How to regard the weight we give to a proposition on the grounds of its being endorsed by an authority? I examine this question as it is raised within the epistemology of science, and I argue that “authority-based weight” should receive special handling, for the following reason. Our assessments of other scientists’ competence or authority are nearly always provisional, in the sense that to save time and money, they are not made nearly as carefully as they could be---indeed, they are (...) typically made on the basis of only a small portion of the available evidence. Consequently, we need to represent the authority-based elements of our epistemic attitudes in such a way as to allow the later revision of those elements, in case we decide in the light of new priorities that a more conscientious assessment is warranted. I look to the literature in confirmation theory, statistics, and economics for a semiformal model of this revision process, and make a particular proposal of my own. The discussion also casts some light on the question of why certain aspects of science’s epistemic state are not made public. (shrink)

I discuss several issues related to "classical" spacetime structure. I review Galilean, Newtonian, and Leibnizian spacetimes, and briefly describe more recent developments. The target audience is undergraduates and early graduate students in philosophy; the presentation avoids mathematical formalism as much as possible.

The viability of metaphysics as a field of knowledge has been challenged time and again. But in spite of the continuing tendency to dismiss metaphysics, there has been considerable progress in this field in the 20th- and 21st- centuries. One of the newest − though, in a sense, also oldest − frontiers of metaphysics is the grounding project. In this paper I raise a methodological challenge to the new grounding project and propose a constructive solution. Both the challenge and its (...) solution apply to metaphysics in general, but grounding theory puts the challenge in an especially sharp focus. The solution consists of a new methodology, holistic grounding or holistic metaphysics. This methodology is modeled after a recent epistemic methodology, foundational holism, that enables us to pursue the foundational project of epistemology without being hampered by the problems associated with foundationalism. (shrink)

Confirmation and falsification are different strategies for testing theories and characterizing the outcomes of those tests. Roughly speaking, confirmation is the act of using evidence or reason to verify or certify that a statement is true, definite, or approximately true, whereas falsification is the act of classifying a statement as false in the light of observation reports. After expounding the intellectual history behind confirmation and falsificationism, reaching back to Plato and Aristotle, I survey some of the main controversial issues and (...) arguments that pertain to the choice between these strategies: the Raven Paradox, the Duhem/Quine problem and the Grue Paradox. Finally, I outline an evolutionary criticism of inductive Bayesian approaches based on my assumption of doxastic involuntarism. (shrink)

Herbert Simon’s work on scientific discovery deserves serious attention by philosophers of science for several reasons. First, Simon was an early advocate of rational scientific discovery, contra Popper and logical empiricist philosophers of science (Simon 1966). This proposal spurred on investigation of scientific discovery in philosophy of science, as philosophers used and developed Simon’s notions of “problem solving” and “heuristics” in attempts to provide rational accounts of scientific discovery (See Nickles 1980a, Wimsatt 1980). Second, Simon promoted and developed many of (...) the crucial techniques and methods used in cognitive science. One is the use of computers to model internal psychological processes, a technique central to his account of scientific discovery. Another is protocol analysis, the use of the verbal reports of experimental subjects in psychology to construct accounts of their psychological processes. Protocol analysis is given a detailed formulation by Simon (Simon and Ericsson 1984), and is modified for use in the study of scientific cognition in the paper on Krebs (Kulkarni and Simon 1988). (shrink)

The role that need plays in dealing with problems of distributive justice is examined in a series of vignette studies. Among other things, it becomes clear that impartial observers make gradual assessments of justice that depend on the extent to which the observed individuals are endowed with a good. If it is known how high their need for that good is, the assessments are made relative to this reference point. In addition, impartial decision-makers make hypothetical distribution decisions that take into (...) account need, productivity, and accountability. The need of individuals is partially compensated even if they have contributed less to the available amount than they themselves require. However, the willingness to do so decreases if they are accountable for needing more than others or for having contributed less than others. Lastly, both impartial observers and impartial decision-makers distinguish between different types of needs, the fulfillment of which is given different levels of importance. (shrink)

The ontology of decision theory has been subject to considerable debate in the past, and discussion of just how we ought to view decision problems has revealed more than one interesting problem, as well as suggested some novel modifications of classical decision theory. In this paper it will be argued that Bayesian, or evidential, decision-theoretic characterizations of decision situations fail to adequately account for knowledge concerning the causal connections between acts, states, and outcomes in decision situations, and so they are (...) incomplete. Second, it will be argues that when we attempt to incorporate the knowledge of such causal connections into Bayesian decision theory, a substantial technical problem arises for which there is no currently available solution that does not suffer from some damning objection or other. From a broader perspective, this then throws into question the use of decision theory as a model of human or machine planning. (shrink)

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

Anti-exceptionalism about logic takes logical theories to be continuous with scientific theories. Scientific theories are subject to criteria of theoretical equivalence. This article compares two types of theoretical equivalence – one syntactic and one semantic – in the context of logical anti-exceptionalism, and argues that the syntactic approach leads to undesirable consequences. The anti-exceptionalist should therefore take a semantic approach when evaluating whether logical theories, understood as scientific theories, are equivalent. This article argues for a particular semantic approach, in terms (...) of categorical equivalence, to determine whether logical theories are equivalent. (shrink)

I argue that a criterion of theoretical equivalence due to Glymour :227–251, 1977) does not capture an important sense in which two theories may be equivalent. I then motivate and state an alternative criterion that does capture the sense of equivalence I have in mind. The principal claim of the paper is that relative to this second criterion, the answer to the question posed in the title is “yes”, at least on one natural understanding of Newtonian gravitation.

A common methodological adage holds that diverse evidence better confirms a hypothesis than does the same amount of similar evidence. Proponents of Bayesian approaches to scientific reasoning such as Horwich, Howson and Urbach, and Earman claim to offer both a precise rendering of this maxim in probabilistic terms and an explanation of why the maxim should be part of the methodological canon of good science. This paper contends that these claims are mistaken and that, at best, Bayesian accounts of diverse (...) evidence are crucially incomplete. This failure should lend renewed force to a long-neglected global worry about Bayesian approaches. (shrink)

This article examines the effect of material evidence upon historiographic hypotheses. Through a series of successive Bayesian conditionalizations, I analyze the extended competition among several hypotheses that offered different accounts of the transition between the Bronze Age and the Iron Age in Palestine and in particular to the “emergence of Israel”. The model reconstructs, with low sensitivity to initial assumptions, the actual outcomes including a complete alteration of the scientific consensus. Several known issues of Bayesian confirmation, including the problem of (...) old evidence, the introduction and confirmation of novel theories and the sensitivity of convergence to uncertain and disputed evidence are discussed in relation to the model’s result and the actual historical process. The most important result is that convergence of probabilities and of scientific opinion is indeed possible when advocates of rival hypotheses hold similar judgment about the factual content of evidence, even if they differ sharply in their historiographic interpretation. This speaks against the contention that understanding of present remains is so irrevocably biased by theoretical and cultural presumptions as to make an objective assessment impossible. (shrink)

A simple rule of probability revision ensures that the final result ofa sequence of probability revisions is undisturbed by an alterationin the temporal order of the learning prompting those revisions.This Uniformity Rule dictates that identical learning be reflectedin identical ratios of certain new-to-old odds, and is grounded in the oldBayesian idea that such ratios represent what is learned from new experiencealone, with prior probabilities factored out. The main theorem of this paperincludes as special cases (i) Field's theorem on commuting probability-kinematical (...) revisions and (ii) the equivalence of two strategiesfor generalizing Jeffrey's solution to the old evidence problem tothe case of uncertain old evidence and probabilistic new explanation. (shrink)

In a recent paper James Bogen and James Woodward denounce a set of views on confirmation that they collectively brand 'IRS'. The supporters of these views cast confirmation in terms of Inferential Relations between observational and theoretical Sentences. Against 1RS accounts of confirmation, Bogen and Woodward unveil two main objections: (a) inferential relations are not necessary to model confirmation relations since many data are neither in sentential form nor can they be put in such a form and (b) inferential relations (...) are not sufficient to model confirmation relations because the former cannot capture evidentially relevant factors about the detection processes and instruments that generate the data. In this paper I have a two-fold aim: (i) to show that Bogen and Woodward fail to provide compelling grounds for the rejection of IRS models and (ii) to highlight some of the models' neglected merits. (shrink)

The frequent occurrence of comorbidity has brought about an extensive theoretical debate in psychiatry. Why are the rates of psychiatric comorbidity so high and what are their implications for the ontological and epistemological status of comorbid psychiatric diseases? Current explanations focus either on classification choices or on causal ties between disorders. Based on empirical and philosophical arguments, we propose a conventionalist interpretation of psychiatric comorbidity instead. We argue that a conventionalist approach fits well with research and clinical practice and resolves (...) two problems for psychiatric diseases: experimenter’s regress and arbitrariness. (shrink)

Much of scientific inference involves fitting numerical data with a curve, or functional relation. The received view is that the fittest curve is the curve which best balances the conflicting demands of simplicity and accuracy, where simplicity is measured by the number ofparameters in the curve. The problem with this view is that there is no commonly accepted justification for desiring simplicity. This paper presents a measure of the stability of equations. It is argued that the fittest curve is the (...) curve which best balances stability and accuracy. The received view is defended with a proof that simplicity corresponds to stability, for linear regression equations. 1This paper is based on part of my doctoral dissertation. My thanks go to my thesis supervisor Professor Alasdair Urquhart for his encouragement, constructive criticism, and for directing me to several relevant articles: to my advisor Professor Ian Hacking for reminding me to concentrate on results that might have some application in the real world; and to my friend Wendy Brandts for sharing her ideas on a closely related problem. My thanks also to an anonymous referee of The British Journal of the Philosophy of Science for several helpful comments, to my friends and family for unfailing support, and to the Social Sciences and Humanities Research Council (awards 452-86-5885 and 453-87-0513) and the University of Toronto for financial assistance. (shrink)

Philosophers have often noted that science displays an uncommon degree of consensus on beliefs among its practitioners. Yet consensus in the sciences is not a goal in itself. I consider cases of consensus on beliefs as concrete events. Consensus on beliefs is neither a sufficient nor a necessary condition for presuming that these beliefs constitute knowledge. A concrete consensus on a set of beliefs by a group of people at a given historical period may be explained by different factors according (...) to various hypotheses. A particularly interesting hypothesis from an epistemic perspective is the knowledge hypothesis: shared knowledge explains a consensus on beliefs. If all the alternative hypotheses to the knowledge hypotheses are false or are not as good in explaining a concrete consensus on beliefs, the knowledge hypothesis is the best explanation of the consensus. If the knowledge hypothesis is best, a consensus becomes a plausible, though fallible, indicator of knowledge. I argue that if a consensus on beliefs is uncoerced, uniquely heterogeneous and large, the gap between the likelihood of the consensus given the knowledge hypothesis and its likelihoods given competing hypotheses tends to increase significantly. Consensus is a better indicator of knowledge than "success" or "human flourishing". (shrink)

The author uses a series of examples to illustrate two versions of a new, nonprobabilist principle of epistemic rationality, the special and general versions of the metacognitive, expected relative frequency principle. These are used to explain the rationality of revisions to an agent’s degrees of confidence in propositions based on evidence of the reliability or unreliability of the cognitive processes responsible for them—especially reductions in confidence assignments to propositions antecedently regarded as certain—including certainty-reductions to instances of the law of excluded (...) middle or the law of noncontradiction in logic or certainty-reductions to the certainties of probabilist epistemology. The author proposes special and general versions of the MERF principle and uses them to explain the examples, including the reasoning that would lead to thoroughgoing fallibilism—that is, to a state of being certain of nothing. The author responds to the main defenses of probabilism: Dutch Book arguments, Joyce’s potential accuracy defense, and the potential calibration defenses of Shimony and van Fraassen by showing that, even though they do not satisfy the probability axioms, degrees of belief that satisfy the MERF principle minimize expected inaccuracy in Joyce’s sense; they can be externally calibrated in Shimony and van Fraassen’s sense; and they can serve as a basis for rational betting, unlike probabilist degrees of belief, which, in many cases, human beings have no rational way of ascertaining. The author also uses the MERF principle to subsume the various epistemic akrasia principles in the literature. Finally, the author responds to Titelbaum’s argument that epistemic akrasia principles require that we be certain of some epistemological beliefs, if we are rational. (shrink)

Amalgamating evidence of different kinds for the same hypothesis into an overall confirmation is analogous, I argue, to amalgamating individuals’ preferences into a group preference. The latter faces well-known impossibility theorems, most famously “Arrow’s Theorem”. Once the analogy between amalgamating evidence and amalgamating preferences is tight, it is obvious that amalgamating evidence might face a theorem similar to Arrow’s. I prove that this is so, and end by discussing the plausibility of the axioms required for the theorem.

Scientific and statistical inferences build heavily on explicit, parametric models, and often with good reasons. However, the limited scope of parametric models and the increasing complexity of the studied systems in modern science raise the risk of model misspecification. Therefore, I examine alternative, data-based inference techniques, such as bootstrap resampling. I argue that their neglect in the philosophical literature is unjustified: they suit some contexts of inquiry much better and use a more direct approach to scientific inference. Moreover, they make (...) more parsimonious assumptions and often replace theoretical understanding and knowledge about mechanisms by careful experimental design. Thus, it is worthwhile to study in detail how nonparametric models serve as inferential engines in science. (shrink)

Why are conditional degrees of belief in an observation E, given a statistical hypothesis H, aligned with the objective probabilities expressed by H? After showing that standard replies are not satisfactory, I develop a suppositional analysis of conditional degree of belief, transferring Ramsey’s classical proposal to statistical inference. The analysis saves the alignment, explains the role of chance-credence coordination, and rebuts the charge of arbitrary assessment of evidence in Bayesian inference. Finally, I explore the implications of this analysis for Bayesian (...) reasoning with idealized models in science. (shrink)

The main aim of this paper is to revisit the curve fitting problem using the reliability of inductive inference as a primary criterion for the ‘fittest' curve. Viewed from this perspective, it is argued that a crucial concern with the current framework for addressing the curve fitting problem is, on the one hand, the undue influence of the mathematical approximation perspective, and on the other, the insufficient attention paid to the statistical modeling aspects of the problem. Using goodness-of-fit as the (...) primary criterion for ‘best', the mathematical approximation perspective undermines the reliability of inference objective by giving rise to selection rules which pay insufficient attention to ‘accounting for the regularities in the data'. A more appropriate framework is offered by the error-statistical approach, where (i) statistical adequacy provides the criterion for assessing when a curve captures the regularities in the data adequately, and (ii) the relevant error probabilities can be used to assess the reliability of inductive inference. Broadly speaking, the fittest curve (statistically adequate) is not determined by the smallness if its residuals, tempered by simplicity or other pragmatic criteria, but by the nonsystematic (e.g. white noise) nature of its residuals. The advocated error-statistical arguments are illustrated by comparing the Kepler and Ptolemaic models on empirical grounds. ‡I am grateful to Deborah Mayo and Clark Glymour for many valuable suggestions and comments on an earlier draft of the paper; estimating the Ptolemaic model was the result of Glymour's prompting and encouragement. †To contact the author, please write to: Department of Economics, Virginia Tech 3019 Pamplin Hall (0316), Blacksburg, VA 24061; e-mail: [email protected]. (shrink)

Orthodox Bayesianism is a highly idealized theory of how we ought to live our epistemic lives. One of the most widely discussed idealizations is that of logical omniscience: the assumption that an agent’s degrees of belief must be probabilistically coherent to be rational. It is widely agreed that this assumption is problematic if we want to reason about bounded rationality, logical learning, or other aspects of non-ideal epistemic agency. Yet, we still lack a satisfying way to avoid logical omniscience within (...) a Bayesian framework. Some proposals merely replace logical omniscience with a different logical idealization; others sacrifice all traits of logical competence on the altar of logical non-omniscience. We think a better strategy is available: by enriching the Bayesian framework with tools that allow us to capture what agents can and cannot infer given their limited cognitive resources, we can avoid logical omniscience while retaining the idea that rational degrees of belief are in an important way constrained by the laws of probability. In this paper, we offer a formal implementation of this strategy, show how the resulting framework solves the problem of logical omniscience, and compare it to orthodox Bayesianism as we know it. (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)

Tacking by conjunction is a well-known problem for Bayesian confirmation theory. In the first section, disadvantages of existing Bayesian solution proposals to this problem are pointed out and an alternative solution proposal is presented: that of genuine confirmation. In the second section, the notion of GC is briefly recapitulated and three versions of GC are distinguished: full GC, partial GC and quantitative GC. In the third section, the application of partial GC to pure post-facto speculations is explained. In the fourth (...) section it is demonstrated that full GC is a necessary condition for Bayesian convergence to certainty based on the accumulation of conditionally independent pieces of evidence. It is found that whenever a hypothesis is equivalent to a disjunction of more fine-grained hypotheses conveying different probabilities to the evidence, then conditional independence of the evidence fails. This failure occurs typically for unspecific negations of hypotheses. A refined version of the convergence to certainty theorem that overcomes this difficulty is developed in the final section. (shrink)

Tacking by conjunction is a deep problem for Bayesian confirmation theory. It is based on the insight that to each hypothesis h that is confirmed by a piece of evidence e one can ‘tack’ an irrelevant hypothesis h′ so that h∧h′ is also confirmed by e. This seems counter-intuitive. Existing Bayesian solution proposals try to soften the negative impact of this result by showing that although h∧h′ is confirmed by e, it is so only to a lower degree. In this (...) article we outline some problems of these proposals and develop an alternative solution based on a new concept of confirmation that we call genuine confirmation. After pointing out that genuine confirmation is a necessary condition for cumulative confirmation we apply this notion to the tacking by conjunction problem. We consider both the question of what happens when irrelevant hypotheses are added to a hypothesis h that is confirmed by e as well as the question of what happens when h is disconfirmed. The upshot of our discussion will be that genuine confirmation provides a robust solution for each of the different perspectives. _1_ Introduction _2_ Tacking by Conjunction: Existing Solution Proposals _3_ Genuine Confirmation _3.1_ Content elements and content parts _3.2_ Qualitative genuine confirmation _3.3_ Quantitative genuine confirmation _4_ Tacking by Conjunction: The Case of Confirmation _5_ Tacking by Conjunction: The Case of Disconfirmation _6_ Tacking by Conjunction: Adding Multiple Hypotheses _7_ Conclusion Appendix. (shrink)

The concepts of coherence and confirmation are closely intertwined: according to a prominent proposal coherence is nothing but mutual confirmation. Accordingly, it should come as no surprise that both are confronted with similar problems. As regards Bayesian confirmation measures these are illustrated by the problem of tacking by conjunction. On the other hand, Bayesian coherence measures face the problem of belief individuation. In this paper we want to outline the benefit of an approach to coherence and confirmation based on content (...) elements. It will be shown that the resulting concepts, called genuine coherence and genuine confirmation, can be used in order to solve the two mentioned problems. In a final section we present some results on degrees of genuine coherence and genuine confirmation. (shrink)

On analogy with testimony, I define a notion of a scientific theory’s lacking or having candor, in a testing situation, according to whether the theory under test is probabilistically relevant to the processes in the test procedures, and thereby to the reliability of test outcomes. I argue that this property identifies what is distinctive about those theories that Karl Popper denounced as exhibiting “reinforced dogmatism” through their self-protective behavior (e.g., psychoanalysis, Hegelianism, Marxism). I explore whether lack of candor interferes with (...) the testing of theories, and conclude that (1) our default attitude toward theories that lack candor in a given test should be suspicion, but (2) the circumstance that a theory lacks candor in a testing situation does not preclude obtaining independent evidence for the auxiliary assumptions to which the theory is probabilistically relevant, and thereby eliminating the problem that lack of candor creates. Thus, Popper was right to think that lack of candor is a bad thing, but wrong to conclude that candor is a criterion of the scientificity of a theory. Seeing this requires recognition of some differences between intuitive relevance and probabilistic relevance, and proper appreciation of the notion of screening off and of the fact that probabilistic relevance is not transitive. (shrink)

This survey of major developments in North American philosophy of science begins with the mid-1960s consolidation of the disciplinary synthesis of internalist history and philosophy of science (HPS) as a response to criticisms of logical empiricism. These developments are grouped for discussion under the following headings: historical metamethodologies, scientific realisms, philosophies of the special sciences, revivals of empiricism, cognitivist naturalisms, social epistemologies, feminist theories of science, studies of experiment and the disunity of science, and studies of science as practice and (...) culture. A unifying theme of the survey is the relation between historical metamethodologists and scientific realists, which dominated philosophical work in the late 1970s. I argue that many of the alternative cognitive naturalisms, social epistemologies, and feminist theories that have been proposed can be understood as analogues to the differences between metamethodological theories of scientific rationality and realist accounts of successful reference to real causal processes. Recent work on experiment, scientific practice, and the culture of science may, however, challenge the underlying conception of the field according to which realism and historical rationalism (or their descendants) are the important alternatives available, and thus may take philosophy of science in new directions. (shrink)

In this paper, we examine the relationship between general relativity and the theory of Einstein algebras. We show that according to a formal criterion for theoretical equivalence recently proposed by Halvorson and Weatherall, the two are equivalent theories.

With the notable exception of David Lewis, most of those writing on the Sleeping Beauty problem have argued that 1/3 is the correct answer. Terence Horgan has provided the clearest account of why, contrary to Lewis, Beauty has evidence against the proposition that the coin comes up heads when she awakens on Monday. In this paper, I argue that Horgan’s proposal fails because it neglects important facts about epistemic probability.

What attitude should we take toward a scientific theory when it competes with other scientific theories? This question elicited different answers from instrumentalists, logical positivists, constructive empiricists, scientific realists, holists, theory-ladenists, antidivisionists, falsificationists, and anarchists in the philosophy of science literature. I will summarize the diverse philosophical responses to the problem of underdetermination, and argue that there are different kinds of underdetermination, and that they should be kept apart from each other because they call for different responses.

Many philosophers have claimed that Bayesianism can provide a simple justification for hypothetico-deductive inference, long regarded as a cornerstone of the scientific method. Following up a remark of van Fraassen, we analyze a problem for the putative Bayesian justification of H-D inference in the case where what we learn from observation is logically stronger than what our theory implies. Firstly, we demonstrate that in such cases the simple Bayesian justification does not necessarily apply. Secondly, we identify a set of sufficient (...) conditions for the mismatch in logical strength to be justifiably ignored as a "harmless idealization''. Thirdly, we argue, based upon scientific examples, that the pattern of H-D inference of which there is a ready Bayesian justification is only rarely the pattern that one actually finds at work in science. Whatever the other virtues of Bayesianism, the idea that it yields a simple justification of a pervasive pattern of scientific inference appears to have been oversold. (shrink)

Bayesian confirmation theory, as traditionally interpreted, treats the temporal relationship between the formulation of a hypothesis and the confirmation (or recognition) of evidence entailed by that hypothesis merely as a component of the psychology of discovery and acceptance of a hypothesis. The temporal order of these events is irrelevant to the logic of rational theory choice. A few years ago Richmond Campbell and Thomas Vinci offered a reinterpretation of Bayes' Theorem in defense of the view that the temporal relationship between (...) hypothesis and evidence really does matter. More specifically, they advocated the thesis that successful predictions implied by scientific hypothesis H will increase the degree of confirmation of H only if they are novel predictions in the following sense; Evidence E is heuristically novel with respect to hypothesis H if and only if H was not deliberately designed to explain E (if E has already been corroborated) or in anticipation of E (if E is regarded as likely to be corroborated at some future date). Campbell and Vinci argue that the traditional interpretation of Bayes' Theorem misconstrues the significance of predictive novelty by ignoring heuristic novelty. In this paper I review the formal component of their preferred interpretation and demonstrate that it fails to establish that heuristic novelty has any special effect on theory confirmation. That is, even on their revisionist interpretation, regardless of whether H was deliberately designed to explain known evidence E (or in anticipation of suspected E), or whether H was designed without any awareness of the entailment relationship between H and E, Bayes' Theorem will generate the same epistemic probability for hypothesis H. Cases where new evidence was not foreseen at the time a hypothesis first emerged do not carry any more epistemic weight than they would have if such evidence had been foreseen. * Research on this paper was supported by an NEH summer grant. My thanks also to Richmond Campbell and Thomas Vinci for their reply to my initial evaluation of their position (in private correspondence), which compelled me to reconsider their arguments more carefully. (shrink)

The use of the material theory of induction to vindicate a scientist's claims of evidential warrant is illustrated with the cases of Einstein's thermodynamic argument for light quanta of 1905 and his recovery of the anomalous motion of Mercury from general relativity in 1915. In a survey of other accounts of inductive inference applied to these examples, I show that, if it is to succeed, each account must presume the same material facts as the material theory and, in addition, some (...) general principle of inductive inference not invoked by the material theory. Hence these principles are superfluous and the material theory superior in being more parsimonious. (shrink)

The use of the material theory of induction to vindicate a scientist’s claims of evidential warrant is illustrated with the cases of Einstein’s thermodynamic argument for light quanta of 1905 and his recovery of the anomalous motion of Mercury from general relativity in 1915. In a survey of other accounts of inductive inference applied to these examples, I show that, if it is to succeed, each account must presume the same material facts as the material theory and, in addition, some (...) general principle of inductive inference not invoked by the material theory. Hence these principles are superfluous and the material theory superior in being more parsimonious. (shrink)

Bayesians since Savage (1972) have appealed to asymptotic results to counter charges of excessive subjectivity. Their claim is that objectionable differences in prior probability judgments will vanish as agents learn from evidence, and individual agents will converge to the truth. Glymour (1980), Earman (1992) and others have voiced the complaint that the theorems used to support these claims tell us, not how probabilities updated on evidence will actually}behave in the limit, but merely how Bayesian agents believe they will behave, suggesting (...) that the theorems are too weak to underwrite notions of scientific objectivity and intersubjective agreement. I investigate, in a very general framework, the conditions under which updated probabilities actually converge to a settled opinion and the conditions under which the updated probabilities of two agents actually converge to the same settled opinion. I call this mode of convergence deterministic, and derive results that extend those found in Huttegger (2015b). The results here lead to a simple characterization of deterministic convergence for Bayesian learners and give rise to an interesting argument for what I call strong regularity, the view that probabilities of non-empty events should be bounded away from zero. (shrink)

This is a brief, personal retrospective on developments in the treatment of scientific discovery by philosophers, since about 1970.

Van Fraassen argues that explanatory power cannot be a conformational virtue. In this paper I will show that informational features of scientific theories can be positively relevant to their levels of conformation. Thus, in the cases where the explanatory power of a theory is tied to an informational feature of the theory, it can still be the case that the explanatory power of the theory is positively relevant to its level of confirmation.

This paper proposes a framework for representing in Bayesian terms the idea that analogical arguments of various degrees of strength may provide inductive support to yet untested scientific hypotheses. On this account, contextual information plays a crucial role in determining whether, and to what extent, a given similarity or dissimilarity between source and target may confirm an empirical hypothesis over a rival one. In addition to showing confirmation by analogy compatible with the adoption of a Bayesian standpoint, the proposal outlined (...) in this paper reveals a close agreement between the fulfillment of Hesse’s (Models and analogies in science, University of Notre Dame Press, 1963) criteria for analogical arguments capable of inductive support and the attribution of confirmatory power by the lights of Bayesian confirmation theory. In this sense, the Bayesian representation not only enriches a framework, Hesse’s, of enduring relevance for understanding scientific activity, but may offer something akin to a proof of concept of it. (shrink)

This paper is an examination of evidential holism, a prominent position in epistemology and the philosophy of science which claims that experiments only ever confirm or refute entire theories. The position is historically associated with W.V. Quine, and it is at once both popular and notorious, as well as being largely under-described. But even though there’s no univocal statement of what holism is or what it does, philosophers have nevertheless made substantial assumptions about its content and its truth. Moreover they (...) have drawn controversial and important conclusions from these assumptions. In this paper I distinguish three types of evidential holism and argue that the most oft-cited and controversial thesis is entirely unmotivated. The other two theses are much overlooked, but are well-motivated and free from controversial implications. (shrink)

It is well known that the process of scientific inquiry, according to Peirce, is drivenby three types of inference, namely abduction, deduction, and induction. What isbehind these labels is, however, not so clear. In particular, the common identificationof abduction with Inference to the Best Explanation (IBE) begs the question,since IBE appears to be covered by Peirce's concept of induction, not that of abduction.Consequently, abduction ought to be distinguished from IBE, at least on Peirce's account. The main aim of the paper, (...) however, is to show that this distinction is most relevant with respect to current problems in philosophy of science and epistemology (like attempts to supply suitable notions of realism and truth as well as related concepts like coherence and unification). In particular, I also try to show that (and in what way) Peirce's inferential triad can function as a method that ensures both coherence and correspondence. It is in this respect that his careful distinction between abduction and induction (or IBE) ought to be heeded. (shrink)

Charles Peirce’s model of inquiry is supposed to demarcate appropriate methods of inquiry from specious ones. Cheryl Misak points out that Peirce’s explicit account fails, but can nevertheless be rescued by elements of his own system. While Misak’s criticism is a propos, her own attempt to fortify Peirce’s account does not succeed, as it falls prey to the same criticism she raises against Peirce’s explicit account. The account provided in this paper—the ‘open path’ alternative—draws from Peirce’s corollary to his “first (...) rule of reason”, that one should not block the road to inquiry. The ‘open path’ account is able to withstand Misak’s objections, and when combined with other aspects of Peirce’s work, shows us why the optimal way to conduct inquiry is to follow the path of greatest resistance. Inquiry, however, is rarely conducted in optimal conditions. Actual, constrained conditions of inquiry require a measure of economy in terms of what can be reasonably pursued and how. The question, then, is how to conduct our inquiries so that they are as nearly optimal as possible given actual constraints. As a working scientist, Peirce was acutely aware of the need to economize in research. Nicholas Rescher has recognized this issue’s significance for Peirce, and noted its neglect in discussions of Peirce’s work. One issue that has been largely neglected in the literature on Peirce is what specifically he recommends, based on considerations of economy, for how to go about gathering evidence. Kronz & McLaughlin points out that Peirce’s primary recommendation is that in gathering evidence relevant to a particular hypothesis we should test for empirical consequences that would not have been expected otherwise. The view that is developed in this paper is that economy in research, according to Peirce, follows the general line of his theory of inquiry. Peirce’s theory of inquiry implies that pursuit of truth requires maximizing resistance. I argue that his considerations about how to navigate within the constraints introduced in the context of actual research are also best understood as recommendations for maximizing resistance. (shrink)

It has been common wisdom for centuries that scientific inference cannot be deductive; if it is inference at all, it must be a distinctive kind of inductive inference. According to demonstrative theories of induction, however, important scientific inferences are not inductive in the sense of requiring ampliative inference rules at all. Rather, they are deductive inferences with sufficiently strong premises. General considerations about inferences suffice to show that there is no difference in justification between an inference construed demonstratively or ampliatively. (...) The inductive risk may be shouldered by premises or rules, but it cannot be shirked. Demonstrative theories of induction might, nevertheless, better describe scientific practice. And there may be good methodological reasons for constructing our inferences one way rather than the other. By exploring the limits of these possible advantages, I argue that scientific inference is neither of essence deductive nor of essence inductive. (shrink)

Though there is a wide and varied literature on ethical supererogation, there has been almost nothing written about its epistemic counterpart, despite an intuitive analogy between the two fields. This paper seeks to change this state of affairs. I will begin by showing that there are examples which intuitively feature epistemically supererogatory doxastic states. Next, I will present a positive theory of epistemic supererogation that can vindicate our intuitions in these examples, in an explanation that parallels a popular theory of (...) ethical supererogation. Roughly, I will argue that a specific type of epistemic virtue—the ability to creatively think up plausible hypotheses given a body of evidence—is not required of epistemic agents. Thus, certain exercises of this virtue can result in supererogatory doxastic states. In presenting this theory, I will also show how thinking about epistemic supererogation can provide us a new way forward in the debate about the uniqueness thesis for epistemic rationality. (shrink)

For simplicity, most of the literature introduces the concept of definitional equivalence only for disjoint languages. In a recent paper, Barrett and Halvorson introduce a straightforward generalization to non-disjoint languages and they show that their generalization is not equivalent to intertranslatability in general. In this paper, we show that their generalization is not transitive and hence it is not an equivalence relation. Then we introduce another formalization of definitional equivalence due to Andréka and Németi which is equivalent to the Barrett–Halvorson (...) generalization in the case of disjoint languages. We show that the Andréka–Németi generalization is the smallest equivalence relation containing the Barrett–Halvorson generalization and it is equivalent to intertranslatability, which is another definition for definitional equivalence, even for non-disjoint languages. Finally, we investigate which definitions for definitional equivalences remain equivalent when we generalize them for theories in non-disjoint languages. (shrink)