Precision testing of the quantum electrodynamics (QED) and the standard model provides some of the most secure knowledge in the history of physics. These tests can also be used to constrain and search for new physics going beyond the standard model. We examine the evidential structure of relationships between theoretical predictions from QED, precision measurements of these phenomena, and the indirect determination of the fine structure constant. We argue that "pure QED" is no longer sufficient to predict the electron's anomalous (...) magnetic moment, and that standard model effects are needed. The details relevant to low-energy QED are robust against future theory change. (shrink)

Scientific theories are used for a variety of purposes. For example, physical theories such as classical mechanics and electrodynamics have important applications in engineering and technology, and we trust that this results in useful machines, stable bridges, and the like. Similarly, theories such as quantum mechanics and relativity theory have many applications as well. Beyond that, these theories provide us with an understanding of the world and address fundamental questions about space, time, and matter. Here we trust that the answers (...) scientific theories give are reliable and that we have good reason to believe that the features of the world are similar to what the theories say about them. But why do we trust scientific theories, and what counts as evidence in favor of them? (shrink)

How should we reason in science? Jan Sprenger and Stephan Hartmann offer a refreshing take on classical topics in philosophy of science, using a single key concept to explain and to elucidate manifold aspects of scientific reasoning. They present good arguments and good inferences as being characterized by their effect on our rational degrees of belief. Refuting the view that there is no place for subjective attitudes in 'objective science', Sprenger and Hartmann explain the value of convincing evidence in terms (...) of a cycle of variations on the theme of representing rational degrees of belief by means of subjective probabilities (and changing them by Bayesian conditionalization). In doing so, they integrate Bayesian inference—the leading theory of rationality in social science—with the practice of 21st century science. Bayesian Philosophy of Science thereby shows how modeling such attitudes improves our understanding of causes, explanations, confirming evidence, and scientific models in general. It combines a scientifically minded and mathematically sophisticated approach with conceptual analysis and attention to methodological problems of modern science, especially in statistical inference, and is therefore a valuable resource for philosophers and scientific practitioners. (shrink)

I investigate the role of stability in cosmology through two episodes from the recent history of cosmology: Einstein’s static universe and Eddington’s demonstration of its instability, and the flatness problem of the hot big bang model and its claimed solution by inflationary theory. These episodes illustrate differing reactions to instability in cosmological models, both positive ones and negative ones. To provide some context to these reactions, I also situate them in relation to perspectives on stability from dynamical systems theory and (...) its epistemology. This reveals, for example, an insistence on stability as an extreme position in relation to the spectrum of physical systems which exhibit degrees of stability and fragility, one which has a pragmatic rationale, but not any deeper one. (shrink)

I present a recent historical case from cosmology—the story of inflationary cosmology—and on its basis argue that solving explanatory problems is a reliable method for making progress in science. In particular, I claim that the success of inflationary theory at solving its predecessor’s explanatory problems justified the theory epistemically, even in advance of the development of novel predictions from the theory and the later confirmation of those predictions.

Several physicists, among them Hawking, Page, Coule, and Carroll, have argued against the probabilistic intuitions underlying fine-tuning arguments in cosmology and instead propose that the canonical measure on the phase space of Friedman-Robertson-Walker space-times should be used to evaluate fine-tuning. They claim that flat space-times in this set are actually typical on this natural measure and that therefore the flatness problem is illusory. I argue that they misinterpret typicality in this phase space and, moreover, that no conclusion can be drawn (...) at all about the flatness problem by using the canonical measure alone. (shrink)

Eliminative induction is a method for finding the truth by using evidence to eliminate false competitors. It is often characterized as "induction by means of deduction"; the accumulating evidence eliminates false hypotheses by logically contradicting them, while the true hypothesis logically entails the evidence, or at least remains logically consistent with it. If enough evidence is available to eliminate all but the most implausible competitors of a hypothesis, then (and only then) will the hypothesis become highly confirmed. I will argue (...) that, with regard to the evaluation of hypotheses, Bayesian inductive inference is essentially a probabilistic form of induction by elimination. Bayesian induction is an extension of eliminativism to cases where, rather than contradict the evidence, false hypotheses imply that the evidence is very unlikely, much less likely than the evidence would be if some competing hypothesis were true. This is not, I think, how Bayesian induction is usually understood. The recent book by Howson and Urbach, for example, provides an excellent, comprehensive explanation and defense of the Bayesian approach; but this book scarcely remarks on Bayesian induction's eliminative nature. Nevertheless, the very essence of Bayesian induction is the refutation of false competitors of a true hypothesis, or so I will argue. (shrink)

In this essay, which was his presidential address to the Philosophy of Science Association, Ernan McMullin argued that the watershed between “classic” philosophy of science and the “new” philosophy of science can best be understood by analyzing the change in our perception of the role played by values in science. He begins with some general remarks about the nature of value, goes on to explore some of the historical sources for the claim that judgement in science is value‐laden, and concludes (...) by reflecting on the implications of this claim for traditional views of the objectivity of scientific knowledge‐claims. (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)

Isaac Newton's Scientific Method examines Newton's argument for universal gravity and his application of it to resolve the problem of deciding between geocentric and heliocentric world systems by measuring masses of the sun and planets. William L. Harper suggests that Newton's inferences from phenomena realize an ideal of empirical success that is richer than prediction. Any theory that can achieve this rich sort of empirical success must not only be able to predict the phenomena it purports to explain, but also (...) have those phenomena accurately measure the parameters which explain them. Harper explores the ways in which Newton's method aims to turn theoretical questions into ones which can be answered empirically by measurement from phenomena, and to establish that propositions inferred from phenomena are provisionally accepted as guides to further research. This methodology, guided by its rich ideal of empirical success, supports a conception of scientific progress that does not require construing it as progress toward Laplace's ideal limit of a final theory of everything, and is not threatened by the classic argument against convergent realism. Newton's method endorses the radical theoretical transformation from his theory to Einstein's. Harper argues that it is strikingly realized in the development and application of testing frameworks for relativistic theories of gravity, and very much at work in cosmology today. (shrink)

Cosmological inflation is widely considered an integral and empirically successful component of contemporary cosmology. It was originally motivated by its solution of certain so-called fine-tuning problems of the hot big bang model, particularly what are known as the horizon problem and the flatness problem. Although the physics behind these problems is clear enough, the nature of the problems depends on the sense in which the hot big bang model is fine-tuned and how the alleged fine-tuning is problematic. Without clear explications (...) of these, it remains unclear precisely what problems inflationary theory is meant to be solving and whether it does in fact solve them. I analyze the structure of these problems and consider various interpretations that may substantiate the alleged fine-tuning. On the basis of this analysis I argue that at present there is no unproblematic interpretation available for which it can be said that inflation solves the big bang model’s alleged fine-tuning problems. (shrink)

Recently, biologists have argued that data - driven biology fosters a new scientific methodology; namely, one that is irreducible to traditional methodologies of molecular biology defined as the discovery strategies elucidated by mechanistic philosophy. Here I show how data - driven studies can be included into the traditional mechanistic approach in two respects. On the one hand, some studies provide eliminative inferential procedures to prioritize and develop mechanistic hypotheses. On the other, different studies play an exploratory role in providing useful (...) generalizations to complement the procedure of prioritization. Overall this paper aims to shed light on the structure of contemporary research in molecular biology. (shrink)

Scientific theories are hard to find, and once scientists have found a theory, H, they often believe that there are not many distinct alternatives to H. But is this belief justified? What should scientists believe about the number of alternatives to H, and how should they change these beliefs in the light of new evidence? These are some of the questions that we will address in this article. We also ask under which conditions failure to find an alternative to H (...) confirms the theory in question. This kind of reasoning is frequently used in science and therefore deserves a careful philosophical analysis. 1 Introduction2 The Conceptual Framework3 The No Alternatives Argument4 Discussion I: A Quantitative Analysis of the No Alternatives Argument5 Discussion II: The Number of Alternatives and the Problem of Underdetermination6 ConclusionsAppendix AAppendix B. (shrink)

Science depends on judgments of the bearing of evidence on theory. Scientists must judge whether an observation or the result of an experiment supports, disconfirms, or is simply irrelevant to a given hypothesis. Similarly, scientists may judge that, given all the available evidence, a hypothesis ought to be accepted as correct or nearly so, rejected as false, or neither. Occasionally, these evidential judgments can be made on deductive grounds. If an experimental result strictly contradicts a hypothesis, then the truth of (...) the data deductively entails the falsity of the hypothesis. In the great majority of cases, however, the connection between evidence and hypothesis is non-demonstrative, or inductive. In particular, this is so whenever a general hypothesis is inferred to be correct on the basis of the available data, since the truth of the data will not deductively entail the truth of the hypothesis. It always remains possible that the hypothesis is false even though the data are correct. (shrink)

Douglas proposes a new ideal in which values serve an essential function throughout scientific inquiry, but where the role values play is constrained at key points, protecting the integrity and objectivity of science.

This book presents the concept of “complementary science” which contributes to scientific knowledge through historical and philosophical investigations. It emphasizes the fact that many simple items of knowledge that we take for granted were actually spectacular achievements obtained only after a great deal of innovative thinking, painstaking experiments, bold conjectures, and serious controversies. Each chapter in the book consists of two parts: a narrative part that states the philosophical puzzle and gives a problem-centred narrative on the historical attempts to solve (...) the puzzle; and the analysis part which provides in-depth analyses of certain scientific, historical, and philosophical aspects of the story. (shrink)

Pure consequentialists hold that all theoretical justification derives from testing the consequences of hypotheses, while generativists maintain that reasoning (some feature of) the hypothesis from we already know is an important form of justification. The strongest form of justification (they claim) is an idealized discovery argument. In the guise of H-D methodology, consequentialism is widely supposed to have defeated generativism during the 19th century. I argue that novel prediction fails to overcome the logical weakness of consequentialism or to render generative (...) methodology superfluous. Specifically, Bayesian consequentialism is not an alternative to generativism but reduces to an instance of it. (shrink)

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

The usual, comparative, conception of inference to the best explanation (IBE) takes it to be ampliative. In this paper I propose a conception of IBE ('Holmesian inference') that takes it to be a species of eliminative induction and hence not ampliative. This avoids several problems for comparative IBE (for example, how could it be reliable enough to generate knowledge?). My account of Holmesian inference raises the suspicion that it could never be applied, on the grounds that scientific hypotheses are inevitably (...) underdetermined by the evidence (i.e. are inevitably ampliative). I argue that this concern may be resisted by acknowledging, as Timothy Williamson has shown, that all knowledge is evidence. The latter suggests an approach to resisting scepticism different from those (e.g. the reliabilist approach) that embrace fallibilism. (shrink)

During the last three decades, reflections on the growth of scientific knowledge have inspired historians, sociologists, and some philosophers to contend that scientific objectivity is a myth. In this book, Kitcher attempts to resurrect the notions of objectivity and progress in science by identifying both the limitations of idealized treatments of growth of knowledge and the overreactions to philosophical idealizations. Recognizing that science is done not by logically omniscient subjects working in isolation, but by people with a variety of personal (...) and social interests, who cooperate and compete with one another, he argues that, nonetheless, we may conceive the growth of science as a process in which both our vision of nature and our ways of learning more about nature improve. Offering a detailed picture of the advancement of science, he sets a new agenda for the philosophy of science and for other "science studies" disciplines. (shrink)

Having been neglected or maligned for most of this century, Newton's method of 'deduction from the phenomena' has recently attracted renewed attention and support. John Norton, for example, has argued that this method has been applied with notable success in a variety of cases in the history of physics and that this explains why the massive underdetermination of theory by evidence, seemingly entailed by hypothetico-deductive methods, is invisible to working physicists. This paper, through a detailed analysis of Newton's deduction of (...) one particular 'proposition' in optics 'from the phenomena', gives a clearer account than hitherto of the method - highlighting the fact that it is really one of deduction from the phenomena plus 'background knowledge'. It argues, that, although the method has certain heuristic virtues, examination of its putative accreditational strengths reveals a range of important problems that its defenders have yet adequately to address. (shrink)

Maxwell claimed that the electrostatic inverse square law could be deduced from Cavendish's spherical condenser experiment. This is true only if the accuracy claims made by Cavendish and Maxwell are ignored, for both used the inverse square law as a premise in their analyses of experimental accuracy. By so doing, they assumed the very law the accuracy of which the Cavendish experiment was supposed to test. This paper attempts to make rational sense of this apparently circular procedure and to relate (...) it to some variants of traditional problems concerning old and new evidence. (shrink)

In this essay I examine a recent argument by Steven Weinberg that seeks to establish local quantum field theory as the only type of quantum theory in accord with the relevent evidence and satisfying two basic physical principles. I reconstruct the argument as a demonstrative induction and indicate it's role as a foil to the underdetermination argument in the debate over scientific realism.

Falsificationism has dominated 20th century philosophy of science. It seemed to have eclipsed all forms of inductivism. Yet recent debates have revived a specific form of eliminative inductivism, the basic ideas of which go back to F. Bacon and J.S. Mill. These modern endorsements of eliminative inductivism claim to show that progressive problem solving is possible using induction, rather than falsification as a method of justification. But this common ground between falsificationism and eliminative inductivism has not led to a detailed (...) investigation into the relationship, if any, which may exist between these two methodologies. This paper reviews several versions of eliminative inductivism, establishes a natural relation between eliminative inductivism and falsificationism, which derives from the distinction between models and theories, and carries out this investigation against a case study of the construction of atom models. The result of the investigation is that falsificationism is a form of eliminative inductivism in the limit of certain constraints. (shrink)

Contrary to formal theories of induction, I argue that there are no universal inductive inference schemas. The inductive inferences of science are grounded in matters of fact that hold only in particular domains, so that all inductive inference is local. Some are so localized as to defy familiar characterization. Since inductive inference schemas are underwritten by facts, we can assess and control the inductive risk taken in an induction by investigating the warrant for its underwriting facts. In learning more facts, (...) we extend our inductive reach by supplying more localized inductive inference schemes. Since a material theory no longer separates the factual and schematic parts of an induction, it proves not to be vulnerable to Hume's problem of the justification of induction. (shrink)

We have now celebrated the centenary of J. J. Thomson’s famous paper (1897) on the electron and have examined one hundred years of the history of our first fundamental particle. What should philosophers of science learn from this history? To some, the fundamental moral is already suggested by the rapid pace of this history. Thomson’s concern in 1897 was to demonstrate that cathode rays are electrified particles and not aetherial vibrations, the latter being the “almost unanimous opinion of German physicists” (...) (p. 293) But were these German physicists so easily vanquished? De Broglie proposed in 1923 that electrons are a wave phenomenon after all and his proposal was soon multiply vindicated, even by the detection of the diffraction of the electron waves. Should we not learn from such a reversal? Should we not dispense with the simple-minded idea that Thomson discovered our first fundamental particle and admit that the very notion of discovery might well be ill-suited to science? (shrink)

In his recent book The Advancement of Science, Philip Kitcher endorses eliminative induction, or the view that confirmation of hypotheses proceeds by the elimination of alternatives. My intention here is to critically examine Kitcher's eliminativist view of confirmation, and his rejection of the widely held Bayesian position, according to which an hypothesis H is confirmed by evidence E just in case the probability of H conditional on E is greater than the simple unconditional probability of H [i.e. p > p]. (...) Here, I will maintain that while there are aspects of the eliminative approach which Bayesianism must incorporate, as has been argued by John Earman, the eliminativism advocated by Kitcher is unsatisfactory. In addition, I will suggest that Kitcher's reasons for rejecting Bayesian confirmation theory are unconvincing and depend on an overly restrictive version of the position and that indeed Bayesianism has resources needed by an eliminativist account of confirmation. (shrink)

Inflationary cosmology has been widely accepted due to its successful predictions: for a “generic” initial state, inflation produces a homogeneous, flat, bubble with an appropriate spectrum of density perturbations. However, the discovery that inflation is “generically eternal,” leading to a vast multiverse of inflationary bubbles with different low-energy physics, threatens to undermine this account. There is a “predictability crisis” in eternal inflation, because extracting predictions apparently requires a well-defined measure over the multiverse. This has led to discussions of anthropic predictions (...) based on a measure over the multiverse, and an assumption that we are typical observers. I will give a pessimistic assessment of attempts to make predictions in this sense, emphasizing in particular problems that arise even if a unique measure can be found. (shrink)

This article investigates the implications of string theory for the conception of scientific theory confirmation. The classical understanding of theory confirmation is based on the assumption that scientific theory building is underdetermined by the available empirical data. Several arguments are presented, which suggest a devaluation of this ‘principle of scientific underdetermination’ in the context of string theory. An altered conception of scientific progress emerges that is not based on the notion of theory succession.

Allan Franklin has identified a number of strategies that scientists use to build confidence in experimental results. This paper shows that Franklin's strategies have direct analogues in the context of computer simulation and then suggests that one of his strategies—the so-called 'Sherlock Holmes' strategy—deserves a privileged place within the epistemologies of experiment and simulation. In particular, it is argued that while the successful application of even several of Franklin's other strategies (or their analogues in simulation) may not be sufficient for (...) justified belief in results, the successful application of a slightly elaborated version of the Sherlock Holmes strategy is sufficient. (shrink)

I am grateful to Peter Achinstein, Don Howard, and the other participants at the conference, 'The Role of Experiments in Scientific Changer', Virginia Polytechnic Institute and State University, 30 March to 1 April, 1990, for helpful discussion, and especially to Ron Laymon for his discussion comments presented at the conference on an earlier version of this paper.

I discuss the formal implementation, interpretation, and justification of likelihood attributions in cosmology. I show that likelihood arguments in cosmology suffer from significant conceptual and formal problems that undermine their applicability in this context.

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)

How do we go about weighing evidence, testing hypotheses, and making inferences? According to the model of _Inference to the Best Explanation_, we work out what to infer from the evidence by thinking about what would actually explain that evidence, and we take the ability of a hypothesis to explain the evidence as a sign that the hypothesis is correct. In _Inference to the Best Explanation_, Peter Lipton gives this important and influential idea the development and assessment it deserves. The (...) second edition has been substantially enlarged and reworked, with a new chapter on the relationship between explanation and Bayesianism, and an extension and defence of the account of contrastive explanation. It also includes an expanded defence of the claims that our inferences really are guided by diverse explanatory considerations, and that this pattern of inference can take us towards the truth. This edition of _Inference to the Best Explanation_ has also been updated throughout and includes a new bibliography. (shrink)

In 1912, Henri Poincaré published an argument which apparently shows that the hypothesis of quanta is both necessary and sufficient for the truth of Planck''s experimentally corroborated law describing the spectral distribution of radiant energy in a black body. In a recent paper, John Norton has reaffirmed the authority of Poincarés argument, setting it up as a paradigm case in which empirical data can be used to definitively rule out theoretical competitors to a given theoretical hypothesis. My goal is to (...) dispute Norton ''s claim that there is no theoretical underdetermination problem arising between classical physics and early quantum theory. The strategy I use in defending my view is to adopt a suggestion made by Jarrett Leplin and Larry Laudan on how to assess the relative merits of competing theoretical alternatives, where each alternative has an equal capacity to save the phenomena. In the course of the paper, I distinguish between two branches of classical physics: classical mechanics and classical electromagnetism. The former is claimed by Norton and Poincaré to be determinately ruled out by the black body evidence; and it is the former that I argue is compatible with this evidence. (shrink)

In this paper I want to cast doubt on the claim that there is a legitimate process of reasoning to the best explanation which can serve as an alternative to either straightforward inductive reasoning or a combination of inductive and deductive reasoning. I shall argue a) that paradigmatic cases of acceptable arguments to the best explanation must be considered enthymemes and b) that when the suppressed premises are made explicit we have all of the premises we need to present either (...) a straightforward inductive argument or an argument employing both induction and deduction. (shrink)

Eliminative reasoning seems to play an important role in the sciences, but should it be part of our best theory of science? Statistical evidence, prevalent across the sciences, causes problems for eliminative inference, supporting the view that probabilistic theories of confirmation provide a better framework for reasoning about evidence. Here I argue that deductive elimination has an important inferential role to play in science, one that is compatible with probabilistic approaches to evidence. Eliminative inferences help frame testing problems, an essential (...) step that determines the context for evaluating statistical evidence. I illustrate this process with examples from molecular evolutionary biology. (shrink)