I contrast our own evidence for the hypothesis of organic fossil origins with that available in previous centuries, suggesting that the most powerful contemporary evidence consists in a form of projective support whose distinctive features are not well captured by familiar hypothetico-deductive, abductive, or even more recent and more technically sophisticated accounts of scientific confirmation. I suggest that such accounts either misrepresent or ignore something important about the heterogeneous ways in which scientific hypotheses can be supported by (...) evidence, and I go on to suggest that the search for any single such account may be misguided in any case. (shrink)

Some desiderata for scientific confirmation are formulated in the light of a tentative scientific world view. Bayesian confirmation theories generically satisfy most of these desiderata, but one of them, "the strategy of ascent," fits best in a tempered personalist version of Bayesianism. There are both empirical and rational components, dialectically combined, in tempered personalism. The question of explanation vs. prediction is treated in a Bayesian manner, and it is found that both operations are susceptible to characteristic (...) systematic errors. If these are eliminated, however, then explanation and prediction provide equally good evidential support for hypotheses. (shrink)

Scientific realism driven by inference to the best explanation (IBE) takes empirically confirmed objects to exist, independent, pace empiricism, of whether those objects are observable or not. This kind of realism, it has been claimed, does not need probabilistic reasoning to justify the claim that these objects exist. But I show that there are scientific contexts in which a non-probabilistic IBE-driven realism leads to a puzzle. Since IBE can be applied in scientific contexts in which empirical (...) class='Hi'>confirmation has not yet been reached, realists will in these contexts be committed to the existence of empirically unconfirmed objects. As a consequence of such commitments, because they lack probabilistic features, the possible empirical confirmation of those objects is epistemically redundant with respect to realism. (shrink)

Whereas an inference (deductive as well as inductive) is usually viewed as being valid in virtue of its argument form, the present paper argues that scientific reasoning is material inference, i.e., justified in virtue of its content. A material inference is licensed by the empirical content embodied in the concepts contained in the premises and conclusion. Understanding scientific reasoning as material inference has the advantage of combining different aspects of scientific reasoning, such as confirmation, discovery, and (...) explanation. This approach explains why these different aspects (including discovery) can be rational without conforming to formal schemes, and why scientific reasoning is local, i.e., justified only in certain domains and contingent on particular empirical facts. The notion of material inference also fruitfully interacts with accounts of conceptual change and psychological theories of concepts. (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.

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.

In spite of several attempts to explicate the relationship between a scientific hypothesis and evidence, the issue still cries for a satisfactory solution. Logical approaches to confirmation, such as the hypothetico-deductive method and the positive instance account of confirmation, are problematic because of their neglect of the semantic dimension of hypothesis confirmation. Probabilistic accounts of confirmation are no better than logical approaches in this regard. An outstanding probabilistic account of confirmation, the Bayesian approach, for (...) instance, is found to be defective in that it treats evidence as a formal entity and this creates the problem of relevance of evidence to the hypothesis at issue, in addition to the difficulties arising from the subjective interpretation of probabilities. This essay purports to satisfy the need for a successful account of hypothesis confirmation by offering an original formulation based on the notion of instantiation of the relation urged by an hypothesis. (shrink)

The contributions to Testing Scientific Theories are unified by an in-terest in responding to criticisms directed by Glymour against existing models of confirmation—chiefly H-D and Bayesian schemas—and in assessing and correcting the "bootstrap" model of confirmation that he proposed as an alternative in Theory and Evidence (1980). As such, they provide a representative sample of objections to Glymour's model and of the wide range of new initiatives in thinking about scientific confirmation that it has influenced. (...) The effect is a sense of engagement and focus, and of significant advance at least in articulation of the problems that require solution; as Earman observes, "it is . . . heartening to report that the various opposing camps learned from each other" (p. vi).' In what follows I am concerned to assess what has been learned both critically, about Glymour's model, and constructively about the resources of the alternatives he challenges. My thesis is that while the theories emerging in this debate do deal with a wider range of scientific practice than before, their remaining limitations raise important questions about the ambitions and criteria of adequacy that have traditionally governed philosophical inquiry in this area. (shrink)

That many of our most successful scientific theories involve one or more idealizations poses a challenge to traditional models of theory confirmation. One popular response amongst scientific realists is the “improvement model of confirmation”: if tightening up one or more of the idealizations leads to greater predictive accuracy, then this supports the belief that the theory’s inaccuracy is a result of its idealizations and not because it is wrong. In this article I argue that the improvement (...) model is deeply flawed and that therefore idealizations continue to undermine “success-to-truth” arguments for scientific realism. (shrink)

In spite of several attempts to explicate the relationship between a scientific hypothesis and evidence, the issue still cries for a satisfactory solution. Logical approaches to confirmation, such as the hypothetico-deductive method and the positive instance account of confirmation, are problematic because of their neglect of the semantic dimension of hypothesis confirmation. Probabilistic accounts of confirmation are no better than logical approaches in this regard. An outstanding probabilistic account of confirmation, the Bayesian approach, for (...) instance, is found to be defective in that it treats evidence as a formal entity and this creates the problem of relevance of evidence to the hypothesis at issue, in addition to the difficulties arising from the subjective interpretation of probabilities. This essay purports to satisfy the need for a successful account of hypothesis confirmation by offering an original formulation based on the notion of instantiation of the relation urged by an hypothesis. (shrink)

The paper first raises the problem concerning the confirmation of idealized theories in science and its relationship to scientific realism. Then a solution by Laymon is discussed. It is then argued that two different types of idealization need to be distinguished and that only one of them produces false theories. But then, such “theories” are really theory-maps, which point to theories at the end of improvements. Finally, Laymon’s account is modified in accordance with the above insight.

The idea that there might be empirical evidence for the existence of God has been largely discredited these days. Even among theists there are many who hold that it is not a fruitful idea and that there is no point in searching for evidence for theistic beliefs. Some who regard themselves as theists go to the extreme of denying that there is any possibility of there being empirical evidence to support a religious world-view since that view implies no factual claim, (...) as it is essentially a commitment to a given set of values and a way of life and not to the existence of any physically real entity. Others are willing to assert that theism implies the belief in some special facts but that these are so far removed from the mundane experiences upon which physical science is based, that the latter could not possibly support such a belief. Yet others merely say that there is no need at all for confirmatory evidence of the kind employed in science since their beliefs are grounded in something much firmer and more immediate, like religious experience. (shrink)

Kevin T. Kelly and Clark Glymour. Why Bayesian Confirmation Does Not Capture the Logic of Scientific Justification.

In the philosophy of science, it is a common proposal that values are illegitimate in science and should be counteracted whenever they drive inquiry to the confirmation of predetermined conclusions. Drawing on recent cognitive scientific research on human reasoning and confirmation bias, I argue that this view should be rejected. Advocates of it have overlooked that values that drive inquiry to the confirmation of predetermined conclusions can contribute to the reliability of scientific inquiry at the (...) group level even when they negatively affect an individual’s cognition. This casts doubt on the proposal that such values should always be illegitimate in science. It also suggests that advocates of that proposal assume a narrow, individualistic account of science that threatens to undermine their own project of ensuring reliable belief formation in science. (shrink)

It has been questioned whether it is at all possible to give the term “probability” one uniform and consistent interpretation not merely in mathematics, statistics, evaluation of evidence, testing of hypotheses but also in any situation where we want to express a degree of belief. The question itself of assigning a probability to our belief in a scientific theory has raised important questions of an epistemological as well as mathematical nature.

The contributions to Testing Scientific Theories are unified by an interest in responding to criticisms directed by Glymour against existing models of confirmation–-chiefly H-D and Bayesian schemas–-and in assessing and correcting the “bootstrap“ model of confirmation that he proposed as an alternative in Theory and Evidence. As such, they provide a representative sample of objections to Glymour's model and of the wide range of new initiatives in thinking about scientific confirmation that it has influenced. The (...) effect is a sense of engagement and focus, and of significant advance at least in articulation of the problems that require solution; as Earman observes, “it is … heartening to report that the various opposing camps learned from each other”. In what follows I am concerned to assess what has been learned both critically, about Glymour's model, and constructively about the resources of the alternatives he challenges. My thesis is that while the theories emerging in this debate do deal with a wider range of scientific practice than before, their remaining limitations raise important questions about the ambitions and criteria of adequacy that have traditionally governed philosophical inquiry in this area. (shrink)

In this article we argue for the existence of ‘analogue simulation’ as a novel form of scientific inference with the potential to be confirmatory. This notion is distinct from the modes of analogical reasoning detailed in the literature, and draws inspiration from fluid dynamical ‘dumb hole’ analogues to gravitational black holes. For that case, which is considered in detail, we defend the claim that the phenomena of gravitational Hawking radiation could be confirmed in the case that its counterpart is (...) detected within experiments conducted on diverse realizations of the analogue model. A prospectus is given for further potential cases of analogue simulation in contemporary science. 1 Introduction2 Physical Background2.1 Hawking radiation in semi-classical gravity2.2 Modelling sound in fluids2.3 The acoustic analogue model of Hawking radiation3 Simulation and Analogy in Physical Theory3.1 Analogical reasoning and analogue simulation3.2 Confirmation via analogue simulation3.3 Recapitulation4 The Sound of Silence: Analogical Insights into Gravity4.1 Experimental realization of analogue models4.2 Universality and the Hawking effect4.3 Confirmation of gravitational Hawking radiation5 Prospectus. (shrink)

There are good reasons to endorse scientific realism and good reasons to endorse common-sense realism. However, it has sometimes been suggested that there is a tension between the two which makes it difficult to endorse both. Can the common-sense picture of the world be reconciled with the strikingly different picture presented to us by our best confirmed theories of science? This chapter critically examines proposals for doing so, and it offers a new one, which is essentially this. It is (...) a psychological fact that we have certain common-sense beliefs. In the framework of reductive physicalism, all beliefs, including the common-sense ones, are nothing but brain states and processes. Being scientifically realist about these brain states and accepting the reductive-physicalist view of the mind, we can account for the psychological fact that we have certain common-sense beliefs with certain contents, without committing to the idea that the contents of these common-sense beliefs have to be true of the world. In this coherentist approach we are not required to relinquish our common-sense beliefs, since although they are false according to science, this very same science shows that holding those beliefs is fully rational. (shrink)

Any theory of confirmation must answer the following question: what is the purpose of its conception of confirmation for scientific inquiry? In this article, we argue that no Bayesian conception of confirmation can be used for its primary intended purpose, which we take to be making a claim about how worthy of belief various hypotheses are. Then we consider a different use to which Bayesian confirmation might be put, namely, determining the epistemic value of experimental (...) outcomes, and thus to decide which experiments to carry out. Interestingly, Bayesian confirmation theorists rule out that confirmation be used for this purpose. We conclude that Bayesian confirmation is a means with no end. 1 Introduction2 Bayesian Confirmation Theory3 Bayesian Confirmation and Belief4 Confirmation and the Value of Experiments5 Conclusion. (shrink)

Various scientific theories stand in a reductive relation to each other. In a recent article, we have argued that a generalized version of the Nagel-Schaffner model (GNS) is the right account of this relation. In this article, we present a Bayesian analysis of how GNS impacts on confirmation. We formalize the relation between the reducing and the reduced theory before and after the reduction using Bayesian networks, and thereby show that, post-reduction, the two theories are confirmatory of each (...) other. We then ask when a purported reduction should be accepted on epistemic grounds. To do so, we compare the prior and posterior probabilities of the conjunction of both theories before and after the reduction and ask how well each is confirmed by the available evidence. (shrink)

The analysis of theory-confirmation generally takes the deductive form: show that a theory in conjunction with physical data and auxiliary hypotheses yield a prediction about phenomena; verify the prediction; provide a quantitative measure of the degree of theory-confirmation this yields. The issue of confirmation for an entire framework either does not arise, or is dismissed in so far as frameworks are thought not to be the kind of thing that admits scientific confirmation. I argue that (...) there is another form of scientific reasoning that has not received philosophical attention, what I call Newtonian abduction, that does provide confirmation for frameworks as a whole, and does so in two novel ways. I further argue that Newtonian abduction is at least as important a form of reasoning in science as standard deductive and inductive forms. The form is beautifully summed up by Maxwell : “The true method of physical reasoning is to begin with the phenomena and to deduce the forces from them by a direct application of the equations of motion.”. (shrink)

The analysis of theory-confirmation generally takes the deductive form: show that a theory in conjunction with physical data and auxiliary hypotheses yield a prediction about phenomena; verify the prediction; provide a quantitative measure of the degree of theory-confirmation this yields. The issue of confirmation for an entire framework (e.g., Newtonian mechanics en bloc, as opposed, say, to Newton’s theory of gravitation) either does not arise, or is dismissed in so far as frameworks are thought not to be (...) the kind of thing that admits scientific confirmation. I argue that there is another form of scientific reasoning that has not received philosophical attention, what I call Newtonian abduction, that does provide confirmation for frameworks as a whole, and does so in two novel ways. (In particular, Newtonian abduction is not inference to the best explanation, but rather is closer to Peirce’s original idea of abduction.) I further argue that Newtonian abduction is at least as important a form of reasoning in science as standard deductive and inductive forms. The form is beautifully summed up by Maxwell (Proc Camb Philos Soc II:292–294, 1876): “The true method of physical reasoning is to begin with the phenomena and to deduce the forces from them by a direct application of the equations of motion.”. (shrink)

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)

Recent work on inference to the best explanation has come to an impasse regarding the proper way to coordinate the theoretical virtues in explanatory inference with probabilistic confirmation theory, and in particular with aspects of Bayes's Theorem. I argue that the theoretical virtues are best conceived heuristically and that such a conception gives us the resources to explicate the virtues in terms of ceteris paribus theorems. Contrary to some Bayesians, this is not equivalent to identifying the virtues with likelihoods (...) or priors per se; the virtues may be more accessible epistemically than likelihoods or priors. I then prove a ceteris paribus theorem regarding theoretical consilience, use it to correct a recent application of Reichenbach's common cause principle, and apply it to a test case of scientific reasoning. Explanation and confirmation The heuristic conception of theoretical virtues Abduction and the accessibility of explanatory power Evidential and theoretical consilience A test case: gravitational lensing Conclusion Thus natural science appears completely to lose from sight the large and general questions; but all the more splendid is the success when, groping in the thicket of special questions, we suddenly find a small opening that allows a hitherto undreamt of outlook on the whole. (L. Boltzmann, Theoretical Physics and Philosophical Problems). (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)

I critically examine confirmational holism as it pertains to the indispensability arguments for mathematical Platonism. I employ a distinction between pure and applied mathematics that grows out of the often overlooked symbiotic relationship between mathematics and science. I argue that this distinction undercuts the notion that mathematical theories fall under the holistic scope of the confirmation of our scientific theories.Keywords: Confirmational holism; Indispensability argument; Mathematics; Application; Science.

This article reports the results of a study of confirmational response bias among social work journals. A contrived research paper with positive findings and its negative mirror image were submitted to two different groups of social work journals and to two comparison groups of journals outside social work. The quantitative results, suggesting bias, are tentative; but the qualitative findings based upon an analysis of the referee comments are clear and consistent. Few referees from prestigious or nonprestcgrous social work journals prepared (...) reviews that were knowledgeable, scientifically astute, or objective. The best reviews came from journals outside of soccal work or from journals that are accepted as social work journals but originate with other disciplines. (shrink)

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)

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.

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.

The Quine-Putnam Indispensability argument is the argument for treating mathematical entities on a par with other theoretical entities of our best scientific theories. This argument is usually taken to be an argument for mathematical realism. In this chapter I will argue that the proper way to understand this argument is as putting pressure on the viability of the marriage of scientific realism and mathematical nominalism. Although such a marriage is a popular option amongst philosophers of science and mathematics, (...) in light of the indispensability argument, the marriage is seen to be very unstable. Unless one is careful about how the Quine-Putnam argument is disarmed, one can be forced to either mathematical realism or, alternatively, scientific instrumentalism. I will explore the various options: (i) finding a way to reconcile the two partners in the marriage by disarming the indispensability argument (Jody Azzouni [2], Hartry Field [13, 14], Alan Musgrave [18, 19], David Papineau [21]); (ii) embracing mathematical realism (W.V.O. Quine [23], Michael Resnik [25], J.J.C. Smart [27]); and (iii) embracing some form of scientific instrumentalism (Ot´ avio Bueno [7, 8], Bas van Fraassen [30]). Elsewhere [11], I have argued for option (ii) and I won’t repeat those arguments here. Instead, I will consider the difficulties for each of the three options just mentioned, with special attention to option (i). In relation to the latter, I will discuss an argument due to Alan Musgrave [19] for why option (i) is a plausible and promising approach. From the discussion of Musgrave’s argument, it will emerge that the issue of holist versus separatist theories of confirmation plays a curious role in the realism–antirealism debate in the philosophy of mathematics. I will argue that if you take confirmation to be an holistic matter—it’s whole theories (or significant parts thereof) that are confirmed in any experiment—then there’s an inclination to opt for (ii) in order to resolve the marital tension outlined above.. (shrink)

We argue that a particular approach to satisfying the broad predictive ambitions of the sciences demands law confirmation. On this approach we confirm non-nomic generalizations by confirming there are no actually realized ways of causing disconfirming cases. This gives causal generalizations a crucial role in prediction. We then show how rational judgements of relevant causal similarity can be used to confirm that causal generalizations themselves have no actual disconfirmers, providing a distinctive and clearly viable methodology for inductively confirming them. (...) Finally, we argue that for agents in our epistemic position using this methodology to confirm causal generalizations of adequate breadth will commonly demand law confirmation. We make a prima facie assessment of the methodology’s fit with scientific practice and briefly consider the prospects for an associated analysis of laws. (shrink)

Philosophers of science have offered various accounts of climate model evaluation which have largely centered on model-fit assessment. However, despite the wide-spread prevalence of process-based evaluation in climate science practice, this sort of model evaluation has been undertheorized by philosophers of science. In this paper, I aim to expand this narrow philosophical view of climate model evaluation by providing a philosophical account of process evaluation that is rooted in a close examination of scientific practice. I propose dynamical adequacy as (...) a metric by which scientists test and evaluate models that represent and produce key regional climate processes and features. I argue that process-based evaluation confirms the adequacy of a regional climate model for simulating and predicting future changes of a specific regional climate feature. I offer a case study of how, in practice, scientists establish the reliability of model projections by assessing the dynamical adequacy of such models. I also show how process-based evaluation mitigates some well-known shortcomings of model-fit assessment and supports the adequacy and reliability of climate model projections against philosophical objections, like confirmational holism. Such adequacy is especially important for decision makers who need reliable regional model projections to guide their climate change mitigation and adaptation policies. (shrink)

Quine and Putnam argued for mathematical realism on the basis of the indispensability of mathematics to science. They claimed that the mathematics that is used in physical theories is confirmed along with those theories and that scientific realism entails mathematical realism. I argue here that current theories of confirmation suggest that mathematics does not receive empirical support simply in virtue of being a part of well confirmed scientific theories and that the reasons for adopting a realist view (...) of scientific theories do not support realism about mathematical entities, despite the use of mathematics in formulating scientific theory. (shrink)

Quine and Putnam argued for mathematical realism on the basis of the indispensability of mathematics to science. They claimed that the mathematics that is used in physical theories is confirmed along with those theories and that scientific realism entails mathematical realism. I argue here that current theories of confirmation suggest that mathematics does not receive empirical support simply in virtue of being a part of well confirmed scientific theories and that the reasons for adopting a realist view (...) of scientific theories do not support realism about mathematical entities, despite the use of mathematics in formulating scientific theory. (shrink)

The confirmation of scientific hypotheses has a quantitative and qualitative aspect. No empirical hypothesis can be confirmed conclusively, so philosophers of science have used the theory of probability to elucidate the quantitative component, which determines a degree of confirmation ‐ that is, the extent to which the hypothesis is supported by the evidence (see probability and evidence and confirmation). By contrast, the qualitative feature of confirmation concerns the prior question of the nature of the relation (...) between the hypothesis and the evidence if the hypothesis is to be confirmed by its instances. If a hypothesis is to be supported by a body of evidence, it must be related to the evidence in an appropriate way. The paradoxes of confirmation arise in the attempt to characterize in first‐order logic the qualitative relation between hypothesis and evidence. (shrink)

Imagination is necessary for scientific practice, yet there are no in vivo sociological studies on the ways that imagination is taught, thought of, or evaluated by scientists. This article begins to remedy this by presenting the results of a qualitative study performed on two systems biology laboratories. I found that the more advanced a participant was in their scientific career, the more they valued imagination. Further, positive attitudes toward imagination were primarily due to the perceived role of imagination (...) in problem-solving. But not all problem-solving episodes involved clear appeals to imagination, only maximally specific problems did. This pattern is explained by the presence of an implicit norm governing imagination use in the two labs: only use imagination on maximally specific problems, and only when all other available methods have failed. This norm was confirmed by the participants, and I argue that it has epistemological reasons in its favour. I also found that its strength varies inversely with career stage, such that more advanced scientists do (and should) occasionally bring their imaginations to bear on more general problems. A story about scientific pedagogy explains the trend away from (and back to) imagination over the course of a scientific career. Finally, some positive recommendations are given for a more imagination-friendly scientific pedagogy. (shrink)

Does confirmation holism imply meaning holism? A plausible and novel argument, all of whose premises enjoy significant support among contemporary philosophers, links the two theses. This article presents this argument and diagnoses it with a weakness. The weakness illustrates a general difficulty with drawing morals for the nature of ordinary thought and language from claims about the nature of science. The diagnosis is instructive: It suggests more fruitful relations between theories of scientific theory confirmation and semantic theories (...) of our everyday thoughts and statements. (shrink)

Bayesian epistemology postulates a probabilistic analysis of many sorts of ordinary and scientific reasoning. Huber ([2005]) has provided a novel criticism of Bayesianism, whose core argument involves a challenging issue: confirmation by uncertain evidence. In this paper, we argue that under a properly defined Bayesian account of confirmation by uncertain evidence, Huber's criticism fails. By contrast, our discussion will highlight what we take as some new and appealing features of Bayesian confirmation theory. 1. Introduction2. Uncertain Evidence (...) and Bayesian Confirmation3. Bayesian Confirmation by Uncertain Evidence: Test Cases and Basic Principles. (shrink)

In the nineteenth century, William Whewell claimed that his confirmation criterion of consilience was a truth-guarantor: we could, he believed, be certain that a consilient theory was true. Since that time Whewell has been much ridiculed for this claim by critics such as J. S. Mill and Bas van Fraassen. I have argued elsewhere that, while Whewell's claim that consilience can guarantee the truth of a theory is clearly wrong, consilience is indeed quite useful as a confirmation criterion (...) (Snyder 2005). Here I will show that, even when consilience gives evidence for a theory that turns out to be false, there is an important sense in which consilience shows that the theory has captured something correct about the natural-kind structure of the physical world. Whewell was therefore correct to claim that consilience provides a "criterion of reality" (Whewell [1847] 1967, vol. 2, 68). Consilience provides this by giving justification for the claim that we have really `cut nature at its causal joints', to adapt Plato's famous phrase. Because of this, consilience can play a role in an argument for scientific realism. (shrink)