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Interpretation of Probability

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  1. Marshall Abrams, Toward a Mechanistic Interpretation of Probability.
    I sketch a new objective interpretation of probability, called "mechanistic probability", and more specifically what I call "far-flung frequency (FFF) mechanistic probability". FFF mechanistic probability is defined in terms of facts about the causal structure of devices and certain sets of collections of frequencies in the actual world. The relevant kind of causal structure is a generalization of what Strevens (2003) calls microconstancy. Though defined partly in terms of frequencies, FFF mechanistic probability avoids many drawbacks of well-known frequency theories. It (...)
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  2. Lennart Åqvist (2007). An Interpretation of Probability in the Law of Evidence Based on Pro-Et-Contra Argumentation. Artificial Intelligence and Law 15 (4).
    The purpose of this paper is to improve on the logical and measure-theoretic foundations for the notion of probability in the law of evidence, which were given in my contributions Åqvist [ (1990) Logical analysis of epistemic modality: an explication of the Bolding–Ekelöf degrees of evidential strength. In: Klami HT (ed) Rätt och Sanning (Law and Truth. A symposium on legal proof-theory in Uppsala May 1989). Iustus Förlag, Uppsala, pp 43–54; (1992) Towards a logical theory of legal evidence: semantic analysis (...)
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  3. E. Beth (1946). On the Interpretation of Probability Calculi Ernest Nagel. Synthese 5 (1-2).
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  4. Craig Callender, The Emergence and Interpretation of Probability in Bohmian Mechanics.
    A persistent question about the deBroglie–Bohm interpretation of quantum mechanics concerns the understanding of Born’s rule in the theory. Where do the quantum mechanical probabilities come from? How are they to be interpreted? These are the problems of emergence and interpretation. In more than 50 years no consensus regarding the answers has been achieved. Indeed, mirroring the foundational disputes in statistical mechanics, the answers to each question are surprisingly diverse. This paper is an opinionated survey of this literature. While acknowledging (...)
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  5. Maria Carla Galavotti (1989). Anti-Realism in the Philosophy of Probability: Bruno De Finetti's Subjectivism. Erkenntnis 31 (2-3).
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  6. Donald Gillies (2000). Philosophical Theories of Probability. Routledge.
    This book presents a comprehensive and systematic account of the various philosophical theories of probability and explains how they are related. It covers the classical, logical, subjective, frequency, and propensity views of probability. Donald Gillies even provides a new theory of probability -the intersubjective-a development of the subjective theory. He argues for a pluralist view, where there can be more than one valid interpretation of probabiltiy, each appropriate in a different context. The relation of the various interpretations to the Bayesian (...)
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  7. Alan Hájek, Australasian Philosophy of Probability, and Probability in Australasian Philosophy.
    The philosophy of probability has been alive and well for several decades in Australia and New Zealand. Some distinctive lines of thought have emerged, resonating with broader themes that have come to be associated with Australasian philosophers: realist/objectivist accounts of various theoretical entities; an ongoing concern with logic, including the development of non­classical logics; and enthusiasm for conceptual analysis, rooted in commonsense but informed by science. In this article I concentrate on work by philosophers on the interpretation of probability, its (...)
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  8. Alan Hájek, Interpretations of Probability. Stanford Encyclopedia of Philosophy.
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  9. James Logue (1995). Projective Probability. Oxford University Press.
    This book presents a novel theory of probability applicable to general reasoning, science, and the courts. Based on a strongly subjective starting-point, with probabilities viewed simply as the guarded beliefs one can reasonably hold, the theory shows how such beliefs are legitimately "projected" outwards as if they existed in the world independent of our judgements.
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  10. Peter Milne (1986). Can There Be a Realist Single-Case Interpretation of Probability? Erkenntnis 25 (2).
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  11. Jan Plato (1982). The Significance of the Ergodic Decomposition of Stationary Measures for the Interpretation of Probability. Synthese 53 (3).
    De Finetti's representation theorem is a special case of the ergodic decomposition of stationary probability measures. The problems of the interpretation of probabilities centred around de Finetti's theorem are extended to this more general situation. The ergodic decomposition theorem has a physical background in the ergodic theory of dynamical systems. Thereby the interpretations of probabilities in the cases of de Finetti's theorem and its generalization and in ergodic theory are systematically connected to each other.
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  12. Federica Russo (2006). Salmon and Van Fraassen on the Existence of Unobservable Entities: A Matter of Interpretation of Probability. Foundations of Science 11 (3).
    A careful analysis of Salmon’s Theoretical Realism and van Fraassen’s Constructive Empiricism shows that both share a common origin: the requirement of literal construal of theories inherited by the Standard View. However, despite this common starting point, Salmon and van Fraassen strongly disagree on the existence of unobservable entities. I argue that their different ontological commitment towards the existence of unobservables traces back to their different views on the interpretation of probability via different conceptions of induction. In fact, inferences to (...)
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  13. Niall Shanks (1993). Time and the Propensity Interpretation of Probability. Journal for General Philosophy of Science 24 (2).
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  14. Lawrence Sklar (1970). Is Probability a Dispositional Property? Journal of Philosophy 67 (11):355-366.
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  15. Paul Weirich, Calibration.
    Abner Shimony (1988) argues that degrees of belief satisfy the axioms of probability because their epistemic goal is to match estimates of objective probabilities. Because the estimates obey the axioms of probability, degrees of belief must also obey them to reach their epistemic goal. This calibration argument meets some objections, but with a few revisions it can surmount those objections. It offers a good alternative to the Dutch book argument for compliance with the probability axioms. The defense of Shimony's calibration (...)
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Classical Probability
  1. Ernest W. Adams (1996). Four Probability-Preserving Properties of Inferences. Journal of Philosophical Logic 25 (1).
    Different inferences in probabilistic logics of conditionals preserve the probabilities of their premisses to different degrees. Some preserve certainty, some high probability, some positive probability, and some minimum probability. In the first case conclusions must have probability 1 when premisses have probability 1, though they might have probability 0 when their premisses have any lower probability. In the second case, roughly speaking, if premisses are highly probable though not certain then conclusions must also be highly probable. In the third case (...)
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  2. Leon Cohen (1966). Can Quantum Mechanics Be Formulated as a Classical Probability Theory? Philosophy of Science 33 (4):317-322.
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  3. G. Gerlich (1981). Some Remarks on Classical Probability Theory in Quantum Mechanics. Erkenntnis 16 (3).
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  4. Michal Marczyk & Leszek Wronski, Exhaustive Classication of Finite Classical Probability Spaces with Regard to the Notion of Causal Up-to-N-Closedness.
    Extending the ideas from (Hofer-Szabó and Rédei [2006]), we introduce the notion of causal up-to-n-closedness of probability spaces. A probability space is said to be causally up-to-n-closed with respect to a relation of independence R_ind iff for any pair of correlated events belonging to R_ind the space provides a common cause or a common cause system of size at most n. We prove that a finite classical probability space is causally up-to-3-closed w.r.t. the relation of logical independence iff its probability (...)
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  5. Joseph D. Sneed (1970). Quantum Mechanics and Classical Probability Theory. Synthese 21 (1).
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Frequentism
  1. Alan Hájek, Fifteen Arguments Against Hypothetical Frequentism.
    This is the sequel to my "Fifteen Arguments Against Finite Frequentism" (Erkenntnis 1997), the second half of a long paper that attacks the two main forms of frequentism about probability. Hypothetical frequentism asserts: The probability of an attribute A in a reference class B is p..
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  2. Noëul Bonneuil (2004). Repertoires, Frequentism, and Predictability. History and Theory 43 (1):117–123.
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  3. Bas C. Fraassen (1977). Relative Frequencies. Synthese 34 (2).
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  4. Alan Hájek (2009). Fifteen Arguments Against Hypothetical Frequentism. Erkenntnis 70 (2).
    This is the sequel to my “Fifteen Arguments Against Finite Frequentism” ( Erkenntnis 1997), the second half of a long paper that attacks the two main forms of frequentism about probability. Hypothetical frequentism asserts: The probability of an attribute A in a reference class B is p iff the limit of the relative frequency of A ’s among the B ’s would be p if there were an infinite sequence of B ’s. I offer fifteen arguments against this analysis. I (...)
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  5. Alan Hájek (1996). “Mises Redux” — Redux: Fifteen Arguments Against Finite Frequentism. Erkenntnis 45 (2-3):209--27.
    According to finite frequentism, the probability of an attribute A in a finite reference class B is the relative frequency of actual occurrences of A within B. I present fifteen arguments against this position.
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  6. Berna Kilinç (2000). Robert Leslie Ellis and John Stuart Mill on the One and the Many of Frequentism. British Journal for the History of Philosophy 8 (2):251 – 274.
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  7. Wesley C. Salmon (1977). Objectively Homogeneous Reference Classes. Synthese 36 (4).
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  8. Wesley C. Salmon (1965). What Happens in the Long Run? Philosophical Review 74 (3):373-378.
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  9. Wesley C. Salmon (1953). The Frequency Interpretation and Antecedent Probabilities. Philosophical Studies 4 (3).
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  10. Lawrence Sklar (1973). Unfair to Frequencies. Journal of Philosophy 70 (2):41-52.
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  11. Michael Strevens (1996). Quantum Mechanics and Frequentism: A Reply to Ismael. British Journal for the Philosophy of Science 47 (4):575-577.
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  12. Peter M. Williams (1992). Review Essay: A Theory of Logical Frequentism. Synthese 91 (3).
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Logical Probability
  1. J. Franklin (2001). Resurrecting Logical Probability. Erkenntnis 55 (2).
    The logical interpretation of probability, or ``objective Bayesianism''''– the theory that (some) probabilitiesare strictly logical degrees of partial implication – is defended.The main argument against it is that it requires the assignment ofprior probabilities, and that any attempt to determine them by symmetryvia a ``principle of insufficient reason'''' inevitably leads to paradox.Three replies are advanced: that priors are imprecise or of little weight, sothat disagreement about them does not matter, within limits; thatit is possible to distinguish reasonable from unreasonable priorson (...)
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  2. James Hawthorne (2005). Degree-of-Belief and Degree-of-Support: Why Bayesians Need Both Notions. Mind 114 (454):277-320.
    I argue that Bayesians need two distinct notions of probability. We need the usual degree-of-belief notion that is central to the Bayesian account of rational decision. But Bayesians also need a separate notion of probability that represents the degree to which evidence supports hypotheses. Although degree-of-belief is well suited to the theory of rational decision, Bayesians have tried to apply it to the realm of hypothesis confirmation as well. This double duty leads to the problem of old evidence, a problem (...)
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  3. C. Howson (1973). Must the Logical Probability of Laws Be Zero? British Journal for the Philosophy of Science 24 (2):153-163.
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  4. John Maynard Keynes (1921/2004). A Treatise on Probability. Dover Publications.
    With this treatise, an insightful exploration of the probabilistic connection between philosophy and the history of science, the famous economist breathed new life into studies of both disciplines. Originally published in 1921, this important mathematical work represented a significant contribution to the theory regarding the logical probability of propositions. Keynes effectively dismantled the classical theory of probability, launching what has since been termed the “logical-relationist” theory. In so doing, he explored the logical relationships between classifying a proposition as “highly probable” (...)
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  5. Isaac Levi (2010). Probability Logic, Logical Probability, and Inductive Support. Synthese 172 (1).
    This paper seeks to defend the following conclusions: The program advanced by Carnap and other necessarians for probability logic has little to recommend it except for one important point. Credal probability judgments ought to be adapted to changes in evidence or states of full belief in a principled manner in conformity with the inquirer’s confirmational commitments—except when the inquirer has good reason to modify his or her confirmational commitment. Probability logic ought to spell out the constraints on rationally coherent confirmational (...)
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  6. Halina Mortimer (1973). A Rule of Acceptance Based on Logical Probability. Synthese 26 (2).
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  7. Darrell P. Rowbottom (2008). On the Proximity of the Logical and 'Objective Bayesian' Interpretations of Probability. Erkenntnis 69 (3):335-349.
    In his Bayesian Nets and Causality, Jon Williamson presents an ‘Objective Bayesian’ interpretation of probability, which he endeavours to distance from the logical interpretation yet associate with the subjective interpretation. In doing so, he suggests that the logical interpretation suffers from severe epistemological problems that do not affect his alternative. In this paper, I present a challenge to his analysis. First, I closely examine the relationship between the logical and ‘Objective Bayesian’ views, and show how, and why, they are highly (...)
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  8. Hermann Vetter (1969). Logical Probability, Mathematical Statistics, and the Problem of Induction. Synthese 20 (1).
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Propensities
  1. Nuel Belnap, Propensities and Probabilities.
    Popper’s introduction of ‘‘propensity’’ was intended to provide a solid conceptual foundation for objective single-case probabilities. By considering the partly opposed contributions of Humphreys and Miller and Salmon, it is argued that when properly understood, propensities can in fact be understood as objective single-case causal probabilities of transitions between concrete events. The chief claim is that propensities are well-explicated by describing how they fit into the existing formal theory of branching space-times, which is simultaneously indeterministic and causal. Several problematic examples, (...)
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  2. Antony Eagle (2004). Twenty-One Arguments Against Propensity Analyses of Probability. Erkenntnis 60 (3):371–416.
    I argue that any broadly dispositional analysis of probability will either fail to give an adequate explication of probability, or else will fail to provide an explication that can be gainfully employed elsewhere (for instance, in empirical science or in the regulation of credence). The diversity and number of arguments suggests that there is little prospect of any successful analysis along these lines.
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  3. James H. Fetzer (2002). Propensities and Frequencies: Inference to the Best Explanation. Synthese 132 (1-2).
    An approach to inference to the best explanation integrating a Popperianconception of natural laws together with a modified Hempelian account of explanation, one the one hand, and Hacking's law of likelihood (in its nomicguise), on the other, which provides a robust abductivist model of sciencethat appears to overcome the obstacles that confront its inductivist,deductivist, and hypothetico-deductivist alternatives.This philosophy of scienceclarifies and illuminates some fundamental aspects of ontology and epistemology, especially concerning the relations between frequencies and propensities. Among the most important (...)
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  4. Ronald N. Giere (1976). A Laplacean Formal Semantics for Single-Case Propensities. Journal of Philosophical Logic 5 (3).
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  5. N. Gisin (1991). Propensities in a Non-Deterministic Physics. Synthese 89 (2).
    Propensities are presented as a generalization of classical determinism. They describe a physical reality intermediary between Laplacian determinism and pure randomness, such as in quantum mechanics. They are characterized by the fact that their values are determined by the collection of all actual properties. It is argued that they do not satisfy Kolmogorov axioms; other axioms are proposed.
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  6. J. W. Grove (1995). Karl Popper, in Search of a Better World: Lectures and Essays From Thirty Years. Routledge, London and New York, 1992. Pp. X, 245. £25.00. Karl Popper, a World of Propensities. Thoemmes, Bristol, 1990. Pp. IX, 51. £5.99 (Paper). John R. Wettersten, the Roots of Critical Rationalism. Rodopi, Amsterdam and Atlanta, Ga, 1992. Pp. 254. $68.97. Philosophy of the Social Sciences 25 (3).
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  7. Joseph F. Hanna (1981). Single Case Propensities and the Explanation of Particular Events. Synthese 48 (3).
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  8. Colin Howson (1984). Probabilities, Propensities, and Chances. Erkenntnis 21 (3).
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  9. Paul Humphreys (1985). Why Propensities Cannot Be Probabilities. Philosophical Review 94 (4):557-570.
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  10. Frank Jackson & Robert Pargetter (1982). Physical Probability as a Propensity. Noûs 16 (4):567-583.
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  11. Henry Krips (1984). Popper, Propensities, and Quantum Theory. British Journal for the Philosophy of Science 35 (3).
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  12. Review author[s]: Henry E. Kyberg (1974). Propensities and Probabilities. British Journal for the Philosophy of Science 25 (4):358-375.
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  13. Christopher S. I. Mccurdy (1996). Humphrey's Paradox and the Interpretation of Inverse Conditional Propensities. Synthese 108 (1).
    The aim of this paper is to distinguish between, and examine, three issues surrounding Humphreys's paradox and interpretation of conditional propensities. The first issue involves the controversy over the interpretation of inverse conditional propensities — conditional propensities in which the conditioned event occurs before the conditioning event. The second issue is the consistency of the dispositional nature of the propensity interpretation and the inversion theorems of the probability calculus, where an inversion theorem is any theorem of probability that makes explicit (...)
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  14. Roberta L. Millstein (2003). Interpretations of Probability in Evolutionary Theory. Philosophy of Science 70 (5):1317-1328.
    Evolutionary theory (ET) is teeming with probabilities. Probabilities exist at all levels: the level of mutation, the level of microevolution, and the level of macroevolution. This uncontroversial claim raises a number of contentious issues. For example, is the evolutionary process (as opposed to the theory) indeterministic, or is it deterministic? Philosophers of biology have taken different sides on this issue. Millstein (1997) has argued that we are not currently able answer this question, and that even scientific realists ought to remain (...)
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  15. Peter Milne (1985). A Note on Popper, Propensities, and the Two-Slit Experiment. British Journal for the Philosophy of Science 36 (1):66-70.
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  16. Alfred Nordmann (1990). Persistent Propensities: Portrait of a Familiar Controversy. Biology and Philosophy 5 (4).
    Susan Mills and John Beatty's propensity interpretation of fitness encountered very different philosophical criticisms by Alexander Rosenberg and Kenneth Waters. These criticisms and the rejoinders to them are both predictable and important. They are predictable as raisingkinds of issues typically associated with disposition concepts (this is established through a systematic review of the problems generated by Carnap's dispositional interpretation of all scientific terms). They are important as referring the resolution of these issues to the development of evolutionary biology. This historical (...)
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  17. Belnap Nuel (2007). Propensities and Probabilities. Studies in History and Philosophy of Science Part B.
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  18. Kelly Richmond Pope (2005). Measuring the Ethical Propensities of Accounting Students: Mach IV Versus DIT. Journal of Academic Ethics 3 (2-4).
    This study responds to Bay and Greenberg's (Bay, D.D. and Greenberg, R.R. (2001). The relationship of the DIT and behavior: A replication. Issues in Accounting Education 10(3): 367–380) call to investigate alternative psychometric instruments to measure ethical behavior other than the heavily relied upon Defining Issues Test. The Mach IV scale (Christie, 1970) has been cited in more than 500 published psychological studies; however, it has not been used extensively in the accounting ethics research. This study provides some preliminary evidence (...)
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  19. Karl R. Popper (1959). The Propensity Interpretation of Probability. British Journal for the Philosophy of Science 10 (37):25-42.
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  20. Huw Price (1984). Mellor, Chance and the Single Case. British Journal for the Philosophy of Science 35 (1):11-23.
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  21. Wesley C. Salmon (1990). Causal Propensities: Statistical Causality Vs. Aleatory Causality. Topoi 9 (2).
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  22. Wesley C. Salmon (1979). Propensities: A Discussion Review. Erkenntnis 14 (2).
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  23. Brian Skyrms (1977). Resiliency, Propensities, and Causal Necessity. Journal of Philosophy 74 (11):704-713.
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  24. Howard Smokler (1979). Single-Case Propensities, Modality, and Confirmation. Synthese 40 (3).
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  25. Henry P. Stapp (1991). Quantum Propensities and the Brain-Mind Connection. Foundations of Physics 21:1451-77.
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  26. Michael Strevens, Probability Out of Determinism.
    This paper offers a metaphysics of physical probability in (or if you prefer, truth conditions for probabilistic claims about) deterministic systems based on an approach to the explanation of probabilistic patterns in deterministic systems called the method of arbitrary functions. Much of the appeal of the method is its promise to provide an account of physical probability on which probability assignments have the ability to support counterfactuals about frequencies. It is argued that the eponymous arbitrary functions are of little philosophical (...)
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  27. Mauricio Suárez, Probabilities, Causes and Propensities in Physics (Synthese Library, Springer). Chapters 0 & 1 (Contents & Introduction).
    These are the introduction chapters to the forthcoming collection of essays published by Springer (Synthese Library) and entitled Probabilities, Causes and Propensities in Physics.
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  28. Mauricio Suárez, Quantum Propensities.
    This paper reviews four attempts throughout the history of quantum mechanics to explicitly employ dispositional notions in order to solve the quantum paradoxes, namely: Margenau’s latencies, Heisenberg’s potentialities, Maxwell’s propensitons, and the recent selective propensities interpretation of quantum mechanics. Difficulties and challenges are raised for all of them, and it is concluded that the selective propensities approach nicely encompasses the virtues of its predecessors. Finally, some strategies are discussed for reading dispositional notions into two other well-known interpretations of quantum mechanics, (...)
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  29. Mauricio Suárez (2004). On Quantum Propensities: Two Arguments Revisited. Erkenntnis 61 (1).
    Peter Milne and Neal Grossman have argued against Popper's propensity interpretation of quantum mechanics, by appeal to the two-slit experiment and to the distinction between mixtures and superpositions, respectively. In this paper I show that a different propensity interpretation successfully meets their objections. According to this interpretation, the possession of a quantum propensity by a quantum system is independent of the experimental set-ups designed to test it, even though its manifestations are not.
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  30. Mauricio Suárez (2004). Quantum Selections, Propensities and the Problem of Measurement. British Journal for the Philosophy of Science 55 (2).
    This paper expands on, and provides a qualified defence of, Arthur Fine's selective interactions solution to the measurement problem. Fine's approach must be understood against the background of the insolubility proof of the quantum measurement. I first defend the proof as an appropriate formal representation of the quantum measurement problem. The nature of selective interactions, and more generally selections, is then clarified, and three arguments in their favour are offered. First, selections provide the only known solution to the measurement problem (...)
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  31. Peter Urbach (1980). Social Propensities. British Journal for the Philosophy of Science 31 (4):317-328.
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  32. Ursula Wegener (1980). Sind Ludwigs Chancengewichtungen Propensities Im Sinne Poppers? Journal for General Philosophy of Science 11 (1).
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Interpretion of Probability, Misc
  1. David J. Chalmers, Probability and Propositions.
    What are the objects of belief? That is, what are the things we believe, when we believe that it is sunny outside and that Nietzsche is dead? Usually these things are taken to be propositions. But the nature of propositions is itself contested. What is a proposition, such that it can serve as an object of belief?
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  2. Benj Hellie, Jenann Ismael's 'Probability and Physics'.
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  3. Darrell Patrick Rowbottom (2008). Intersubjective Corroboration. Studies in History and Philosophy of Science Part A 39 (1):124-132.
    How are we to understand the use of probability in corroboration functions? Popper says logically, but does not show we could have access to, or even calculate, probability values in a logical sense. This makes the logical interpretation untenable, as Ramsey and van Fraassen have argued. If corroboration functions only make sense when the probabilities employed therein are subjective, however, then what counts as impressive evidence for a theory might be a matter of convention, or even whim. So isn’t so-called (...)
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