Figuring prominently in their decisions regarding which theories to pursue are scientists' appeals to the promise or lack of promise of those theories. Yet philosophy of science has had little to say about how one is to assess theory promise. This essay identifies several indices that might be consulted to determine whether or not a theory is promising and worthy of pursuit. Various historical examples of appeals to such indices are introduced.

For several decades now philosophers have discussed apparent examples of internally inconsistent scientific theories. However, there is still much controversy over how exactly we should conceive of scientific theories in the first place. Here I argue for a new approach, whereby all of the truly important questions about inconsistency in science can be asked and answered without disagreements about theories and theory-content getting in the way. Three examples commonly described as ‘internally inconsistent theories’ are analysed in the light of this (...) approach. In the process, the question ‘Is the theory inconsistent or not?’ is identified as a bad, or at least unimportant, question. (shrink)

The philosophical theory of scientific explanation proposed here involves a radically new treatment of causality that accords with the pervasively statistical character of contemporary science. Wesley C. Salmon describes three fundamental conceptions of scientific explanation--the epistemic, modal, and ontic. He argues that the prevailing view is untenable and that the modal conception is scientifically out-dated. Significantly revising aspects of his earlier work, he defends a causal/mechanical theory that is a version of the ontic conception. Professor Salmon's theory furnishes a robust (...) argument for scientific realism akin to the argument that convinced twentieth-century physical scientists of the existence of atoms and molecules. To do justice to such notions as irreducibly statistical laws and statistical explanation, he offers a novel account of physical randomness. The transition from the "reviewed view" of scientific explanation to the causal/mechanical model requires fundamental rethinking of basic explanatory concepts. (shrink)

I erect a framework within the semantic view of theories for explaining the empirical success of internally inconsistent models and theories, with scientific realism in mind. The framework is an instance of the ‘content-driven’ approach to inconsistency, advocated by both Norton (Philos Sci 54:327–350, 1987) and Smith (Stud Hist Philos Sci 19:429–445, 1988a, In: Fine A, Leplin J (eds) PSA1988, 1988b), whose ideas my analysis aims to clarify and substantiate.

In a review of my book “Wahrscheinlichkeitslehre”, Dr. Ernest Nagel has recently criticized some of my ideas on probability and induction. His review includes a good exposition of my ideas, and I have to thank him for his serious attempts to do justice to my results. He attacks, however, some very essential points of my theory. I may be allowed, therefore, to answer him as frankly and thoroughly as he attacks me.

The old quantum theory of black body radiation was manifestly logically inconsistent. It required the energies of electric resonators to be both quantized and continuous. To show that this manifest inconsistency was inessential to the theory's recovery of the Planck distribution law, I extract a subtheory free of this manifest inconsistency but from which Planck's law still follows.

A Bayesian account of the virtue of unification is given. On this account, the ability of a theory to unify disparate phenomena consists in the ability of the theory to render such phenomena informationally relevant to each other. It is shown that such ability contributes to the evidential support of the theory, and hence that preference for theories that unify the phenomena need not, on a Bayesian account, be built into the prior probabilities of theories.

(This insularity was further promoted by the guileless duplicity of scholars in other fields, who were all too prepared to bequeath "the problem of ...

There exists a problem of the circularity in measurement: construction of theories requires reliable data, but obtaining reliable data requires reliable measurement devices whose construction requires a theory. I argue that adapting Anil Gupta's empiricist epistemology to a scientific context yields a possible solution. One can consider the role of data not as providing a foundation for a theory, but as acting functionally, licensing revisions of a previous theory. Data provide scientists with entitlement to their claims conditional on their background (...) theory. Unconditional entitlement is obtained when different starting theories converge to the same view over the course of experimentation. I explain this idea using two examples, one in thermometry and one involving experiments on the weak neutral current. (shrink)

There exists a problem of the circularity in measurement: construction of theories requires reliable data, but obtaining reliable data requires reliable measurement devices whose construction requires a theory. I argue that adapting Anil Gupta's empiricist epistemology to a scientific context yields a possible solution. One can consider the role of data not as providing a foundation for a theory, but as acting functionally, licensing revisions of a previous theory. Data provide scientists with entitlement to their claims conditional on their background (...) theory. Unconditional entitlement is obtained when different starting theories converge to the same view over the course of experimentation. I explain this idea using two examples, one in thermometry and one involving experiments on the weak neutral current. (shrink)

This paper takes as its point of departure two striking incongruities between scientiªc practice and trends in modern history and philosophy of science. (1) Many modern historians of science are so preoccupied with local scientiªc practices that they fail to recognize important non-local elements. (2) Many modern philosophers of science make a sharp distinction between explanation and evidence, whereas in scientiªc practice explanatory power is routinely used as evidence for scientiªc claims. I draw attention to one speciªc way in..

In this discussion note, we explain how to relax some of the standard assumptions made in Garber-style solutions to the Problem of Old Evidence. The result is a more general and explanatory Bayesian approach.

The aim of this paper is to offer an account of epistemic justification suitable for the context of theory pursuit, that is, for the context in which new scientific ideas, possibly incompatible with the already established theories, emerge and are pursued by scientists. We will frame our account paradigmatically on the basis of one of the influential systems of epistemic justification: Laurence Bonjour’s coherence theory of justification. The idea underlying our approach is to develop a set of criteria which indicate (...) that the pursued system is promising of contributing to the epistemic goal of robustness of scientific knowledge and of developing into a candidate for acceptance. In order to realize this we will (a) adjust the scope of Bonjour’s standards—consistency, inferential density, and explanatory power, and (b) complement them by the requirement of a programmatic character. In this way we allow for the evaluation of the “potential coherence” of the given epistemic system. (shrink)

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)

The ArgumentThis paper is about the context of Albert Einstein's concerns at the time of a most intense intellectual effort — his own and that of a small group of scientists concerned with classical quantum theory. I describe contemporaneous interactions and differing views about the prospects for and the significance of the First Solvay Congress of 1911 as voiced by major participants. There are two axes around which the paper evolves: the Einstein-Nernst-Lorentz dialogue and the public institutional creation of the (...) “Solvay” stage. In certain ways, this paper is about personal and institutional patronage: the working out of a difficult theoretical impasse requires individual and collective moral support. It is about the forging of the identity of a scientific problem and the personal and institutional setting, the public space, in which this problem was collectively addressed. But I also uncover heuristic playfulness and flexibility which accompanies theoretical change. (shrink)

This volume includes Whewell's seminal studies of the logic of induction (with his critique of Mill's theory), arguments for his realist view that science discovers necessary truths about nature, and exercises in the epistemology and ontology of science. The book sets forth a coherent statement of a historically important philosophy of science whose influence has never been greater: every one of Whewell's fundamental ideas about the philosophy of science is presented here.

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)

The old evidence problem affects any probabilistic confirmation measure based on comparing pr(H/E) and pr(H). The article argues for the following points: (1) measures based on likelihood ratios also suffer old evidence difficulties; (2) the less-discussed synchronic old evidence problem is, in an important sense, the most acute; (3) prominent attempts to solve or dissolve the synchronic problem fail; (4) a little-discussed variant of the standard measure avoids the problem, in an appealing way; and (5) this measure nevertheless reveals a (...) different problem for probabilistic confirmation measures, a problem that is unlikely to lend itself to formal solution. (shrink)

The use of multiple means of determination to “triangulate” on the existence and character of a common phenomenon, object, or result has had a long tradition in science but has seldom been a matter of primary focus. As with many traditions, it is traceable to Aristotle, who valued having multiple explanations of a phenomenon, and it may also be involved in his distinction between special objects of sense and common sensibles. It is implicit though not emphasized in the distinction between (...) primary and secondary qualities from Galileo onward. It is arguably one of several conceptions involved in Whewell’s method of the “consilience of inductions” (Laudan 1971) and is to be found in several places in Peirce. (From M. Brewer and B. Collins, eds., (1981); Scientific Inquiry in the Social Sciences (a festschrift for Donald T. Campbell), San Francisco: Jossey-Bass, pp. 123–162.). (shrink)

Drawing on diverse historical cases, this paper describes and examines various aspects of a modality of scientific appraisal which has remained largely unexplored, theory pursuit. Specifically, it addresses the following issues: the epistemic and pragmatic commitments involved in theory pursuit, including how these differ from those characteristic of theory acceptance; how the research interests of scientists enter into their pursuit decisions; some of the strategies for the refinement and extension of a theory's empirical abilities which typify theory pursuit; and the (...) need to distinguish between individual and community rationality in contexts of pursuit. (shrink)