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Summary Scoring rules play an important role in statistics, decision theory, and formal epistemology.  They underpin techniques for eliciting a person's credences in statistics.  And they have been exploited in epistemology to give arguments for various norms that are thought to govern credences, such as Probabilism, Conditionalization, the Reflection Principle, the Principal Principle, and Principles of Indifference, as well as accounts of peer disagreement and the Sleeping Beauty puzzle. A scoring rule is a function that assigns a penalty to an agent's credence (or partial belief or degree of belief) in a given proposition.  The penalty depends on whether the proposition is true or false.  Typically, if the proposition is true then the penalty increases as the credence decreases (the less confident you are in a true proposition, the more you will be penalised); and if the proposition is false then the penalty increases as the credence increases (the more confident you are in a false proposition, the more you will be penalised). In statistics and the theory of eliciting credences, we usually interpret the penalty assigned to a credence by a scoring rule as the monetary loss incurred by an agent with that credence.  In epistemology, we sometimes interpret it as the so-called 'gradational inaccuracy' of the agent's credence:  just as a full belief in a true proposition is more accurate than a full disbelief in that proposition, a higher credence in a true proposition is more accurate than a lower one; and just as a full disbelief in a false proposition is more accurate than a full belief, a lower credence in a false proposition is more accurate than a higher one.  Sometimes, in epistemology, we interpret the penalty given by a scoring rule more generally:  we take it to be the loss in so-called 'cognitive utility' incurred by an agent with that credence, where this is intended to incorporate a measure of the accuracy of the credence, but also measures of all other doxastic virtues it might have as well. Scoring rules assign losses or penalties to individual credences.  But we can use them to define loss or penalty functions for credence functions as well.  The loss assigned to a credence function is just the sum of the losses assigned to the individual credences it gives.  Using this, we can argue for such doxastic norms as Probabilism, Conditionalization, the Principal Principle, the Principle of Indifference, the Reflection Principle, norms for resolving peer disagreement, norms for responding to higher-order evidence, and so on.  For instance, for a large collection of scoring rules, the following holds:  If a credence function violates Probabilism, then there is a credence function that satisfies Probabilism that incurs a lower penalty regardless of how the world turns out.  That is, any non-probabilistic credence function is dominated by a probabilistic one.  Also, for the same large collection of scoring rules, the following holds:  If one's current credence function is a probability function, one will expect updating by conditionalization to incur a lower penalty than updating by any other rule.  There is a substantial and growing body of work on how scoring rules can be used to establish other doxastic norms.
Key works Leonard Savage (Savage 1971) and Bruno de Finetti (de Finetti 1970) introduced the notion of a scoring rule independently.  The notion was introduced into epistemology by Jim Joyce (Joyce 1998) and Graham Oddie (Oddie 1997).  Joyce used it to justify Probabilism; Oddie used it to justify Conditionalization.  Since then, authors have improved and generalized both arguments.  Improved arguments for Probabilism can be found in (Joyce 2009), (Leitgeb & Pettigrew 2010), (Leitgeb & Pettigrew 2010), (Predd et al 2009), (Schervish et al manuscript), (Pettigrew 2016).  Improved arguments for Conditionalization can be found in (Greaves & Wallace 2006), (Easwaran 2013), (Schoenfield 2017), (Pettigrew 2016).  Furthermore, other norms have been considered, such as the Principal Principle (Pettigrew 2012), (Pettigrew 2013), the Principle of Indifference (Pettigrew 2016), the Reflection Principle (Huttegger 2013), norms for resolving peer disagreement (Moss 2011), (Levinstein 2015), (Levinstein 2017), and norms for responding to higher-order evidence (Schoenfield 2018).
Introductions Pettigrew, Richard (2011) 'Epistemic Utility Arguments for Probabilism', Stanford Encyclopedia of Philosophy (Pettigrew 2011)
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  1. What is Justified Credence?Richard Pettigrew - 2021 - Episteme 18 (1):16-30.
    In this paper, we seek a reliabilist account of justified credence. Reliabilism about justified beliefs comes in two varieties: process reliabilism (Goldman, 1979, 2008) and indicator reliabilism (Alston, 1988, 2005). Existing accounts of reliabilism about justified credence comes in the same two varieties: Jeff Dunn (2015) proposes a version of process reliabilism, while Weng Hong Tang (2016) offers a version of indicator reliabilism. As we will see, both face the same objection. If they are right about what justification is, it (...)
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  2. Partial Belief, Full Belief, and Accuracy–Dominance.Branden Fitelson & Kenny Easwaran - manuscript
    Arguments for probabilism aim to undergird/motivate a synchronic probabilistic coherence norm for partial beliefs. Standard arguments for probabilism are all of the form: An agent S has a non-probabilistic partial belief function b iff (⇐⇒) S has some “bad” property B (in virtue of the fact that their p.b.f. b has a certain kind of formal property F). These arguments rest on Theorems (⇒) and Converse Theorems (⇐): b is non-Pr ⇐⇒ b has formal property F.
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  3. On Accuracy and Coherence with Infinite Opinion Sets.Mikayla Kelley - manuscript
    There is a well-known equivalence between avoiding accuracy dominance and having probabilistically coherent credences (see, e.g., de Finetti 1974, Joyce 2009, Predd et al. 2009, Schervish et al. 2009, Pettigrew 2016). However, this equivalence has been established only when the set of propositions on which credence functions are defined is finite. In this paper, we establish connections between accuracy dominance and coherence when credence functions are defined on an infinite set of propositions. In particular, we establish the necessary results to (...)
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  4. Self-Locating Belief and the Goal of Accuracy.Richard Pettigrew - manuscript
    The goal of a partial belief is to be accurate, or close to the truth. By appealing to this norm, I seek norms for partial beliefs in self-locating and non-self-locating propositions. My aim is to find norms that are analogous to the Bayesian norms, which, I argue, only apply unproblematically to partial beliefs in non-self-locating propositions. I argue that the goal of a set of partial beliefs is to minimize the expected inaccuracy of those beliefs. However, in the self-locating framework, (...)
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  5. Epistemic Risk and the Demands of Rationality.Richard Pettigrew - manuscript
    The short abstract: Epistemic utility theory + permissivism about attitudes to epistemic risk => permissivism about rational credences. The longer abstract: I argue that epistemic rationality is permissive. More specifically, I argue for two claims. First, a radical version of interpersonal permissivism about rational credence: for many bodies of evidence, there is a wide range of credal states for which there is some individual who might rationally adopt that state in response to that evidence. Second, a slightly less radical version (...)
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  6. On the Pragmatic and Epistemic Virtues of Inference to the Best Explanation.Richard Pettigrew - manuscript
    In a series of papers over the past twenty years, and in a new book, Igor Douven has argued that Bayesians are too quick to reject versions of inference to the best explanation or abduction that cannot be accommodated within their framework. In this paper, I survey Douven’s worries and bring to bear a series of pragmatic and purely epistemic arguments to show that Bayes’ Rule really is the only correct way to respond to your evidence.
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  7. A Non-Pragmatic Dominance Argument for Conditionalization.Robert Williams - manuscript
    In this paper, I provide an accuracy-based argument for conditionalization (via reflection) that does not rely on norms of maximizing expected accuracy. -/- (This is a draft of a paper that I wrote in 2013. It stalled for no very good reason. I still believe the content is right).
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  8. The Foundations of Epistemic Decision Theory.Jason Konek & Ben Levinstein - 2017
    According to accuracy-first epistemology, accuracy is the fundamental epistemic good. Epistemic norms — Probabilism, Conditionalization, the Principal Principle, etc. — have their binding force in virtue of helping to secure this good. To make this idea precise, accuracy-firsters invoke Epistemic Decision Theory (EpDT) to determine which epistemic policies are the best means toward the end of accuracy. Hilary Greaves and others have recently challenged the tenability of this programme. Their arguments purport to show that EpDT encourages obviously epistemically irrational behavior. (...)
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  9. An Accuracy‐Dominance Argument for Conditionalization.R. A. Briggs & Richard Pettigrew - forthcoming - Noûs.
  10. Dilating and Contracting Arbitrarily.David Builes, Sophie Horowitz & Miriam Schoenfield - forthcoming - Noûs.
    Standard accuracy-based approaches to imprecise credences have the consequence that it is rational to move between precise and imprecise credences arbitrarily, without gaining any new evidence. Building on the Educated Guessing Framework of Horowitz (2019), we develop an alternative accuracy-based approach to imprecise credences that does not have this shortcoming. We argue that it is always irrational to move from a precise state to an imprecise state arbitrarily, however it can be rational to move from an imprecise state to a (...)
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  11. Accuracy Monism and Doxastic Dominance: Reply to Steinberger.Matt Hewson - forthcoming - Analysis.
    Given the standard dominance conditions used in accuracy theories for outright belief, epistemologists must invoke epistemic conservatism if they are to avoid licensing belief in both a proposition and its negation. Florian Steinberger (2019) charges the committed accuracy monist — the theorist who thinks that the only epistemic value is accuracy — with being unable to motivate this conservatism. I show that the accuracy monist can avoid Steinberger’s charge by moving to a subtly different set of dominance conditions. Having done (...)
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  12. Epistemic Conservativity and Imprecise Credence.Jason Konek - forthcoming - Philosophy and Phenomenological Research.
    Unspecific evidence calls for imprecise credence. My aim is to vindicate this thought. First, I will pin down what it is that makes one's imprecise credences more or less epistemically valuable. Then I will use this account of epistemic value to delineate a class of reasonable epistemic scoring rules for imprecise credences. Finally, I will show that if we plump for one of these scoring rules as our measure of epistemic value or utility, then a popular family of decision rules (...)
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  13. Can All-Accuracy Accounts Justify Evidential Norms?Christopher J. G. Meacham - forthcoming - In Kristoffer Ahlstrom-Vij & Jeff Dunn (eds.), Epistemic Consequentialism. Oxford University Press.
    Some of the most interesting recent work in formal epistemology has focused on developing accuracy-based approaches to justifying Bayesian norms. These approaches are interesting not only because they offer new ways to justify these norms, but because they potentially offer a way to justify all of these norms by appeal to a single, attractive epistemic goal: having accurate beliefs. Recently, Easwaran & Fitelson (2012) have raised worries regarding whether such “all-accuracy” or “purely alethic” approaches can accommodate and justify evidential Bayesian (...)
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  14. Accuracy-Dominance and Conditionalization.Michael Nielsen - forthcoming - Philosophical Studies:1-20.
    Epistemic decision theory produces arguments with both normative and mathematical premises. I begin by arguing that philosophers should care about whether the mathematical premises (1) are true, (2) are strong, and (3) admit simple proofs. I then discuss a theorem that Briggs and Pettigrew (2020) use as a premise in a novel accuracy-dominance argument for conditionalization. I argue that the theorem and its proof can be improved in a number of ways. First, I present a counterexample that shows that one (...)
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  15. Bayesian Updating When What You Learn Might Be False.Richard Pettigrew - forthcoming - Erkenntnis:1-16.
    Michael Rescorla (2020) has recently pointed out that the standard arguments for Bayesian Conditionalization assume that whenever you take yourself to learn something with certainty, it's true. Most people would reject this assumption. In response, Rescorla offers an improved Dutch Book argument for Bayesian Conditionalization that does not make this assumption. My purpose in this paper is two-fold. First, I want to illuminate Rescorla's new argument by giving a very general Dutch Book argument that applies to many cases of updating (...)
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  16. Accuracy-First Epistemology Without Additivity.Richard Pettigrew - forthcoming - Philosophy of Science.
    Accuracy arguments for the core tenets of Bayesian epistemology differ mainly in the conditions they place on the legitimate ways of measuring the inaccuracy of our credences. The best existing arguments rely on three conditions: Continuity, Additivity, and Strict Propriety. In this paper, I show how to strengthen the arguments based on these conditions by showing that the central mathematical theorem on which each depends goes through without assuming Additivity.
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  17. XIII—Dutch Book and Accuracy Theorems.Anna Mahtani - 2021 - Proceedings of the Aristotelian Society 120 (3):309-327.
    Dutch book and accuracy arguments are used to justify certain rationality constraints on credence functions. Underlying these Dutch book and accuracy arguments are associated theorems, and I show that the interpretation of these theorems can vary along a range of dimensions. Given that the theorems can be interpreted in a variety of different ways, what is the status of the associated arguments? I consider three possibilities: we could aggregate the results of the differently interpreted theorems in some way, and motivate (...)
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  18. Accuracy and Credal Imprecision.Dominik Berger & Nilanjan Das - 2020 - Noûs 54 (3):666-703.
    Many have claimed that epistemic rationality sometimes requires us to have imprecise credal states (i.e. credal states representable only by sets of credence functions) rather than precise ones (i.e. credal states representable by single credence functions). Some writers have recently argued that this claim conflicts with accuracy-centered epistemology, i.e., the project of justifying epistemic norms by appealing solely to the overall accuracy of the doxastic states they recommend. But these arguments are far from decisive. In this essay, we prove some (...)
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  19. Time-Slice Rationality and Self-Locating Belief.David Builes - 2020 - Philosophical Studies 177 (10):3033-3049.
    The epistemology of self-locating belief concerns itself with how rational agents ought to respond to certain kinds of indexical information. I argue that those who endorse the thesis of Time-Slice Rationality ought to endorse a particular view about the epistemology of self-locating belief, according to which ‘essentially indexical’ information is never evidentially relevant to non-indexical matters. I close by offering some independent motivations for endorsing Time-Slice Rationality in the context of the epistemology of self-locating belief.
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  20. On the Accuracy of Group Credences.Richard Pettigrew - 2020 - Oxford Studies in Epistemology 6.
    to appear in Szabó Gendler, T. & J. Hawthorne (eds.) Oxford Studies in Epistemology volume 6 We often ask for the opinion of a group of individuals. How strongly does the scientific community believe that the rate at which sea levels are rising increased over the last 200 years? How likely does the UK Treasury think it is that there will be a recession if the country leaves the European Union? What are these group credences that such questions request? And (...)
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  21. What is conditionalization, and why should we do it?Richard Pettigrew - 2020 - Philosophical Studies 177 (11):3427-3463.
    Conditionalization is one of the central norms of Bayesian epistemology. But there are a number of competing formulations, and a number of arguments that purport to establish it. In this paper, I explore which formulations of the norm are supported by which arguments. In their standard formulations, each of the arguments I consider here depends on the same assumption, which I call Deterministic Updating. I will investigate whether it is possible to amend these arguments so that they no longer depend (...)
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  22. An Accuracy Argument in Favor of Ranking Theory.Eric Raidl & Wolfgang Spohn - 2020 - Journal of Philosophical Logic 49 (2):283-313.
    Fitelson and McCarthy have proposed an accuracy measure for confidence orders which favors probability measures and Dempster-Shafer belief functions as accounts of degrees of belief and excludes ranking functions. Their accuracy measure only penalizes mistakes in confidence comparisons. We propose an alternative accuracy measure that also rewards correct confidence comparisons. Thus we conform to both of William James’ maxims: “Believe truth! Shun error!” We combine the two maxims, penalties and rewards, into one criterion that we call prioritized accuracy optimization. That (...)
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  23. The Uniqueness of Local Proper Scoring Rules: The Logarithmic Family.Jingni Yang - 2020 - Theory and Decision 88 (2):315-322.
    Local proper scoring rules provide convenient tools for measuring subjective probabilities. Savage, 783–801, 1971) has shown that the only local proper scoring rule for more than two exclusive events is the logarithmic family. We generalize Savage by relaxing the properness and the domain, and provide simpler proof.
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  24. A Theory of Epistemic Risk.Boris Babic - 2019 - Philosophy of Science 86 (3):522-550.
    I propose a general alethic theory of epistemic risk according to which the riskiness of an agent’s credence function encodes her relative sensitivity to different types of graded error. After motivating and mathematically developing this approach, I show that the epistemic risk function is a scaled reflection of expected inaccuracy. This duality between risk and information enables us to explore the relationship between attitudes to epistemic risk, the choice of scoring rules in epistemic utility theory, and the selection of priors (...)
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  25. Accuracy and Ur-Prior Conditionalization.Nilanjan Das - 2019 - Review of Symbolic Logic 12 (1):62-96.
    Recently, several epistemologists have defended an attractive principle of epistemic rationality, which we shall call Ur-Prior Conditionalization. In this essay, I ask whether we can justify this principle by appealing to the epistemic goal of accuracy. I argue that any such accuracy-based argument will be in tension with Evidence Externalism, i.e., the view that agent's evidence may entail non-trivial propositions about the external world. This is because any such argument will crucially require the assumption that, independently of all empirical evidence, (...)
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  26. Lockeans Maximize Expected Accuracy.Kevin Dorst - 2019 - Mind 128 (509):175-211.
    The Lockean Thesis says that you must believe p iff you’re sufficiently confident of it. On some versions, the 'must' asserts a metaphysical connection; on others, it asserts a normative one. On some versions, 'sufficiently confident' refers to a fixed threshold of credence; on others, it varies with proposition and context. Claim: the Lockean Thesis follows from epistemic utility theory—the view that rational requirements are constrained by the norm to promote accuracy. Different versions of this theory generate different versions of (...)
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  27. Accuracy and the Imps.James M. Joyce & Brian Weatherson - 2019 - Logos and Episteme 10 (3):263-282.
    Recently several authors have argued that accuracy-first epistemology ends up licensing problematic epistemic bribes. They charge that it is better, given the accuracy-first approach, to deliberately form one false belief if this will lead to forming many other true beliefs. We argue that this is not a consequence of the accuracy-first view. If one forms one false belief and a number of other true beliefs, then one is committed to many other false propositions, e.g., the conjunction of that false belief (...)
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  28. IP Scoring Rules: Foundations and Applications.Jason Konek - 2019 - Proceedings of Machine Learning Research 103:256-264.
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  29. In Favor of Logarithmic Scoring.Randall G. McCutcheon - 2019 - Philosophy of Science 86 (2):286-303.
    Shuford, Albert and Massengill proved, a half century ago, that the logarithmic scoring rule is the only proper measure of inaccuracy determined by a differentiable function of probability assigned the actual cell of a scored partition. In spite of this, the log rule has gained less traction in applied disciplines and among formal epistemologists that one might expect. In this paper we show that the differentiability criterion in the Shuford et. al. result is unnecessary and use the resulting simplified characterization (...)
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  30. What Accuracy Could Not Be.Graham Oddie - 2019 - British Journal for the Philosophy of Science 70 (2):551-580.
    Two different programmes are in the business of explicating accuracy—the truthlikeness programme and the epistemic utility programme. Both assume that truth is the goal of inquiry, and that among inquiries that fall short of realizing the goal some get closer to it than others. Truthlikeness theorists have been searching for an account of the accuracy of propositions. Epistemic utility theorists have been searching for an account of the accuracy of credal states. Both assume we can make cognitive progress in an (...)
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  31. On the Accuracy of Group Credences.Richard Pettigrew - 2019 - Oxford Studies in Epistemology 6.
    We often ask for the opinion of a group of individuals. How strongly does the scientific community believe that the rate at which sea levels are rising has increased over the last 200 years? How likely does the UK Treasury think it is that there will be a recession if the country leaves the European Union? What are these group credences that such questions request? And how do they relate to the individual credences assigned by the members of the particular (...)
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  32. Repugnant Accuracy.Brian Talbot - 2019 - Noûs 53 (3):540-563.
    Accuracy‐first epistemology is an approach to formal epistemology which takes accuracy to be a measure of epistemic utility and attempts to vindicate norms of epistemic rationality by showing how conformity with them is beneficial. If accuracy‐first epistemology can actually vindicate any epistemic norms, it must adopt a plausible account of epistemic value. Any such account must avoid the epistemic version of Derek Parfit's “repugnant conclusion.” I argue that the only plausible way of doing so is to say that accurate credences (...)
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  33. Lying, Accuracy and Credence.Matthew A. Benton - 2018 - Analysis 78 (2):195-198.
    Traditional definitions of lying require that a speaker believe that what she asserts is false. Sam Fox Krauss seeks to jettison the traditional belief requirement in favour of a necessary condition given in a credence-accuracy framework, on which the liar expects to impose the risk of increased inaccuracy on the hearer. He argues that this necessary condition importantly captures nearby cases as lies which the traditional view neglects. I argue, however, that Krauss's own account suffers from an identical drawback of (...)
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  34. Ideal Counterpart Theorizing and the Accuracy Argument for Probabilism.Clinton Castro & Olav Vassend - 2018 - Analysis 78 (2):207-216.
    One of the main goals of Bayesian epistemology is to justify the rational norms credence functions ought to obey. Accuracy arguments attempt to justify these norms from the assumption that the source of value for credences relevant to their epistemic status is their accuracy. This assumption and some standard decision-theoretic principles are used to argue for norms like Probabilism, the thesis that an agent’s credence function is rational only if it obeys the probability axioms. We introduce an example that shows (...)
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  35. Disagreement, Credences, and Outright Belief.Michele Palmira - 2018 - Ratio 31 (2):179-196.
    This paper addresses a largely neglected question in ongoing debates over disagreement: what is the relation, if any, between disagreements involving credences and disagreements involving outright beliefs? The first part of the paper offers some desiderata for an adequate account of credal and full disagreement. The second part of the paper argues that both phenomena can be subsumed under a schematic definition which goes as follows: A and B disagree if and only if the accuracy conditions of A's doxastic attitude (...)
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  36. Précis of Accuracy and the Laws of Credence.Richard Pettigrew - 2018 - Philosophy and Phenomenological Research 96 (3):749-754.
  37. The Population Ethics of Belief: In Search of an Epistemic Theory X.Richard Pettigrew - 2018 - Noûs 52 (2):336-372.
    Consider Phoebe and Daphne. Phoebe has credences in 1 million propositions. Daphne, on the other hand, has credences in all of these propositions, but she's also got credences in 999 million other propositions. Phoebe's credences are all very accurate. Each of Daphne's credences, in contrast, are not very accurate at all; each is a little more accurate than it is inaccurate, but not by much. Whose doxastic state is better, Phoebe's or Daphne's? It is clear that this question is analogous (...)
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  38. Information and Inaccuracy.William Roche & Tomoji Shogenji - 2018 - British Journal for the Philosophy of Science 69 (2):577-604.
    This article proposes a new interpretation of mutual information. We examine three extant interpretations of MI by reduction in doubt, by reduction in uncertainty, and by divergence. We argue that the first two are inconsistent with the epistemic value of information assumed in many applications of MI: the greater is the amount of information we acquire, the better is our epistemic position, other things being equal. The third interpretation is consistent with EVI, but it is faced with the problem of (...)
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  39. An Accuracy Based Approach to Higher Order Evidence.Miriam Schoenfield - 2018 - Philosophy and Phenomenological Research 96 (3):690-715.
    The aim of this paper is to apply the accuracy based approach to epistemology to the case of higher order evidence: evidence that bears on the rationality of one's beliefs. I proceed in two stages. First, I show that the accuracy based framework that is standardly used to motivate rational requirements supports steadfastness—a position according to which higher order evidence should have no impact on one's doxastic attitudes towards first order propositions. The argument for this will require a generalization of (...)
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  40. Accuracy and Epistemic Conservatism.Florian Steinberger - 2018 - Analysis:any094.
    Epistemic utility theory (EUT) is generally coupled with \emph{veritism}. Veritism is the view that truth is the sole fundamental epistemic value. Veritism, when paired with EUT, entails a methodological commitment: Norms of epistemic rationality are justified only if they can be derived from considerations of accuracy alone. According to EUT, then, believing truly has epistemic value, while believing falsely has epistemic disvalue. This raises the question as to how the rational believer should balance the prospect of true belief against the (...)
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  41. Accuracy Uncomposed: Against Calibrationism.Ben Levinstein - 2017 - Episteme 14 (1):59-69.
    Pettigrew offers new axiomatic constraints on legitimate measures of inaccuracy. His axiom called ‘Decomposition’ stipulates that legitimate measures of inaccuracy evaluate a credence function in part based on its level of calibration at a world. I argue that if calibration is valuable, as Pettigrew claims, then this fact is an explanandum for accuracy-rst epistemologists, not an explanans, for three reasons. First, the intuitive case for the importance of calibration isn’t as strong as Pettigrew believes. Second, calibration is a perniciously global (...)
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  42. Permissive Rationality and Sensitivity.Benjamin Anders Levinstein - 2017 - Philosophy and Phenomenological Research 94 (2):342-370.
    Permissivism about rationality is the view that there is sometimes more than one rational response to a given body of evidence. In this paper I discuss the relationship between permissivism, deference to rationality, and peer disagreement. I begin by arguing that—contrary to popular opinion—permissivism supports at least a moderate version of conciliationism. I then formulate a worry for permissivism. I show that, given a plausible principle of rational deference, permissive rationality seems to become unstable and to collapse into unique rationality. (...)
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  43. A Pragmatist’s Guide to Epistemic Utility.Benjamin Anders Levinstein - 2017 - Philosophy of Science 84 (4):613-638.
    We use a theorem from M. J. Schervish to explore the relationship between accuracy and practical success. If an agent is pragmatically rational, she will quantify the expected loss of her credence with a strictly proper scoring rule. Which scoring rule is right for her will depend on the sorts of decisions she expects to face. We relate this pragmatic conception of inaccuracy to the purely epistemic one popular among epistemic utility theorists.
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  44. The Accuracy and Rationality of Imprecise Credences.Miriam Schoenfield - 2017 - Noûs 51 (4):667-685.
    It has been claimed that, in response to certain kinds of evidence, agents ought to adopt imprecise credences: doxastic states that are represented by sets of credence functions rather than single ones. In this paper I argue that, given some plausible constraints on accuracy measures, accuracy-centered epistemologists must reject the requirement to adopt imprecise credences. I then show that even the claim that imprecise credences are permitted is problematic for accuracy-centered epistemology. It follows that if imprecise credal states are permitted (...)
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  45. Conditionalization Does Not Maximize Expected Accuracy.Miriam Schoenfield - 2017 - Mind 126 (504):1155-1187.
    Greaves and Wallace argue that conditionalization maximizes expected accuracy. In this paper I show that their result only applies to a restricted range of cases. I then show that the update procedure that maximizes expected accuracy in general is one in which, upon learning P, we conditionalize, not on P, but on the proposition that we learned P. After proving this result, I provide further generalizations and show that much of the accuracy-first epistemology program is committed to KK-like iteration principles (...)
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  46. Accuracy for Believers.Julia Staffel - 2017 - Episteme 14 (1):39-48.
    In Accuracy and the Laws of Credence Richard Pettigrew assumes a particular view of belief, which states that people don't have any other doxastic states besides credences. This is in tension with the popular position that people have both credences and outright beliefs. Pettigrew claims that such a dual view of belief is incompatible with the accuracy-first approach. I argue in this paper that it is not. This is good news for Pettigrew, since it broadens the appeal of his framework.
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  47. On the Preference for More Specific Reference Classes.Paul Thorn - 2017 - Synthese 194 (6):2025-2051.
    In attempting to form rational personal probabilities by direct inference, it is usually assumed that one should prefer frequency information concerning more specific reference classes. While the preceding assumption is intuitively plausible, little energy has been expended in explaining why it should be accepted. In the present article, I address this omission by showing that, among the principled policies that may be used in setting one’s personal probabilities, the policy of making direct inferences with a preference for frequency information for (...)
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  48. Direct Inference From Imprecise Frequencies.Paul D. Thorn - 2017 - In Michela Massimi, Jan-Willem Romeijn & Gerhard Schurz (eds.), EPSA15 Selected Papers: The 5th conference of the European Philosophy of Science Association in Düsseldorf. Springer. pp. 347-358.
    It is well known that there are, at least, two sorts of cases where one should not prefer a direct inference based on a narrower reference class, in particular: cases where the narrower reference class is gerrymandered, and cases where one lacks an evidential basis for forming a precise-valued frequency judgment for the narrower reference class. I here propose (1) that the preceding exceptions exhaust the circumstances where one should not prefer direct inference based on a narrower reference class, and (...)
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  49. The Brier Rule Is Not a Good Measure of Epistemic Utility.Don Fallis & Peter J. Lewis - 2016 - Australasian Journal of Philosophy 94 (3):576-590.
    Measures of epistemic utility are used by formal epistemologists to make determinations of epistemic betterness among cognitive states. The Brier rule is the most popular choice among formal epistemologists for such a measure. In this paper, however, we show that the Brier rule is sometimes seriously wrong about whether one cognitive state is epistemically better than another. In particular, there are cases where an agent gets evidence that definitively eliminates a false hypothesis, but where the Brier rule says that things (...)
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  50. In Search of Good Probability Assessors: An Experimental Comparison of Elicitation Rules for Confidence Judgments.Guillaume Hollard, Sébastien Massoni & Jean-Christophe Vergnaud - 2016 - Theory and Decision 80 (3):363-387.
    In this paper, we use an experimental design to compare the performance of elicitation rules for subjective beliefs. Contrary to previous works in which elicited beliefs are compared to an objective benchmark, we consider a purely subjective belief framework. The performance of different elicitation rules is assessed according to the accuracy of stated beliefs in predicting success. We measure this accuracy using two main factors: calibration and discrimination. For each of them, we propose two statistical indexes and we compare the (...)
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