In this dissertation, I explore the work of Donald Davidson, reveal an inconsistency in it, and resolve that inconsistency in a way that complements a debate in philosophy of science. In Part One, I explicate Davidson's extensional account of meaning; though not defending Davidson from all objections, I nonetheless present his seemingly disparate views as a coherent whole. In Part Two, I explicate Davidson's views on the dualism between conceptual schemes and empirical content, isolating four seemingly different arguments that Davidson (...) makes against the dualism; I demonstrate that, though the arguments fail, each is ultimately meant to rely on his account of meaning. ;In Part Three, I show that Davidson's extensional account of meaning gives rise to the analytic-synthetic distinction, while simultaneously needing to reject it. I then propose a resolution to Davidson's dilemma. Rather than treating interpretation of meaning as continuous with the holistic enterprise of science, as Quine treats translation, one should treat it as conceptually prior to science, as Kant treats epistemology. Nonetheless I recognize four reasons why Davidson himself would reject doing so. I therefore propose a view called 'transcendental semantics', based on Davidson's, that accepts my resolution. Further, transcendental semantics, like Kant's own transcendental idealism, posits a single conceptual scheme; nonetheless Kant's is concerned with Newtonian physics, transcendental semantics' with interpretation. ;Finally, in Part Four, I show how positing such a scheme allows transcendental semantics to complement a promising neo-Carnapian account of theory confirmation in science proposed by Michael Friedman. Scientists are first and foremost interpreters, a fact that allows transcendental semantics to help Friedman establish the possibility of rational continuity through scientific revolutions. In fact, transcendental semantics, by complementing Friedman's project, reunites two of Carnap's own concerns, philosophy of language and philosophy of science. I conclude that philosophy of language without philosophy of science is empty , while philosophy of science without philosophy of language is blind. (shrink)

The universal acceptance of atomism in physics and chemistry in the early 20th century went along with an altered view on the epistemic status of microphysical conjectures. Contrary to the prevalent understanding during the 19th century, on the new view unobservable objects could be ‘discovered’. It is argued in the present paper that this shift can be connected to the implicit integration of elements of meta-empirical theory assessment into the concept of theory confirmation.

Long before skeptical theism was called “skeptical theism,” Stephen Wykstra (1984) defended a version of it based on an epistemological principle he called CORNEA. In this paper, I use elementary confirmation theory to analyze CORNEA’s core. This enables me to show precisely what is right about Wykstra’s very influential defense of skeptical theism and, perhaps more importantly, precisely what is wrong with it. A key premise of that defense is that, on the assumption that God exists, we wouldn’t (...) expect to know what God’s reasons for allowing certain evils are. I show that, while that premise together with CORNEA’s core shows that our inability to adequately explain the existence of those evils in terms of theism is not strong evidence against theism, it fails to show that the evils themselves are not strong evidence against theism. (shrink)

This paper examines problems of order and periodicity which arise when the attempt is made to define a confirmation function for a language containing elementary number theory as applied to a universe in which the individuals are considered to be arranged in some fixed order. Certain plausible conditions of adequacy are stated for such a confirmation function. By the construction of certain types of predicates, it is proved, however, that these conditions of adequacy are violated by any (...) confirmation function defined for the type of language in question. Various possible solutions to these difficulties are explored and found to be inadequate. In particular, a proposal which stems from the suggestion to restrict a fundamental principle of confirmation to hypotheses containing only non-positional predicates is cited. This proposal, however, is shown to prevent confirmation functions from taking periodicities into account, and so is deemed unsatisfactory. A general theorem is proved to the effect that if non-positional predicates are taken to satisfy the conditions of adequacy which have been formulated, then no periodicity predicates whatsoever (i.e., predicates used in formulating hypotheses which foretell periodicities) can be subject to these conditions, on pain of contradiction. Yet it seems that periodicity predicates must be subject to these conditions of adequacy if a confirmation function is to recognize periodic occurrences. Thus, an impasse seems to be reached. In the final sections we consider the beginnings of one possible solution to these difficulties. Our proposal involves treating sets of individuals, rather than individuals themselves, as instances of an hypothesis which predicts a periodicity. On this basis we formulate new conditions of adequacy which are free from the previous difficulties and which will permit a confirmation function that satisfies them to take periodicities into account. (shrink)

Confirmation theory is the study of the logic by which scientific hypotheses may be confirmed or disconfirmed, or even refuted by evidence. A specific theory of confirmation is a proposal for such a logic. Presumably the epistemic evaluation of scientific hypotheses should largely depend on their empirical content – on what they say the evidentially accessible parts of the world are like, and on the extent to which they turn out to be right about that. Thus, (...) all theories of confirmation rely on measures of how well various alternative hypotheses account for the evidence.1 Most contemporary confirmation theories employ probability functions to provide such a measure. They measure how well the evidence fits what the hypothesis says about the world in terms of how likely it is that the evidence should occur were the hypothesis true. Such hypothesis-based probabilities of evidence claims are called likelihoods. Clearly, when the evidence is more likely according to one hypothesis than according to an alternative, that should redound to the credit of the former hypothesis and the discredit of the later. But various theories of confirmation diverge on precisely how this credit is to be measured? (shrink)

Hempel's qualitative criteria of converse consequence and special consequence for confirmation are examined, and the resulting paradoxes traced to the general intransitivity of confirmation. Adopting a probabilistic measure of confirmation, a limiting form of transitivity of confirmation from evidence to predictions is derived, and it is shown to what extent its application depends on prior probability judgments. In arguments involving this kind of transitivity therefore there is no necessary "convergence of opinion" in the sense claimed by (...) some personalists. The conditions of application of the limiting transitivity theorem are most perspicuously described in terms of De Finetti's notion of exchangeability, which leads to a suggested revaluation of the function of theories in relation to confirmation and explanation. (shrink)

Two types of idealization in theory construction are distinguished, and the distinction is used to give a critique of Ron Laymon's account of confirming idealized theories and his argument for scientific realism.

The likelihood principle (LP) is a core issue in disagreements between Bayesian and frequentist statistical theories. Yet statements of the LP are often ambiguous, while arguments for why a Bayesian must accept it rely upon unexamined implicit premises. I distinguish two propositions associated with the LP, which I label LP1 and LP2. I maintain that there is a compelling Bayesian argument for LP1, based upon strict conditionalization, standard Bayesian decision theory, and a proposition I call the practical relevance principle. (...) In contrast, I argue that there is no similarly compelling argument for or against LP2. I suggest that these conclusions lead to a restrictedly pluralistic view of Bayesian confirmation measures. (shrink)

Following Nancy Cartwright and others, I suggest that most (if not all) theories incorporate, or depend on, one or more idealizing assumptions. I then argue that such theories ought to be regimented as counterfactuals, the antecedents of which are simplifying assumptions. If this account of the logic form of theories is granted, then a serious problem arises for Bayesians concerning the prior probabilities of theories that have counterfactual form. If no such probabilities can be assigned, the the posterior probabilities will (...) be undefined, as the latter are defined in terms of the former. I argue here that the most plausible attempts to address the problem of probabilities of conditionals fail to help Bayesians, and, hence, that Bayesians are faced with a new problem. In so far as these proposed solutions fail, I argue that Bayesians must give up Bayesianism or accept the counterintuitive view that no theories that incorporate any idealizations have ever really been confirmed to any extent whatsoever. Moreover, as it appears that the latter horn of this dilemma is highly implausible, we are left with the conclusion that Bayesianism should be rejected, at least as it stands. (shrink)

Le problème épistémologique de la confirmation scientifique consiste à déterminer ou comparer le degré de confirmation des hypothèses scientifiques (c’est-à-dire le niveau d’avantage épistémique que nous devons leur accorder) au regard des données empiriques. Ce problème est la plupart du temps traité dans le cadre d’une interprétation probabiliste du raisonnement inductif, notamment au moyen du calcul bayésien, de telle sorte que l’on parle de théorie bayésienne de la confirmation. Nous proposerons ici de considérer la théorie poppérienne de (...) la corroboration comme une théorie alternative de la confirmation scientifique, qui se caractériserait justement par son rejet radical des probabilités et de l’induction. Plus précisément, nous soutiendrons ici, contre certaines lectures de Popper, que le concept poppérien de corroboration peut être assimilé à une forme de confirmation, et nous essaierons d’établir quels seraient les principes d’une théorie poppérienne de la confirmation. Nous... (shrink)

In order to confirm any statement of the form A are B we consider a sufficiently large number of A in order to check them for having or failing to have property B. But logic leads us to believe that A are B is equivalent to non-B are non-A. If this is so then it seems reasonable to suppose that we confirm and in the same way. Whatever set of things we consider for confirming one must be the same set (...) that we consider for the other. Yet in confirming the set considered seems to be the set of A, while in confirming the set considered seems to be the set of non-B. How can two logically equivalent statements be confirmable in different ways? (shrink)

Following Nancy Cartwright and others, I suggest that most theories incorporate, or depend on, one or more idealizing assumptions. I then argue that such theories ought to be regimented as counterfactuals, the antecedents of which are simplifying assumptions. If this account of the logical form of theories is granted, then a serious problem arises for Bayesians concerning the prior probabilities of theories that have counterfactual form. If no such probabilities can be assigned, then posterior probabilities will be undefined, as the (...) latter are defined in terms of the former. I argue here that the most plausible attempts to address the problem of probabilities of conditionals fail to help Bayesians, and, hence, that Bayesians are faced with a new problem. In so far as these proposed solutions fail, I argue that Bayesians must give up Bayesianism or accept the counterintuitive view that no theories that incorporate any idealizations have ever really been confirmed to any extent whatsoever. Moreover, as it appears that the latter horn of this dilemma is highly implausible, we are left with the conclusion that Bayesianism should be rejected, at least as it stands. (shrink)

According to Bayesian confirmation theory, evidence E (incrementally) confirms (or supports) a hypothesis H (roughly) just in case E and H are positively probabilistically correlated (under an appropriate probability function Pr). There are many logically equivalent ways of saying that E and H are correlated under Pr. Surprisingly, this leads to a plethora of non-equivalent quantitative measures of the degree to which E confirms H (under Pr). In fact, many non-equivalent Bayesian measures of the degree to which E (...) confirms (or supports) H have been proposed and defended in the literature on inductive logic. I provide a thorough historical survey of the various proposals, and a detailed discussion of the philosophical ramifications of the differences between them. I argue that the set of candidate measures can be narrowed drastically by just a few intuitive and simple desiderata. In the end, I provide some novel and compelling reasons to think that the correct measure of degree of evidential support (within a Bayesian framework) is the (log) likelihood ratio. The central analyses of this research have had some useful and interesting byproducts, including: (i ) a new Bayesian account of (confirmationally) independent evidence, which has applications to several important problems in con- firmation theory, including the problem of the (confirmational) value of evidential diversity, and (ii ) novel resolutions of several problems in Bayesian confirmation theory, motivated by the use of the (log) likelihood ratio measure, including a reply to the Popper-Miller critique of probabilistic induction, and a new analysis and resolution of the problem of irrelevant conjunction (a.k.a., the tacking problem). (shrink)

Does the Bayesian theory of confirmation put real constraints on our inductive behavior? Or is it just a framework for systematizing whatever kind of inductive behavior we prefer? Colin Howson (Hume's Problem) has recently championed the second view. I argue that he is wrong, in that the Bayesian apparatus as it is usually deployed does constrain our judgments of inductive import, but also that he is right, in that the source of Bayesianism's inductive prescriptions is not the Bayesian (...) machinery itself, but rather what David Lewis calls the ``Principal Principle''. (shrink)

The extra value of novel confirmation over accommodation is explained based on an analysis of the underdetermination of scientific theory building. Novel confirmation can provide information on the number of possible scientific alternatives to a predictively successful theory. This information, in turn, can raise the probability that the given theory is true or will be empirically viable in the future.

In this paper I examine Quine''s indispensability argument, with particular emphasis on what is meant by ''indispensable''. I show that confirmation theory plays a crucial role in answering this question and that once indispensability is understood in this light, Quine''s argument is seen to be a serious stumbling block for any scientific realist wishing to maintain an anti-realist position with regard to mathematical entities.

A recent development in the philosophy of religion has been the attempt to justify belief in God using Bayesian confirmation theory. My dissertation critically discusses two prominent spokesmen for this approach--Richard Swinburne and J. L. Mackie. Using probabilistic confirmation theory, these philosophers come to wildly divergent conclusions with respect to the hypothesis of theism; Swinburne contends that the evidence raises the overall probability of the hypothesis of theism, whereas Mackie argues that the evidence disconfirms the existence (...) of God. After a careful analysis of the individual authors, this dissertation critically examines the assumptions of the project. The authors consider arguments for the existence of God separately--the cosmological argument, the argument from design, apparent miracles, the problem of evil, and arguments from religious experience--and then conjoin them to assess the cumulative effect of the arguments. The assumptions are that the probability calculus may be interpreted for a successful inductive argument for or against the existence of God, that inference to best explanation is applicable to the justification of religious belief, that the justification of belief in God is analogous to the justification of a scientific theory, and that a classical foundationalist conception of rationality is correct. It is the contention of this dissertation that all of these assumptions are incorrect. All of the major interpretations of the probability calculus are examined and it is argued that there are either no interpretations for the probability assignments or no interpretations which will advance an argument for or against the existence of God. It is also argued that the usual methods for interpreting the explanatory power of theism will not determine any non-zero probabilities; however, density measuring will provide a non-zero interpretation. In the final chapter it is argued that a subjective Bayesian conception of rationality is neither a necessary nor a sufficient condition of rationality and that classical foundationalism is self-referentially inconsistent. An alternative approach to the rationality of religious belief is offered that proceeds along Reidian and Plantingan lines, belief in God is properly basic. (shrink)

This chapter contains sections titled: Abstract Introduction First Attempts The Bayesian Paradigm What Good Is There in a Subjectivist Confirmation Theory? Concluding Remarks References.

Confirmation theorists seek to define a function that will take into account the various factors relevant in determining the degree to which an hypothesis is confirmed by its evidence. Among confirmation theorists, only Rudolf Carnap has constructed a system which purports to consider factors in addition to the number of instances, viz. the variety manifested by the instances and the amount of analogy between the instances. It is the purpose of this paper to examine the problem which these (...) additional factors raise for confirmation theory, and to prove that, despite Carnap's claim, no confirmation function satisfying the requirements he has specified can take account of variety and analogy. This result is first proved for a special case, and then, in a subsequent section, is generalized through the introduction of a theorem (the proof of which is given in Appendix I). In the final section of the paper it is shown that, contrary to a claim which Carnap has made, not even the concept of the "logical width" of a predicate will enable confirmation functions satisfying his requirements to take adequate account of analogies between instances. (shrink)

The Quine/Putnam indispensability approach to the confirmation of mathematical theories in recent times has been the subject of significant criticism. In this paper I explore an alternative to the Quine/Putnam indispensability approach. I begin with a van Fraassen-like distinction between accepting the adequacy of a mathematical theory and believing in the truth of a mathematical theory. Finally, I consider the problem of moving from the adequacy of a mathematical theory to its truth. I argue that the (...) prospects for justifying this move are qualitatively worse in mathematics than they are in science. (shrink)

This brief annotated bibliography is intended to help students get started with their research. It is not a substitute for personal investigation of the literature, and it is not a comprehensive bibliography on the subject. For those just beginning to study probabilistic confirmation theory and Bayesian reasoning, I suggest the starred items as good places to start your reading.

I defend a naturalist theory of moral justification, "Confirmation Theory", from an objection raised by David Copp and Geoffrey Sayre-McCord. Confirmation Theory holds that some moral theory is justified because it is needed in the best empirical explanation of the world. The objection is that moral explanations are "incidental", that even if a moral theory is indispensable, this doesn't establish that any moral standard is justified. I show that the naturalist can concede that (...) moral explanations are incidental and still maintain the attractive elements of Confirmation Theory. (shrink)

This essay is concerned with the special difficulties that arise in testing and appraising mainstream economic theory. I argue that, like other theories designed to apply to complex open systems, it is very hard to confirm mainsteam economics. Parts can be tested and appraised, but the theory is only very weakly supported by evidence.

This essay is concerned with the special difficulties that arise in testing and appraising mainstream economic theory. I argue that, like other theories designed to apply to complex open systems, it is very hard to confirm mainsteam economics. Parts can be tested and appraised, but the theory is only very weakly supported by evidence.

There is currently no viable alternative to the Bayesian analysis of scientific inference, yet the available versions of Bayesianism fail to do justice to several aspects of the testing and confirmation of scientific hypotheses. Bayes or Bust? provides the first balanced treatment of the complex set of issues involved in this nagging conundrum in the philosophy of science. Both Bayesians and anti-Bayesians will find a wealth of new insights on topics ranging from Bayes's original paper to contemporary formal learning (...) theory. In a paper published posthumously in 1763, the Reverend Thomas Bayes made a seminal contribution to the understanding of "analogical or inductive reasoning." Building on his insights, modem Bayesians have developed an account of scientific inference that has attracted numerous champions as well as numerous detractors. Earman argues that Bayesianism provides the best hope for a comprehensive and unified account of scientific inference, yet the presently available versions of Bayesianisin fail to do justice to several aspects of the testing and confirming of scientific theories and hypotheses. By focusing on the need for a resolution to this impasse, Earman sharpens the issues on which a resolution turns. John Earman is Professor of History and Philosophy of Science at the University of Pittsburgh. (shrink)

Bayesian confirmation theory—abbreviated to in these notes—is the predominant approach to confirmation in late twentieth century philosophy of science. It has many critics, but no rival theory can claim anything like the same following. The popularity of the Bayesian approach is due to its flexibility, its apparently effortless handling of various technical problems, the existence of various a priori arguments for its validity, and its injection of subjective and contextual elements into the process of confirmation (...) in just the places where critics of earlier approaches had come to think that subjectivity and sensitivity to context were necessary. (shrink)

In a recent paper Samir Okasha has suggested an application of Arrow’s impossibility theorem to theory choice. When epistemic virtues are interpreted as ‘voters’ in charge of ranking competing theories, and there are more than two theories at stake, the final ordering is bound to coincide with the one proposed by one of the voters, provided a number of seemingly reasonable conditions are in place. In a similar spirit, Jacob Stegenga has shown that Arrow’s theorem applies to the amalgamation (...) of evidence; the ‘voters’ here are the different sources of evidence. As with Okasha’s proposal, it is not clear how to avoid Arrow’s pessimistic conclusion.In this paper we develop a novel argument that purports to show that, in typical examples, Arrow’s result does not obtain when dealing with evidence amalgamation. The reason is that we cannot escape the well-known Duhem problem: the evidence actually confirms complex conjunctions that include various auxiliary hypotheses. We argue that confirmational holism induces us to restrict the domain of a reasonable amalgamation function, thus violating one of Arrow’s conditions. The upshot is that we are now able to see the Duhem problem under a different, positive light – namely, as a phenomenon that makes the aggregation of the evidence possible in the first place, when there are at least three options on the table. (shrink)

Bayesian confirmation theory is a leading theory to decide the confirmation/refutation of a hypothesis based on probability calculus. While it may be much discussed in philosophy of science, is it actually practiced in terms of hypothesis testing by scientists? Since the assignment of some of the probabilities in the theory is open to debate and the risk of making the wrong decision is unknown, many scientists do not use the theory in hypothesis testing. Instead, (...) they use alternative statistical tests that can measure the risk or the reliability in decision making, circumventing some of the theoretical problems in practice. Therefore, the theory is not very popular in hypothesis testing among scientists at present. However, there are some proponents of Bayesian hypothesis testing, and software packages are made available to accelerate utilization by scientists. Time will tell whether Bayesian confirmation theory can become both a leading theory and a widely practiced method. In addition, this theory can be used to model the belief of scientists when testing hypotheses. (shrink)

I argue that so-called 'background knowledge' in confirmation theory has little, if anything, to do with 'knowledge' in the sense of mainstream epistemology. I argue that it is better construed as 'background information', which need not be believed in, justified, or true.

Proponents of Bayesian confirmation theory believe that they have the solution to a significant, recalcitrant problem in philosophy of science. It is the identification of the logic that governs evidence and its inductive bearing in science. That is the logic that lets us say that our catalog of planetary observations strongly confirms Copernicus’ heliocentric hypothesis; or that the fossil record is good evidence for the theory of evolution; or that the 3oK cosmic background radiation supports big bang (...) cosmology. The definitive solution to this problem would be a significant achievement. The problem is of central importance to philosophy of science, for, in the end, what distinguishes science from myth making is that we have good evidence for the content of science, or at least of mature sciences, whereas myths are evidentially ungrounded fictions. The core ideas shared by all versions of Bayesian confirmation theory are, at a good first approximation, that a scientist’s beliefs are or should conform to a probability measure; and that the incorporation of new evidence is through conditionalization using Bayes’ theorem. While the burden of this chapter will be to inventory why critics believe this theory may not be the solution after all, it is worthwhile first to summarize here the most appealing virtues of this simple account. There are three. First, the theory reduces the often nebulous notion of a logic of.. (shrink)

The argument from analogy is examined from the point of view of Carnap's confirmation theory. It is argued that if inductive arguments are to be applicable to the real world, they must contain elementary analogical inferences. Carnap's system as originally developed (theλ -system) is not strong enough to take account of analogical arguments, but it is shown that the new system, which he has announced but not published in detail (theη -system), is capable of satisfying the conditions of (...) inductive analogy. Finally it is shown that an elementary analysis of analogical inference yields postulates of the η -system with a minimum of arbitrary assumptions. (shrink)

Neuroeconomics is a research programme founded on the thesis that cognitive and neurobiological data constitute evidence for answering economic questions. I employ confirmation theory in order to reject arguments both for and against neuroeconomics. I also emphasize that some arguments for neuroeconomics will not convince the skeptics because these arguments make a contentious assumption: economics aims for predictions and deep explanations of choices in general. I then argue for neuroeconomics by appealing to a much more restrictive (and thereby (...) skeptic-friendly) characterization of the aims of economics. (shrink)

This paper examines the famous doctrine that independent prediction garners more support than accommodation. The standard arguments for the doctrine are found to be invalid, and a more realistic position is put forward, that whether evidence supports or not a hypothesis depends on the prior probability of the hypothesis, and is independent of whether it was proposed before or after the evidence. This position is implicit in the subjective Bayesian theory of confirmation, and the paper ends with a (...) brief account of this theory, and answer to the principal objections to it. (shrink)

The Paradox of the Ravens (a.k.a,, The Paradox of Confirmation) is indeed an old chestnut. A great many things have been written and said about this paradox and its implications for the logic of evidential support. The first part of this paper will provide a brief survey of the early history of the paradox. This will include the original formulation of the paradox and the early responses of Hempel, Goodman, and Quine. The second part of the paper will describe (...) attempts to resolve the paradox within a Bayesian framework, and show how to improve upon them. This part begins with a discussion of how probabilistic methods can help to clarify the statement of the paradox itself. And it describes some of the early responses to probabilistic explications. We then inspect the assumptions employed by traditional (canonical) Bayesian approaches to the paradox. These assumptions may appear to be overly strong. So, drawing on weaker assumptions, we formulate a new-and-improved Bayesian confirmation-theoretic resolution of the Paradox of the Ravens. (shrink)

Neurolaw is the emerging research field and practice of applying neuroscientific knowledge to legal standards and proceedings. This intersection of neuroscience and law has put up some serious claims, the most significant of which is the overall transformation of the legal system as we know it. The claim has met with strong opposition from scholars of law, such as Michael Pardo and Dennis Patterson (2011), who argue that neurolaw (and neuroscience more generally) is conceptually wrong and thus perceive most of (...) it as “nonsense” (Patterson, 2003). I expose a flaw in Pardo and Patterson’s arguments by means of confirmation theory. My main point is that Pardo and Patterson use implicit hypothetico-deductivism in their attack on neurolaw, and that we have good reasons to doubt the employment of such a model, because it faces serious theoretical problems. I then demonstrate how the alleged problems associated with neurolaw disappear if we use a quantitative probabilistic account of confirmation. I also explain why it provides a better account for the way the legal system actually works. (shrink)