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  1. Wesley C. Salmon., Scientific Explanation and the Causal Structure of the World.Robert John Ackermann - 1989 - International Studies in Philosophy 21 (1):112-113.
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  2. Theories of Probabilistic Causality.Joseph David Bessie - 1991 - 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. How Effects Depend on Their Causes, Why Causal Transitivity Fails, and Why We Care About Causation.Gunnar Björnsson - 2007 - 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. Rethinking Objective Homogeneity: Statistical Versus Ontic Approaches.Richard N. Burnor - 1993 - Philosophical Studies 71 (3):307 - 325.
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  5. Book Review: M. Suárez, Probabilities, Causes and Propensities in Physics. [REVIEW]Esteban Céspedes - 2011 - Physics and Philosophy 2011.
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  6. Probabilistic Causality.L. Jonathan Cohen - 1992 - Philosophical Books 33 (2):86-88.
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  7. Probabilistic Causality.Wayne A. Davis & Ellery Eells - 1993 - Philosophical Review 102 (3):410.
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  8. Counterfactuals, Hypotheticals and Potential Responses: A Philosophical Examination of Statistical Causality.A. P. Dawid - 2007 - In Federica Russo & Jon Williamson (eds.), Causality and Probability in the Sciences. pp. 503--532.
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  9. On the Reduction of Process Causality to Statistical Relations.Phil Dowe - 1993 - British Journal for the Philosophy of Science 44 (2):325-327.
  10. Probabilistic Causality: A Rejoinder to Ellery Eells.John Dupre - 1990 - 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. Probabilistic Causality Emancipated.John Dupré - 1984 - Midwest Studies in Philosophy 9 (1):169-175.
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  12. Experimental Indistinguishability of Causal Structures.Frederick Eberhardt - 2013 - 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. Mellor on Chance and Causation. [REVIEW]Dorothy Edgington - 1997 - 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. Review: Cartwright on Probabilistic Causality: Types, Tokens, and Capacities. [REVIEW]Ellery Eells - 1995 - Philosophy and Phenomenological Research 55 (1):169 - 175.
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  15. Cartwright on Probabilistic Causality. [REVIEW]Ellery Eells - 1995 - Philosophy and Phenomenological Research 55 (1):169-175.
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  16. Probabilistic Causality.Ellery Eells - 1991 - 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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  17. Probabilistic Causality: Reply to John Dupré.Ellery Eells - 1987 - 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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  18. Cartwright and Otte on Simpson's Paradox.Ellery Eells - 1987 - 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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  19. Probabilistic Causality and the Question of Transitivity.Ellery Eells & Elliott Sober - 1983 - 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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  20. Correlation, Partial Correlation, and Causation.Frederick S. Ellett & David P. Ericson - 1986 - Synthese 67 (2):157-173.
    Philosophers and scientists have maintained that causation, correlation, and partial correlation are essentially related. These views give rise to various rules of causal inference. This essay considers the claims of several philosophers and social scientists for causal systems with dichotomous variables. In section 2 important commonalities and differences are explicated among four major conceptions of correlation. In section 3 it is argued that whether correlation can serve as a measure of A's causal influence on B depends upon the conception of (...)
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  21. A Probabilistic Causal Calculus: Conflicting Conceptions.James H. Fetzer & Donald E. Nute - 1981 - Synthese 48 (3):241 - 246.
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  22. A Probabilistic Causal Calculus: Conflicting Conceptions.James H. Fetzer & Donald E. Nute - 1980 - Synthese 44 (2):241 - 246.
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  23. Probability and Causality Essays in Honor of Wesley C. Salmon.James H. Fetzer & Wesley C. Salmon - 1988
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  24. Causal Nets, Interventionism, and Mechanisms.Alexander Gebharter - 2017 - 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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  25. How Occam's Razor Provides a Neat Definition of Direct Causation.Alexander Gebharter & Gerhard Schurz - 2014 - 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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  26. Ellery Eells on Probabilistic Causation.Mansure Ghabdian - 2011 - Philosophical Investigations 7 (19):157-182.
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  27. On the Metaphysics of Probabilistic Causation: Lessons From Social Epidemiology.Bruce Glymour - 2003 - 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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  28. A Probabilistic Analysis of Causation.Luke Glynn - 2011 - 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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  29. A Further Note on Probabilistic Causality: Mending the Chain.I. J. Good - 1980 - Pacific Philosophical Quarterly 61 (4):452.
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  30. Some Comments on Probabilistic Causality.I. J. Good - 1980 - Pacific Philosophical Quarterly 61 (3):301.
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  31. Causal Priority at the Singular Level: Fork Asymmetry-Based Accounts Meet the Generalization Strategy.Linda Leanne Habeeb - 1998 - Dissertation, City University of New York
    I dissect one particular strategy for explaining causal priority: the fork asymmetry strategy. I argue that the best objections that have been raised are objections to versions which are less than optimal. I develop the strongest version of the principle and argue that this stronger version is fully equipped to explain causal priority at the type level. So far so good. But, I discover and attempt to deal with one remaining and perhaps insurmountable problem--Fork asymmetry accounts cannot explain causal priority (...)
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  32. Scientific Explanation and the Causal Structure of the World.Joseph F. Hanna - 1986 - Review of Metaphysics 39 (3):582-585.
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  33. Objective Homogeneity Relativized.Joseph F. Hanna - 1986 - PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1986:422 - 431.
    In his recent book Scientific Explanation and the Causal Structure of the World Wesley Salmon provides a detailed explanation of objective homogeneity, a concept which is central to his S-R model of explanation. 1 propose a modification of Salmon's definition which both simplifies and (in minor ways) corrects it, while at the same time generalizes it by including an important temporal factor that is missing from the original. I argue that if the world is irreducibly stochastic, then objective probabilities (determined (...)
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  34. Probabilistic Explanation and Probabilistic Causality.Joseph F. Hanna - 1982 - PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1982:181 - 193.
    This paper argues that if the world is irreducibly stochastic, then both Salmon's S-R model of explanation and Fetzer's C-R model of explanation have the following undesirable consequence: the objective probability (associated with the model's relevance condition) of any actual macro-event is either undefined or else, if defined, it equals one--so that the event is not even a candidate for a probabilistic explanation. This result follows from the temporal ambiguity of ontic probability in an irreducibly stochastic world. It is argued (...)
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  35. Partitions, Probabilistic Causal Laws, and Simpson's Paradox.Valerie Gray Hardcastle - 1991 - Synthese 86 (2):209 - 228.
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  36. Probabilistic Causality and Causal Generalizations.Daniel M. Hausman - 2010 - In Ellery Eells & James H. Fetzer (eds.), The Place of Probability in Science. Springer. pp. 47--63.
  37. Causal Asymmetries.Daniel M. Hausman - 1998 - Cambridge University Press.
    This book, by one of the pre-eminent philosophers of science writing today, offers the most comprehensive account available of causal asymmetries. Causation is asymmetrical in many different ways. Causes precede effects; explanations cite causes not effects. Agents use causes to manipulate their effects; they don't use effects to manipulate their causes. Effects of a common cause are correlated; causes of a common effect are not. This book explains why a relationship that is asymmetrical in one of these regards is asymmetrical (...)
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  38. A Probabilistic Theory of Second Order Causation.Christopher Hitchcock - 1996 - 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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  39. The Mishap at Reichenbach Fall: Singular Vs. General Causation.Christopher Read Hitchcock - 1995 - Philosophical Studies 78 (3):257 - 291.
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  40. A Generalized Probabilistic Theory of Causal Relevance.Christopher Read Hitchcock - 1993 - 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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  41. Probabilistic Causation in Scientific Explanation.Christopher Read Hitchcock - 1993 - Dissertation, University of Pittsburgh
    Salmon has argued that science provides explanations by describing a causal nexus: For Salmon, this nexus is a network of processes and interactions. I argue that this picture of the causal nexus is insufficient for an account of scientific explanation: a taxonomy of causal relevance is also needed. ;Probabilistic theories of causation seem to provide such a taxonomy in their dichotomy between promoting and inhibiting causes. However, standard probabilistic theories are beset by a difficulty called the problem of disjunctive factors. (...)
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  42. Explanatory Relations Between the Direction of Causation and the Fork Asymmetry.Paul Horwich - 1993 - Analysis 53 (3):154 - 155.
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  43. Causal Modeling and the Statistical Analysis of Causation.Gurol Irzik - 1986 - PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1986:12 - 23.
    Recent philosophical studies of probabilistic causation and statistical explanation have opened up the possibility of unifying philosophical approaches with causal modeling as practiced in the social and biological sciences. This unification rests upon the statistical tools employed, the principle of common cause, the irreducibility of causation to statistics, and the idea of causal process as a suitable framework for understanding causal relationships. These four areas of contact are discussed with emphasis on the relevant aspects of causal modeling.
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  44. Probabilistic Causality: In Defense of the Unanimity Theory.Joonsung Kim - 2002 - Dissertation, The University of Wisconsin - Madison
    My dissertation defends the theory of probabilistic causation called "the unanimity theory" against three challenges, which I call "the metaphysical challenge", "the conceptual challenge" and "the methodological challenge". I argue that the unanimity theory meets these three challenges, and coheres with each of the three theories of probabilistic causation that have been naturally inspired by the three challenges. I conclude that the unanimity theory constitutes a foundation of the three theories, which in fact reveals the versatility of the unanimity theory. (...)
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  45. Causation.Douglas Kutach - 2014 - 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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  46. Would Cause.Adam Morton - 1980 - 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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  47. Natural-Born Deterministe: A New Defense of Causation as Probability-Raising.Robert Northcott - 2010 - 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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  48. Natural-Born Determinists: A New Defense of Causation as Probability-Raising.Robert Northcott - 2010 - 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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  49. Some Problems of Causal Interpretation of Statistical Relationships.Stefan Nowak - 1960 - 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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  50. Probability and Causality.Richard Edward Otte - 1982 - Dissertation, The University of Arizona
    Probability and Causality is a critical analysis of the problem of causality in indeterministic contexts. Most philosophers who have written about probabilistic causality feel that Hume's requirement of constant conjunction should be replaced by a requirement of positive statistical relevance. After arguing that a theory of probabilistic causality is necessary to account for many causal relations, Hume's theory of probabilistic causality is analyzed. Although Hume's theory is inadequate, it does form the basis for later discussions of probabilistic causality. ;The first (...)
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