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Profile: "Jim", "James" "James M." Joyce (University of Michigan, Ann Arbor)
  1. Alan Hájek & James M. Joyce, Confirmation.
    I.1. Introduction Confirmation theory is intended to codify the evidential bearing of observations on hypotheses, characterizing relations of inductive “support” and “counter­support” in full generality. The central task is to understand what it means to say that datum E confirms or supports a hypothesis H when E does not logically entail H.
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  2. James M. Joyce (2012). Regret and Instability in Causal Decision Theory. Synthese 187 (1):123-145.
    Andy Egan has recently produced a set of alleged counterexamples to causal decision theory (CDT) in which agents are forced to decide among causally unratifiable options, thereby making choices they know they will regret. I show that, far from being counterexamples, CDT gets Egan's cases exactly right. Egan thinks otherwise because he has misapplied CDT by requiring agents to make binding choices before they have processed all available information about the causal consequences of their acts. I elucidate CDT in a (...)
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  3. James M. Joyce (2010). A Defense of Imprecise Credences in Inference and Decision Making1. Philosophical Perspectives 24 (1):281-323.
  4. James M. Joyce (2010). Causal Reasoning and Backtracking. Philosophical Studies 147 (1):139 - 154.
    I argue that one central aspect of the epistemology of causation, the use of causes as evidence for their effects, is largely independent of the metaphysics of causation. In particular, I use the formalism of Bayesian causal graphs to factor the incremental evidential impact of a cause for its effect into a direct cause-to-effect component and a backtracking component. While the “backtracking” evidence that causes provide about earlier events often obscures things, once we our restrict attention to the cause-to-effect component (...)
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  5. James M. Joyce (2007). Epistemic Deference: The Case of Chance. Proceedings of the Aristotelian Society 107 (2):187 - 206.
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  6. James M. Joyce (2007). Are Newcomb Problems Really Decisions? Synthese 156 (3):537 - 562.
    Richard Jeffrey long held that decision theory should be formulated without recourse to explicitly causal notions. Newcomb problems stand out as putative counterexamples to this ‘evidential’ decision theory. Jeffrey initially sought to defuse Newcomb problems via recourse to the doctrine of ratificationism, but later came to see this as problematic. We will see that Jeffrey’s worries about ratificationism were not compelling, but that valid ratificationist arguments implicitly presuppose causal decision theory. In later work, Jeffrey argued that Newcomb problems are not (...)
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  7. James M. Joyce (2007). ``Epistemic Deference: The Case of Chance&Quot. Proceedings of the Aristotelian Society 107 (1pt2):187-206.
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  8. James M. Joyce (2007). Meeting of the Aristotelian Society Held at Senate House, University of London, on 5 March 2007 at 4: 15 Pm. Proceedings of the Aristotelian Society 107 (Part 2):187.
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  9. James M. Joyce (2005). How Probabilities Reflect Evidence. Philosophical Perspectives 19 (1):153–178.
  10. James M. Joyce (2004). The Development of Subjective Bayesianism. In Dov M. Gabbay, John Woods & Akihiro Kanamori (eds.), Handbook of the History of Logic. Elsevier. 10--415.
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  11. James M. Joyce (2003). Paul Weirich, Decision Space: Multidimensional Decision Analysis:Decision Space: Multidimensional Decision Analysis. Ethics 113 (4):914-919.
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  12. James M. Joyce (2002). Levi on Causal Decision Theory and the Possibility of Predicting One's Own Actions. Philosophical Studies 110 (1):69 - 102.
    Isaac Levi has long criticized causal decisiontheory on the grounds that it requiresdeliberating agents to make predictions abouttheir own actions. A rational agent cannot, heclaims, see herself as free to choose an actwhile simultaneously making a prediction abouther likelihood of performing it. Levi is wrongon both points. First, nothing in causaldecision theory forces agents to makepredictions about their own acts. Second,Levi's arguments for the ``deliberation crowdsout prediction thesis'' rely on a flawed modelof the measurement of belief. Moreover, theability of agents (...)
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  13. James M. Joyce (2000). Why We Still Need the Logic of Decision. Philosophy of Science 67 (3):13.
    In The Logic of Decision Richard Jeffrey defends a version of expected utility theory that advises agents to choose acts with an eye to securing evidence for thinking that desirable results will ensue. Proponents of "causal" decision theory have argued that Jeffrey's account is inadequate because it fails to properly discriminate the causal features of acts from their merely evidential properties. Jeffrey's approach has also been criticized on the grounds that it makes it impossible to extract a unique probability/utility representation (...)
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  14. James M. Joyce (1998). A Nonpragmatic Vindication of Probabilism. Philosophy of Science 65 (4):575-603.
    The pragmatic character of the Dutch book argument makes it unsuitable as an "epistemic" justification for the fundamental probabilist dogma that rational partial beliefs must conform to the axioms of probability. To secure an appropriately epistemic justification for this conclusion, one must explain what it means for a system of partial beliefs to accurately represent the state of the world, and then show that partial beliefs that violate the laws of probability are invariably less accurate than they could be otherwise. (...)
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