Cartwright's solution, and I argue that there are difficulties with the theory of probabilistic causality that Otte proposes.
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  16. Ellery Eells (1987). Probabilistic Causality: Reply to John Dupré. Philosophy of Science 54 (1):105-114.
    John Dupré (1984) has recently criticized the theory of probabilistic causality developed by, among others, Good (1961-62), Suppes (1970), Cartwright (1979), and Skyrms (1980). He argues that there is a tension or incompatibility between one of its central requirements for the presence of a causal connection, on the one hand, and a feature of the theory pointed out by Elliott Sober and me (1983), on the other. He also argues that the requirement just alluded to should be given up. I (...)
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  17. Ellery Eells & Elliott Sober (1983). Probabilistic Causality and the Question of Transitivity. Philosophy of Science 50 (1):35-57.
    After clarifying the probabilistic conception of causality suggested by Good (1961-2), Suppes (1970), Cartwright (1979), and Skyrms (1980), we prove a sufficient condition for transitivity of causal chains. The bearing of these considerations on the units of selection problem in evolutionary theory and on the Newcomb paradox in decision theory is then discussed.
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  18. James H. Fetzer & Donald E. Nute (1981). A Probabilistic Causal Calculus: Conflicting Conceptions. Synthese 48 (3):241 - 246.
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  19. James H. Fetzer & Donald E. Nute (1980). A Probabilistic Causal Calculus: Conflicting Conceptions. Synthese 44 (2):241 - 246.
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  20. James H. Fetzer & Wesley C. Salmon (1988). Probability and Causality Essays in Honor of Wesley C. Salmon.
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  21. Alexander Gebharter (2017). Causal Nets, Interventionism, and Mechanisms. Cham: Springer.
    This monograph looks at causal nets from a philosophical point of view. The author shows that one can build a general philosophical theory of causation on the basis of the causal nets framework that can be fruitfully used to shed new light on philosophical issues. Coverage includes both a theoretical as well as application-oriented approach to the subject. The author first counters David Hume’s challenge about whether causation is something ontologically real. The idea behind this is that good metaphysical concepts (...)
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  22. Alexander Gebharter & Gerhard Schurz (2014). How Occam's Razor Provides a Neat Definition of Direct Causation. In J. M. Mooij, D. Janzing, J. Peters, T. Claassen & A. Hyttinen (eds.), Proceedings of the UAI Workshop Causal Inference: Learning and Prediction. CEUR-WS. pp. 1-10.
    In this paper we show that the application of Occam’s razor to the theory of causal Bayes nets gives us a neat definition of direct causation. In particular we show that Occam’s razor implies Woodward’s (2003) definition of direct causation, provided suitable intervention variables exist and the causal Markov condition (CMC) is satisfied. We also show how Occam’s razor can account for direct causal relationships Woodward style when only stochastic intervention variables are available.
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  23. Mansure Ghabdian (2011). Ellery Eells on Probabilistic Causation. Philosophical Investigations 7 (19):157-182.
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  24. Bruce Glymour (2003). On the Metaphysics of Probabilistic Causation: Lessons From Social Epidemiology. Philosophy of Science 70 (5):1413-1423.
    I argue that the orthodox account of probabilistic causation, on which probabilistic causes determine the probability of their effects, is inconsistent with certain ontological assumptions implicit in scientific practice. In particular, scientists recognize the possibility that properties of populations can cause the behavior of members of the populations. Such emergent population‐level causation is metaphysically impossible on the orthodoxy.
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  25. Luke Glynn (2011). A Probabilistic Analysis of Causation. British Journal for the Philosophy of Science 62 (2):343-392.
    The starting point in the development of probabilistic analyses of token causation has usually been the naïve intuition that, in some relevant sense, a cause raises the probability of its effect. But there are well-known examples both of non-probability-raising causation and of probability-raising non-causation. Sophisticated extant probabilistic analyses treat many such cases correctly, but only at the cost of excluding the possibilities of direct non-probability-raising causation, failures of causal transitivity, action-at-a-distance, prevention, and causation by absence and omission. I show that (...)
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  26. I. J. Good (1980). Some Comments on Probabilistic Causality. Pacific Philosophical Quarterly 61 (3):301.
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  27. Christopher Hitchcock (1996). A Probabilistic Theory of Second Order Causation. Erkenntnis 44 (3):369 - 377.
    Larry Wright and others have advanced causal accounts of functional explanation, designed to alleviate fears about the legitimacy of such explanations. These analyses take functional explanations to describe second order causal relations. These second order relations are conceptually puzzling. I present an account of second order causation from within the framework of Eells' probabilistic theory of causation; the account makes use of the population-relativity of causation that is built into this theory.
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  28. Christopher Read Hitchcock (1995). The Mishap at Reichenbach Fall: Singular Vs. General Causation. Philosophical Studies 78 (3):257 - 291.
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  29. Christopher Read Hitchcock (1993). A Generalized Probabilistic Theory of Causal Relevance. Synthese 97 (3):335 - 364.
    I advance a new theory of causal relevance, according to which causal claims convey information about conditional probability functions. This theory is motivated by the problem of disjunctive factors, which haunts existing probabilistic theories of causation. After some introductory remarks, I present in Section 3 a sketch of Eells's (1991) probabilistic theory of causation, which provides the framework for much of the discussion. Section 4 explains how the problem of disjunctive factors arises within this framework. After rejecting three proposed solutions, (...)
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  30. Douglas Kutach (2014). Causation. Polity.
    In most academic and non-academic circles throughout history, the world and its operation have been viewed in terms of cause and effect. The principles of causation have been applied, fruitfully, across the sciences, law, medicine, and in everyday life, despite the lack of any agreed-upon framework for understanding what causation ultimately amounts to. In this engaging and accessible introduction to the topic, Douglas Kutach explains and analyses the most prominent theories and examples in the philosophy of causation. The book is (...)
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  31. Adam Morton (1980). Would Cause. Proceedings of the Aristotelian Society 81:139 - 151.
    I discuss 'cause' embedded in the consequent of a counterfactual: if e1 then e2 would cause e3. I argue that surprising as it may seem this idea is in some respects easier to understand than simple 'e1 caused e2'.
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  32. Robert Northcott (2010). Natural-Born Determinists: A New Defense of Causation as Probability-Raising. Philosophical Studies 150 (1):1-20.
    A definition of causation as probability-raising is threatened by two kinds of counterexample: first, when a cause lowers the probability of its effect; and second, when the probability of an effect is raised by a non-cause. In this paper, I present an account that deals successfully with problem cases of both these kinds. In doing so, I also explore some novel implications of incorporating into the metaphysical investigation considerations of causal psychology.
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  33. Stefan Nowak (1960). Some Problems of Causal Interpretation of Statistical Relationships. Philosophy of Science 27 (1):23-38.
    In following paper an attempt will be made to analyse the statistical relationships between variables as the functions of causal relations existing between them. Our basic assumption here is that statistical relationships between traits, events, or characteristics of objects, may be logically derived from the pattern of their mutual causal connections, if this pattern is described by appropriate concepts and with sufficient precision. The first part of the paper presents basic concepts, which according to author's view may serve for the (...)
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  34. Wesley Salmon (1984). Scientific Explanation and the Causal Structure of the World. Princeton University Press.
    The philosophical theory of scientific explanation proposed here involves a radically new treatment of causality that accords with the pervasively statistical character of contemporary science. Wesley C. Salmon describes three fundamental conceptions of scientific explanation--the epistemic, modal, and ontic. He argues that the prevailing view is untenable and that the modal conception is scientifically out-dated. Significantly revising aspects of his earlier work, he defends a causal/mechanical theory that is a version of the ontic conception. Professor Salmon's theory furnishes a robust (...)
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  35. Jonathan Schaffer (2007). Review of Dowe and Noordhof: Cause and Chance: Causation in an Indeterministic World. [REVIEW] British Journal for the Philosophy of Science 58 (4):869-874.
    This is an excellent anthology. The contributors are first-rate, the contributions are state-of-the-art, and the content is highly unified. The introduction further connects the essays and succinctly articulates the main themes. What results will be of interest to anyone interested in the contemporary discussion of causation.
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  36. Jonathan Schaffer (2000). Overlappings: Probability-Raising Without Causation. Australasian Journal of Philosophy 78 (1):40 – 46.
    The leading regularity, counterfactual, and agential accounts of causation converge on the idea that causation is probability-raising. While the necessity of probability-raising for causation remains in dispute, the sufficiency of probability-raising for causation is generally assumed, at least in the direct (no intermediaries involved) and precisely described case. I offer a class of counterexamples: overlappings.
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  37. Gerhard Schurz & Alexander Gebharter (2016). Causality as a Theoretical Concept: Explanatory Warrant and Empirical Content of the Theory of Causal Nets. Synthese 193 (4):1073-1103.
    We start this paper by arguing that causality should, in analogy with force in Newtonian physics, be understood as a theoretical concept that is not explicated by a single definition, but by the axioms of a theory. Such an understanding of causality implicitly underlies the well-known theory of causal nets and has been explicitly promoted by Glymour. In this paper we investigate the explanatory warrant and empirical content of TCN. We sketch how the assumption of directed cause–effect relations can be (...)
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  38. Patrick Suppes (1970). A Probabilistic Theory of Causality. Amsterdam: North-Holland Pub. Co..
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  39. László E. Szabó (2008). The Einstein--Podolsky--Rosen Argument and the Bell Inequalities. Internet Encyclopedia of Philosophy.
    In 1935, Einstein, Podolsky, and Rosen (EPR) published an important paper in which they claimed that the whole formalism of quantum mechanics together with what they called a “Reality Criterion” imply that quantum mechanics cannot be complete. That is, there must exist some elements of reality that are not described by quantum mechanics. They concluded that there must be a more complete description of physical reality involving some hidden variables that can characterize the state of affairs in the world in (...)
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  40. Michael Tooley (2004). Probability and Causation. In Phil Dowe & Paul Noordhof (eds.), Cause and Chance: Causation in an Indeterministic World. Routledge.
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  41. Charles R. Twardy & Kevin B. Korb (2011). Actual Causation by Probabilistic Active Paths. Philosophy of Science 78 (5):900-913.
    We present a probabilistic extension to active path analyses of token causation (Halpern & Pearl 2001, forthcoming; Hitchcock 2001). The extension uses the generalized notion of intervention presented in (Korb et al. 2004): we allow an intervention to set any probability distribution over the intervention variables, not just a single value. The resulting account can handle a wide range of examples. We do not claim the account is complete --- only that it fills an obvious gap in previous active-path approaches. (...)
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  42. Brad Weslake (2006). Common Causes and the Direction of Causation. Minds and Machines 16 (3):239-257.
    Is the common cause principle merely one of a set of useful heuristics for discovering causal relations, or is it rather a piece of heavy duty metaphysics, capable of grounding the direction of causation itself? Since the principle was introduced in Reichenbach’s groundbreaking work The Direction of Time (1956), there have been a series of attempts to pursue the latter program—to take the probabilistic relationships constitutive of the principle of the common cause and use them to ground the direction of (...)
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  43. James Woodward (2003). Making Things Happen: A Theory of Causal Explanation. Oxford University Press.
    Woodward's long awaited book is an attempt to construct a comprehensive account of causation explanation that applies to a wide variety of causal and explanatory claims in different areas of science and everyday life. The book engages some of the relevant literature from other disciplines, as Woodward weaves together examples, counterexamples, criticisms, defenses, objections, and replies into a convincing defense of the core of his theory, which is that we can analyze causation by appeal to the notion of manipulation.
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