Cover Accuracy and the Laws of Credence Copyright Contents Acknowledgements Introduction PART I: The accuracy argument for Probabilism 1: From No Drop to Probabilism 2: Formulating the dominance principle 2.1 From Dominance to Undominated Dominance 2.2 From Undominated Dominance to Immodest Dominance 2.3 From Immodest Dominance to Deontological Immodest Dominance 3: Measuring accuracy: existing accounts 3.1 Joyce on convexity 3.2 Leitgeb and Pettigrew on agreement and epistemicdilemmas 3.3 Joyce on coherent admissibility 4 Measuring accuracy: a new account. 4.1 Additive divergences4.2 Continuity and the absence of jumps 4.3 Calibration and accuracy 4.4 Symmetry 5: The Bronfman objection 5.1 Epistemicism 5.2 Supervaluationism 5.3 Subjectivism 6: Howson's robustness objection 7: The accuracy argument for Probabilism Appendix I: The mathematical results I.A Characterizing the probabilistic credence functions I.B Characterizing legitimate inaccuracy measures (without Symmetry) I.C Characterizing legitimate inaccuracy measures (with Symmetry) I.D Two theorems concerning additive Bregman divergences PART II: Chance-credence principles. 8: The Principal Principle9: Vindication and chance 9.1 Objections to Ur-Chance Initial Vindication 9.2 Introducing the Temporal Principal Principle 9.3 Beyond the initial credence function 9.4 An objection to Current Chance Evidential Vindication 10: Dominance and chance 10.1 Adapting the argument 10.2 The circularity objection 11: Self-undermining chances 11.1 Self-undermining chance functions 11.2 An accuracy-based argument for Ismael'sGeneral Recipe 11.3 An accuracy-based argument for the New Principle Appendix II: A summaryof chance-credence principles. Appendix III: The mathematical resultsIII. A Proof of Theorem III. A.2 III. B Proof of Theorem 11.1.1 III. C Proof of Theorem 11.2.1 III. D Proof of Theorem 11.2.2 PART III: The Principle of Indifference 12: Maximin and the Principleof Indifference 12.1 The Argument from Evidential Support 12.2 The Argument from Minimal Information 12.3 The Argument from Accuracy 12.4 Generalizing the argument 12.5 Epistemic risk aversion 12.6 Language dependence 13: Hurwicz, regret, and C-maximin 13.1 The Hurwicz criterion 13.2 Risking regret 13.3 Risk and chances. Appendix IV:The mathematical resultsIV. A Proof of Theorem 13.1.1 IV. A.1 Proof ofTheorem 13.1.1(I) IV. A.2 Proof ofTheorem 13.1.1(II) IV. B Proof ofTheorem 13.3.1 PART IV: Accuracy and updating 14: Plan Conditionalization 14.1 Forward-facing argument 14.2 Backwards-facing argument 14.3 Neither-facing argument 15: Diachronic Conditionalization 15.1 The argument from the prior standpoint 15.2 The argument from diachronic continence Appendix V: The mathematical results V.A Proof ofTheorem 14.1.1 V.C Proof ofTheorem 14.3.1 V.D Proof ofTheorem 15.1.1 V.F Proof ofTheorem 15.1.5.
SUMMARY OR ABSTRACT
Text of Note
Richard Pettigrew offers an extended investigation into a particular way of justifying the rational principles that govern our credences (or degrees of belief). He draws on decision theory in order to justify the central tenets of Bayesian epistemology, and sets out a veritistic account of epistemic utility.