An adequate account of laws should satisfy at least five desiderata: it should provide a unified account of laws and chances, it should yield plausible relations between laws and chances, it should vindicate numerical chance assignments, it should accommodate dynamical and non-dynamical chances, and it should accommodate a plausible range of nomic possibilities. No extant account of laws satisfies these desiderata. This paper presents a non-Humean account of laws, the Nomic Likelihood Account, that does.

When can a shift from a prior to a posterior be represented by conditionalization? A well-known result, known as “superconditioning” and going back to work by Diaconis and Zabell, gives a sharp answer. This paper extends the result and connects it to the reflection principle and common priors. I show that a shift from a prior to a set of posteriors can be represented within a conditioning model if and only if the prior and the posteriors are connected via a (...) general form of the reflection principle. Common priors can be characterized by principles that require a certain kind of coherence between distinct sets of posteriors. I discuss the implications these results have for diachronic and synchronic modes of updating, learning experiences, the common prior assumption of game theory, and time-slice epistemology. (shrink)

Infallibilism leads to skepticism, and fallibilism is plagued by the threshold problem. Within this narrative, the pragmatic turn in epistemology has been marketed as a way for fallibilists to address the threshold problem. In contrast, pragmatic versions of infallibilism have been left unexplored. However, I propose that going pragmatic offers the infallibilist a way to address its main problem, the skeptical problem. Pragmatic infallibilism, however, is committed to a shifty view of epistemic certainty, where the strength of a subject’s epistemic (...) state can vary depending upon the practical context. Pragmatic views of epistemic strength are quite radical so the argumentative goal of my discussion is to argue for its plausibility, thereby arguing for the plausibility of pragmatic infallibilism. To do so, I discuss the role that the framing of decision problems and the construction of our deliberative attitudes have in our theories of rational choice. And I explore a way in which these necessary components of a normative theory of rationality can be used to motivate pragmatic views of evidential support. Finally, since the plausibility of our pragmatic account will depend upon the plausibility of a constructive account of rational choice, I conclude by comparing the adequacy of the constructive account with orthodox Bayesian and knowledge-based accounts. (shrink)

The present paper probes the relation between the metaphysics of human freedom and the Rothbardian branch of Austrian economics. It transpires that Rothbard and his followers embrace metaphysical libertarianism, which holds that free will is incompatible with determinism and that the thesis of determinism is false as pertaining to human action. However, as we demonstrate, their economics with its reliance on value scales requires for its tenability compatibilist freedom. Moreover, we attempt to show that the notion of value scales (or (...) preferences) postulated by them implies that value scales are determinative of choices people make. We contend that it is for this reason that the said Austrians should jettison their metaphysical libertarianism. (shrink)

This paper is about time preferences, the phenomenon that the very same things are usually considered the less valuable the farther in the future they are obtained. The utilities of those things are discounted at a certain rate. The paper presents a novel normative argument for exponential discount rates, whatever their empirical adequacy. It proposes to take indexical utility seriously, i.e. utilities referring to indexical propositions (that speak of ‘I’, ‘now’, etc.) as opposed to non-indexical propositions. Economic focus is only (...) on the latter, while the former are neglected. The potential ignorance of when is now generates a difference between indexical and non-indexical utility that can be exploited for a novel argument in favour of exponential discount rates. (shrink)

In previous work, I have suggested a doxastic account of perceptual experience according to which experiences form a kind of belief: Beliefs with what I have called “phenomenal” or “looks-content”. I have argued that this account can not only accommodate the intuitive reason providing role of experience, but also its justificatory role. I have also argued that, in general, construing experience and perceptual beliefs, i.e. the beliefs most directly based on experience, as having different contents best accounts for the defeasibility (...) of experiential reasons. In this paper, I shall have a closer look at the evidential or inferential relation between looks-propositions and the contents of perceptual beliefs and argue for a form of what I shall call “Pollockianism” about experiential reasons: such reasons are good unless defeated. Questions to be investigated include: Does the resulting picture of perceptual justification contain an externalist element? Is it compatible with Bayesianism? And how does it do with respect to problems that have been raised for other forms of Pollockianism such as dogmatism or phenomenal conservatism? (shrink)

The Principle of Indifference, which dictates that we ought to assign two outcomes equal probability in the absence of known reasons to do otherwise, is vulnerable to well-known objections. Nevertheless, the appeal of the principle, and of symmetry-based assignments of equal probability, persists. We show that, relative to a given class of symmetries satisfying certain properties, we are justified in calling certain outcomes equally probable, and more generally, in defining what we call relative probabilities. Relative probabilities are useful in providing (...) a generalized approach to conditionalization. The technique is illustrated by application to simple examples. (shrink)

How should we adjust our beliefs in light of the testimony of those who are in a better epistemic position than ourselves, such as experts and other epistemic superiors? In this paper, I develop and defend a deference model of epistemic authority. The paper attempts to resolve the debate between the preemption view and the total evidence view of epistemic authority by taking an accuracy-first approach to the issue of how we should respond to authoritative and expert testimony. I argue (...) that when we look at the debate through the lens of accuracy, it becomes clear that matters are more complicated than either the preemption view or the total evidence view are able to account for. Consequently, a deference model, outlined within a credence-based framework, does a better job of capturing the relevant phenomena, and explaining how we should update our beliefs in response to epistemically authoritative testimony. (shrink)

Advocates of Causal Decision Theory (CDT) argue that Evidential Decision Theory (EDT) is inadequate because it gives the wrong result in Newcomb problems. Egan (2007) provides a recipe for converting Newcomb problems to counterexamples to CDT, arguing that CDT is inadequate too. Proposed by Edgington (2011), the Conditional Causal Decision Theory (CCDT) is widely taken uncritically in the recent literature as a version of CDT that conforms to the supposedly correct pre-theoretic judgments about the rationality of acts in Newcomb problems (...) and Egan cases. While the renewed attention to the debate between EDT and CDT is mostly focused on how various theories treat Egan cases, this paper scrutinizes Edgington’s treatment of Newcomb problems and argues that, despite Edgington’s promise, CCDT actually fails in Newcomb problems. This, I assume, shows that CCDT is superior neither to the classic visions of CDT nor to EDT. The paper concludes by arguing, in general, that CCDT is systematically bound to deliver the same results as does EDT in any decision problem. Despite being formulated in terms of causal notions, therefore, it collapses back into the classic EDT. (shrink)

The classic formulation of causal decision theory (CDT) appeals to counterfactuals. It says that you should aim to choose an option that would have a good outcome, were you to choose it. However, this version of CDT faces trouble if the laws of nature are deterministic. After all, the standard theory of counterfactuals says that, if the laws are deterministic, then if anything—including the choice you make—were different in the present, either the laws would be violated or the distant past (...) would be changed. And as several authors have shown, it's easy to transform this upshot of the standard theory of counterfactuals into full-blown counterexamples to CDT. In response to these counterexamples, I argue here that the problem lies, not so much with CDT's guiding idea—that it's the expected causal consequences of your actions that matter for rational decision-making—but with the fact that the classic formulation of CDT doesn't pay sufficient attention to the context-sensitivity of counterfactuals. I develop a contextualist version of CDT which better accounts for this context-sensitivity. And I show that my theory avoids the problems faced by the classic formulation of CDT in determinstic worlds. (shrink)

In this essay, I analyze and critique Richard Jeffrey's radical probabilism. The basic theses defining it are examined, particularly the idea that probabilistic coherence involves a kind of "consistency." The main challenges to Jeffrey's view are (1) that there is an inconsistency between regarding probabilities as subjective and some probabilistic judgments as better than others, and (2) that decision theory so conceived has no normative import. I argue that both of these challenges can be met.

The representation theorems of expected utility theory show that having certain types of preferences is both necessary and sufficient for being representable as having subjective probabilities. However, unless the expected utility framework is simply assumed, such preferences are also consistent with being representable as having degrees of belief that do not obey the laws of probability. This fact shows that being representable as having subjective probabilities is not necessarily the same as having subjective probabilities. Probabilism can be defended on the (...) basis of the representation theorems only if attributions of degrees of belief are understood either antirealistically or purely qualitatively, or if the representation theorems are supplemented by arguments based on other considerations (simplicity, consilience, and so on) that single out the representation of a person as having subjective probabilities as the only true representation of the mental state of any person whose preferences conform to the axioms of expected utility theory. (shrink)

This paper has two main parts. In the first part, we motivate a kind of indeterminate, suppositional credences by discussing the prospect for a subjective interpretation of a causal Bayesian network, an important tool for causal reasoning in artificial intelligence. A CBN consists of a causal graph and a collection of interventional probabilities. The subjective interpretation in question would take the causal graph in a CBN to represent the causal structure that is believed by an agent, and interventional probabilities in (...) a CBN to represent suppositional credences. We review a difficulty noted in the literature with such an interpretation, and suggest that a natural way to address the challenge is to go for a generalization of CBN that allows indeterminate credences. In the second part, we develop a decision-theoretic foundation for such indeterminate suppositional credences, by generalizing a theory of coherent choice functions to accommodate some form of act-state dependence. The upshot is a decision-theoretic framework that is not only rich enough to, so to speak, ground the probabilities in a subjectively interpreted causal network, but also interesting in its own right, in that it accommodates both act-state dependence and imprecise probabilities. (shrink)

It’s difficult nowadays to write an interesting new book on vagueness, but Andrew Bacon has succeeded. He hasn’t done so by putting forth revolutionary views ab.

This article reveals one general scheme for creating counter examples to Bayesian confirmation theory. The reason of the problems is that: in daily life the degree of confirmation is affected not only by probability but also by some non-probabilistic factors, e.g., structural similarity, quantity of evidence, and marginal utility, while Bayesian confirmation theory considers only probabilities to measure the degree of confirmation. This article resolves these problems after some detail analyses, and proposes a new confirmation measure based on these factors.

In this paper, I motivate a puzzle about epistemic rationality. On the one hand, there seems to be something problematic about frequently changing your mind. On the other hand, changing your mind once is often permissible. Why do one-off changes of mind seem rationally permissible, even admirable, while constant changes seem quintessentially irrational? The puzzle of fickleness is to explain this asymmetry. To solve the puzzle, I propose and defend the Ratifiable Reasoning Account. According to this solution, as agents redeliberate, (...) they gain two types of evidence. First, they gain inductive evidence that they will not stably settle their belief. Second, this inductive evidence affords higher-order evidence that they are unreliable at assessing the matter at hand. The fact that fickle agents gain this higher-order evidence explains why fickleness can be epistemically—not just practically—irrational. In addition to solving the puzzle, my account captures a wide range of contextual factors that are relevant for our judgments. (shrink)

Revisionary theories of logic or truth require revisionary theories of mind. This essay outlines nonclassically based theories of rational belief, desire, and decision making, singling out the supervaluational family for special attention. To see these nonclassical theories of mind in action, this essay examines a debate between David Lewis and Derek Parfit over what matters in survival. Lewis argued that indeterminacy in personal identity allows caring about psychological connectedness and caring about personal identity to amount to the same thing. The (...) essay argues that Lewis's treatment of two of Parfit's puzzle cases—degreed survival and fission—presuppose different nonclassical treatments of belief and desire. (shrink)

It is argued that a subject's evidence consists of all and only the propositions that the subject knows.

A theory of evidential probability is developed from two assumptions:(1) the evidential probability of a proposition is its probability conditional on the total evidence;(2) one's total evidence is one's total knowledge. Evidential probability is distinguished from both subjective and objective probability. Loss as well as gain of evidence is permitted. Evidential probability is embedded within epistemic logic by means of possible worlds semantics for modal logic; this allows a natural theory of higher-order probability to be developed. In particular, it is (...) emphasized that it is sometimes uncertain which propositions are part of one's total evidence; some surprising implications of this fact are drawn out. (shrink)

At the centenary of Frank H. Knight’s Risk, Uncertainty, and Profit, we explore the continuing relevance of Knightian uncertainty to the theory and practice of entrepreneurship. There are three challenges facing such assessment. First, RUP is complex and difficult to interpret. The key but neglected element of RUP is that Knight’s account is not solely about risk and uncertainty as states of nature, but about how an agent’s beliefs about uncertain outcomes and confidence in those beliefs guide their choices. Second, (...) RUP is Knight’s only effort in this area. His subsequent career led elsewhere, so he did not engage with subsequent interpretations of this work. Third, much of the current literature emphasizes that decisions must be different under the two states of nature with a consequent misunderstanding of entrepreneurial agency. This paper addresses each challenge in sequence. First, we explicate Knight’s approach and explain why that approach is murky. Second, as a complement to Knight’s interpretation, we examine Frank P. Ramsey’s approach to subjective probabilities to help clarify Knight’s murky approach. What links Knight and Ramsey is a shared pragmatism about entrepreneurial agency under uncertainty that depends upon the beliefs about, and confidence in, their judgments of possible outcomes. This Knight-Ramsey approach does not require actor’s behaviors to be determined by the class of uncertain environment they face. We focus on the response by the entrepreneur to the existence of uncertainty in all its forms. We argue that this reductive account provides a foundation to examine common problems in management, including managerial hubris, the interaction between entrepreneurs and venture capitalists, and the need for experimentation in advance of new product and venture launches. Third, we critique current literature that favors epistemic purism about the ontology of risk and uncertainty and ignores Knight-Ramsey pragmatism in meeting uncertainty, such as using formal and informal institutions for uncertainty mitigation. Our account locates Frank Knight’s subtleties in entrepreneurial behavior firmly in the literature on entrepreneurial agency a century later. (shrink)

The 'Why ain'cha rich?' argument for one-boxing in Newcomb's problem allegedly vindicates evidential decision theory and undermines causal decision theory. But there is a good response to the argument on behalf of causal decision theory. I develop this response. Then I pose a new problem and use it to give a new 'Why ain'cha rich?' argument. Unlike the old argument, the new argument targets evidential decision theory. And unlike the old argument, the new argument is sound.

After defending the pluralistic approach to the interpretation of probability statements, I argue that the correctness of objective probability statements is not to be explained in terms of objective probabilities attached to propositions. Such an explanation will enable us to uphold an intuitively appealing connection between probability and action only in indeterministic contexts, whereas the objectivity of probability statements doesn’t depend on the truth of indeterminism. I show how objective probability statements can be interpreted without ascribing objective probabilities to propositions. (...) Finally, I draw a cautionary conclusion about the prospects for providing a probabilistic analysis of causation. (shrink)

Causal decision theory produces decision instability in cases such as Death in Damascus where a decision itself provides evidence concerning the utility of options. Several authors have proposed ways of handling this instability. William Harper (1985 and 1986) advances one of the most elegant proposals. He recommends maximizing causal expected utility among the options that are causally ratifiable. Unfortunately, Harper's proposal imposes certain restrictions; for instance, the restriction that mixed strategies are freely available. To obtain a completely general method of (...) handling decision instability, I step outside the confines of pure causal decision theory. I introduce a new kind of backtracking expected utility and propose maximizing it among the options that are causally ratifiable. In other words, I propose a hierarchical maximization of (1) conditional causal expected utility and (2) the new backtracking expected utility. I support this proposal with some intuitive considerations concerning the distinction between optimality and conditional optimality. And I prove that the proposal yields a solution in every finite decision problem. (shrink)

Fallibilism is an attractive epistemological position, avoiding the Scylla of rationalism, and the Charybdis of scepticism. Acknowledging, on the one hand, human imperfection, yet claiming that science and rational inquiry are possible. Fallibilism is a thesis, but equally importantly – an epistemological recommendation. that we should never be absolutely sure of anything. My aim in this paper is to drive a wedge between the thesis and the recommendation. The (eminently plausible) doctrine, I shall argue, cannot be used to ground the (...) epistemological prescription for caution. (shrink)

The expected utility of an option for a decision maker is defined with respect to probability and utility functions that represent the decision maker’s beliefs and desires. Therefore, as the decision maker’s beliefs and desires change, the expected utility of an opinion may change. Some options are such that their realizations change beliefs and desires in ways that change the expected utilities of the options. If a decision is made among options that include one or more of these special options, (...) I call it a decision made in a dynamic setting.The rule to maximize expected utility, MEU, is insufficient for decisions in dynamic settings. It does not say how to take account of information about the way in which the realization of an option would change the expected utility of the option. (shrink)

The conditional probability of h given e is commonly claimed to be equal to the probability that h would have if e were learned. Here I contend that this general claim about conditional probabilities is false. I present a counter-example that involves probabilities of probabilities, a second that involves probabilities of possible future actions, and a third that involves probabilities of indicative conditionals. In addition, I briefly defend these counter-examples against charges that the probabilities they involve are illegitimate.

Suppose that it is rational to choose or intend a course of action if and only if the course of action maximizes some sort of expectation of some sort of value. What sort of value should this definition appeal to? According to an influential neo-Humean view, the answer is “Utility”, where utility is defined as a measure of subjective preference. According to a rival neo-Aristotelian view, the answer is “Choiceworthiness”, where choiceworthiness is an irreducibly normative notion of a course of (...) action that is good in a certain way. The neo-Humean view requires preferences to be measurable by means of a utility function. Various interpretations of what exactly a “preference” is are explored, to see if there is any interpretation that supports the claim that a rational agent’s “preferences” must satisfy the “axioms” that are necessary for them to be measurable in this way. It is argued that the only interpretation that supports the idea that the rational agent’s preferences must meet these axioms interprets “preferences” as a kind of value-judgment. But this turns out to be version of the neo-Aristotelian view, rather than the neo-Humean view. Rational intentions maximize expected choiceworthiness, not expected utility. (shrink)

Why do people who disagree about one subject tend to disagree about other subjects as well? In this paper, we introduce a model to explore this phenomenon of ‘epistemic factionization’. Agents attempt to discover the truth about multiple propositions by testing the world and sharing evidence gathered. But agents tend to mistrust evidence shared by those who do not hold similar beliefs. This mistrust leads to the endogenous emergence of factions of agents with multiple, highly correlated, polarized beliefs.

Necessity and sufficiency are the building blocks of all successful explanations. Yet despite their importance, these notions have been conceptually underdeveloped and inconsistently applied in explainable artificial intelligence, a fast-growing research area that is so far lacking in firm theoretical foundations. In this article, an expanded version of a paper originally presented at the 37th Conference on Uncertainty in Artificial Intelligence, we attempt to fill this gap. Building on work in logic, probability, and causality, we establish the central role of (...) necessity and sufficiency in XAI, unifying seemingly disparate methods in a single formal framework. We propose a novel formulation of these concepts, and demonstrate its advantages over leading alternatives. We present a sound and complete algorithm for computing explanatory factors with respect to a given context and set of agentive preferences, allowing users to identify necessary and sufficient conditions for desired outcomes at minimal cost. Experiments on real and simulated data confirm our method’s competitive performance against state of the art XAI tools on a diverse array of tasks. (shrink)

Faced with the paradox of undermining futures, Humeans have resigned themselves to accounts of chance that severely conflict with our intuitions. However, such resignation is premature: The problem is Humean supervenience (HS), not Humeanism. This paper develops a projectivist Humeanism on which chance claims are understood as normative, rather than fact stating. Rationality constraints on the cotenability of norms and factual claims ground a factual-normative worlds semantics that, in addition to solving the Frege-Geach problem, delivers the intuitive set of possibilia (...) for each chance law. Hence, the account does not entail HS, and the paradox does not arise. A confirmation theory is developed, and the 'principal principle' is justified. (shrink)

Richard Jeffrey’s “Conditioning, Kinematics, and Exchangeability” is one of the foundational documents of probability kinematics. However, the section entitled “Successive Updating” contains a subtle error regarding the applicability of updating by so-called relevance quotients in order to ensure the commutativity of successive probability kinematical revisions. Upon becoming aware of this error, Jeffrey formulated the appropriate remedy, but he never discussed the issue in print. To head off any confusion, it seems worthwhile to alert readers of Jeffrey’s “Conditioning, Kinematics, and Exchangeability” (...) to the aforementioned error and to document his remedy, placing it in the context of both earlier and subsequent work on commuting probability kinematical revisions.1. (shrink)

The so-called "non-commutativity" of probability kinematics has caused much unjustified concern. When identical learning is properly represented, namely, by identical Bayes factors rather than identical posterior probabilities, then sequential probability-kinematical revisions behave just as they should. Our analysis is based on a variant of Field's reformulation of probability kinematics, divested of its (inessential) physicalist gloss.

Jeffrey has devised a probability revision method that increases the probability of hypothesis H when it is discovered that H implies previously known evidence E. A natural extension of Jeffrey's method likewise increases the probability of H when E has been established with sufficiently high probability and it is then discovered, quite apart from this, that H confers sufficiently higher probability on E than does its logical negation H̄.

Additional results are reported on the author's earlier generalization of Richard Jeffrey's solution to the problem of old evidence and new explanation.

How does deductive logic constrain probability? This question is difficult for subjectivistic approaches, according to which probability is just strength of (prudent) partial belief, for this presumes logical omniscience. This paper proposes that the way in which probability lies always between possibility and necessity can be made precise by exploiting a minor theorem of de Finetti: In any finite set of propositions the expected number of truths is the sum of the probabilities over the set. This is generalized to apply (...) to denumerable languages. It entails that the sum of probabilities can neither exceed nor be exceeded by the cardinalities of all consistent and closed (within the set) subsets. In general any numerical function on sentences is said to be logically coherent if it satisfies this condition. Logical coherence allows the relativization of necessity: A function p on a language is coherent with respect to the concept T of necessity iff there is no set of sentences on which the sum of p exceeds or is exceeded by the cardinality of every T-consistent and T-closed (within the set) subset of the set. Coherence is easily applied as well to sets on which the sum of p does not converge. Probability should also be relativized by necessity: A T-probability assigns one to every T-necessary sentence and is additive over disjunctions of pairwise T-incompatible sentences. Logical T-coherence is then equivalent to T-probability: All and only T-coherent functions are T-probabilities. (shrink)

It is often thought that the main significant difference between evidential decision theory and causal decision theory is that they recommend different acts in Newcomb-style examples (broadly construed) where acts and states are correlated in peculiar ways. However, this paper presents a class of non-Newcombian examples that evidential decision theory cannot adequately model whereas causal decision theory can. Briefly, the examples involve situations where it is clearly best to perform an act that will not influence the desired outcome. On evidential (...) decision theory—but not causal decision theory—this situation turns out to be impossible: acts that an agent does not think influence the desired outcome are never optimal. Typically, sophisticated versions of evidential decision theory emulate causal decision theoretic reasoning by (implicitly) conditioning on causal confounders, but in the kind of example considered here, this trick does not work. The upshot is that there is more to causal reasoning than has so far been appreciated. (shrink)

Bayesian inference is limited in scope because it cannot be applied in idealized contexts where none of the hypotheses under consideration is true and because it is committed to always using the likelihood as a measure of evidential favouring, even when that is inappropriate. The purpose of this article is to study inductive inference in a very general setting where finding the truth is not necessarily the goal and where the measure of evidential favouring is not necessarily the likelihood. I (...) use an accuracy argument to argue for probabilism and I develop a new kind of argument to argue for two general updating rules, both of which are reasonable in different contexts. One of the updating rules has standard Bayesian updating, Bissiri et al.’s general Bayesian updating, Douven’s IBE-based updating, and Vassend’s ]) quasi-Bayesian updating as special cases. The other updating rule is novel. (shrink)

In this paper, we explain why the antecedent of a biscuit conditional is relevant to its consequent by extending Douvenʼs evidential support theory of conditionals making use of utilities. By this extension, we can also explain why a biscuit conditional gives rise to the inference that the consequence is (most likely) true. Finally, we account for the intuition that (indicative) biscuit sentences are false when the antecedent is false and allow for counterfactual biscuits.

It has recently been argued that a non-Bayesian probabilistic version of inference to the best explanation (IBE*) has a number of advantages over Bayesian conditionalization (Douven [2013]; Douven and Wenmackers [2017]). We investigate how IBE* could be generalized to uncertain evidential situations and formulate a novel updating rule IBE**. We then inspect how it performs in comparison to its Bayesian counterpart, Jeffrey conditionalization (JC), in a number of simulations where two agents, each updating by IBE** and JC, respectively, try to (...) detect the bias of a coin while they are only partially certain what side the coin landed on. We show that IBE** more often prescribes high probability to the actual bias than JC. We also show that this happens considerably faster, that IBE** passes higher thresholds for high probability, and that it in general leads to more accurate probability distributions than JC. (shrink)

I argue that Quinean naturalists’ holism-based arguments against analyticity and apriority are more difficult to resist than is generally supposed, for two reasons. First, although opponents of naturalism sometimes dismiss these arguments on the grounds that the holistic premises on which they depend are unacceptably radical, it turns out that the sort of holism required by these arguments is actually quite minimal. And second, although it’s true, as Grice and Strawson pointed out long ago, that these arguments can succeed only (...) if there isn’t any principled criterion for meaning change, such a criterion turns out to be hard to come by. David Chalmers has recently argued that such a criterion must exist, since the norms governing belief revision are subject to obvious exceptions that can be explained only by appeal to meaning change. But this, I argue, is incorrect: if choices about how to use language are themselves rationally assessable, then there are no such exceptions to be explained. To show that this is so, I formulate a new kind of coherence norm that may be useful for reasoning formally about the relationship between meaning and evidence. (shrink)