Scientific realism is the optimistic view that modern science is on the right track: that the world really is the way our best scientific theories describe it. In his book, Stathis Psillos gives us a detailed and comprehensive study which restores the intuitive plausibility of scientific realism. We see that throughout the twentieth century, scientific realism has been challenged by philosophical positions from all angles: from reductive empiricism, to instrumentalism and to modern sceptical empiricism. _Scientific Realism_ explains that the history (...) of science does not undermine the arguments for scientific realism, but instead makes it reasonable to accept scientific realism as the best philosophical account of science, its empirical success, its progress and its practice. Anyone wishing to gain a deeper understanding of the state of modern science and why scientific realism is plausible, should read this book. (shrink)

The historical record of scientific inquiry, Stanford suggests, is characterized by what he calls the problem of unconceived alternatives. Past scientists have routinely failed even to conceive of alternatives to their own theories and lines of theoretical investigation, alternatives that were both well-confirmed by the evidence available at the time and sufficiently serious as to be ultimately accepted by later scientific communities. Stanford supports this claim with a detailed investigation of the mid-to-late 19th century theories of inheritance and generation proposed (...) in turn by Charles Darwin, Francis Galton, and August Weismann. He goes on to argue that this historical pattern strongly suggests that there are equally well-confirmed and scientifically serious alternatives to our own best theories that remain currently unconceived. Moreover, this challenge is more serious than those rooted in either the so-called pessimistic induction or the underdetermination of theories by evidence, in part because existing realist responses to these latter challenges offer no relief from the problem of unconceived alternatives itself.Stanford concludes by investigating what positive account of the spectacularly successful edifice of modern theoretical science remains open to us if we accept that our best scientific theories are powerful conceptual tools for accomplishing our practical goals, but abandon the view that the descriptions of the world around us that they offer are therefore even probably or approximately true."Stanford has genuinely advanced the philosophical discussion about scientific realism with his careful articulation of the problem of unconceived alternatives."-- The Review of Metaphysics "Stanford's book deserves to be widely read. Its central argument is clearly stated, its conclusion is radical, it engages in a productive fashion with detailed case studies, and it lays down several substantial challenges to scientific realism. Lastly, it is consistently thought-provoking."-Science. (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 inter 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 contractive 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 incudes a new bibliography."--BOOK JACKET. (shrink)

Van Fraassen believes our current best theories enable us to make accurate predictions because they have been subjected to a selection process similar to natural selection. His explanation for the predictive success of our best theories has been subjected to extensive criticism from realists. I aim to clarify the nature of van Fraassen’s selectionist explanation for the success of science. Contrary to what the critics claim, the selectionist can explain why it is that we have successful theories, as well as (...) why it is reasonable to expect past successful theories to be successful in the future. I also argue that the plausibility of the realists’ explanation rests on an inaccurate understanding of the nature of predictive success . The predictive success of our best theories is a relative success. (shrink)

Are theories ‘underdetermined by the evidence’ in any way that should worry the scientific realist? I argue that no convincing reason has been given for thinking so. A crucial distinction is drawn between data equivalence and empirical equivalence. Duhem showed that it is always possible to produce a data equivalent rival to any accepted scientific theory. But there is no reason to regard such a rival as equally well empirically supported and hence no threat to realism. Two theories are empirically (...) equivalent if they share all consequences expressed in purely observational vocabulary. This is a much stronger requirement than has hitherto been recognised— two such ‘rival’ theories must in fact agree on many claims that are clearly theoretical in nature. Given this, it is unclear how much of an impact on realism a demonstration that there is always an empirically equivalent ‘rival’ to any accepted theory would have—even if such a demonstration could be produced. Certainly in the case of the version of realism that I defend—structural realism—such a demonstration would have precisely no impact: two empirically equivalent theories are, according to structural realism, cognitively indistinguishable. (shrink)

According to the thesis of Strong Predictionism, we typically have stronger evidence for a theory if it was used to predict certain data, than if it was deliberately constructed to accommodate those same data, even if we fully grasp the theory and all the evidence on which it was based. This thesis faces powerful objections and the existing arguments in support of it are seriously flawed. I offer a new defence of Strong Predictionism which overcomes the objections and provides a (...) deeper understanding of the epistemic importance of prediction. I conclude by applying this account to strategies for defending scientific realism. (shrink)

ports the thesis that there exist very many universes. The view has found favor with a number of philosophers such as Derek Parfit ~1998!, J. J. C. Smart ~1989! and Peter van Inwagen ~1993!.1 My purpose is to argue that this is a mistake. First let me set out the issue in more detail.

In this paper, I argue (i) that there are certain methodological practices that are epistemically significant, and (ii) that we can test for the success of these practices empirically by examining case-studies in the history of science. Analysing a particular episode from the history of medicine, I explain how this can help us resolve specific cases of underdetermination. I conclude that, while the anti-realist is (more or less legitimately) able to construct underdetermination scenarios on a case-by-case basis, he will have (...) to abandon the strategy of using algorithms to do so, thus losing the much needed guarantee that there will always be rival cases of the required kind. (shrink)

One typical realist response to the argument from underdetermination of theories by evidence is an appeal to epistemic criteria besides the empirical evidence to argue that, while scientific theories might be empirically equivalent, they are not epistemically equivalent. In this article, I spell out a new and reformulated version of the underdetermination argument that takes such criteria into account. I explain the notion of epistemic equivalence which this new argument appeals to, and argue that epistemic equivalence can be achieved in (...) several, significantly different, ways. On the basis of this ‘multiple realisability’ of epistemic equivalence, I then proceed to explain and examine some of the main consequences of this reformulated underdetermination argument for both realists and anti-realists. (shrink)

Advocates have sought to prove that underdetermination obtains because all theories have empirical equivalents. But algorithms for generating empirical equivalents simply exchange underdetermination for familiar philosophical chestnuts, while the few convincing examples of empirical equivalents will not support the desired sweeping conclusions. Nonetheless, underdetermination does not depend on empirical equivalents: our warrant for current theories is equally undermined by presently unconceived alternatives as well-confirmed merely by the existing evidence, so long as this transient predicament recurs for each theory and body (...) of evidence we consider. The historical record supports the claim that this recurrent, transient underdetermination predicament is our own. (shrink)

Advocates have sought to prove that underdetermination obtains because all theories have empirical equivalents. But algorithms for generating empirical equivalents simply exchange underdetermination for familiar philosophical chestnuts, while the few convincing examples of empirical equivalents will not support the desired sweeping conclusions. Nonetheless, underdetermination does not depend on empirical equivalents: our warrant for current theories is equally undermined by presently unconceived alternatives as well-confirmed merely by the existing evidence, so long as this transient predicament recurs for each theory and body (...) of evidence we consider. The historical record supports the claim that this recurrent, transient underdetermination predicament is our own. (shrink)

I develop an account of predictive similarity that allows even Antirealists who accept a correspondence conception of truth to answer the Realist demand (recently given sophisticated reformulations by Musgrave and Leplin) to explain the success of particular scientific theories by appeal to some intrinsic feature of those theories (notwithstanding the failure of past efforts by van Fraassen, Fine, and Laudan). I conclude by arguing that we have no reason to find truth a better (i.e., more plausible) explanation of a theory's (...) success than predictive similarity, even of its success in making novel predictions. (shrink)

The essays in this volume represent an approach to human knowledge that has had a profound influence on many recent thinkers. Popper breaks with a traditional commonsense theory of knowledge that can be traced back to Aristotle. A realist and fallibilist, he argues closely and in simple language that scientific knowledge, once stated in human language, is no longer part of ourselves but a separate entity that grows through critical selection.

Van Fraassen (1980) claims that successful theories exist today because successful theories survive and unsuccessful ones die. Wray (2007, 2010) appeals to Stanford’s new pessimistic induction (2006), arguing that van Fraassen’s selectionist explanation is better than the realist explanation that successful theories exist because they are approximately true. I argue that if the pessimistic induction is correct, then the evolutionary explanation is neither true nor empirically adequate, and that realism is better than selectionism because realism explains more phenomena in science (...) than selectionism. (shrink)

The no-miracles argument and the pessimistic induction are arguably the main considerations for and against scientific realism. Recently these arguments have been accused of embodying a familiar, seductive fallacy. In each case, we are tricked by a base rate fallacy, one much-discussed in the psychological literature. In this paper we consider this accusation and use it as an explanation for why the two most prominent `wholesale' arguments in the literature seem irresolvable. Framed probabilistically, we can see very clearly why realists (...) and anti-realists have been talking past one another. We then formulate a dilemma for advocates of either argument, answer potential objections to our criticism, discuss what remains (if anything) of these two major arguments, and then speculate about a future philosophy of science freed from these two arguments. In so doing, we connect the point about base rates to the wholesale/retail distinction; we believe it hints at an answer of how to distinguish profitable from unprofitable realism debates. In short, we offer a probabilistic analysis of the feeling of ennui afflicting contemporary philosophy of science. (shrink)

Scientific realists have claimed that the posit that our theories are (approximately) true provides the best or the only explanation for their success . In response, I revive two non-realists explanations. I show that realists, in discarding them, have either misconstrued the phenomena to be explained or mischaracterized the relationship between these explanations and their own. I contend nonetheless that these non-realist competitors, as well as their realist counterparts, should be rejected; for none of them succeed in explaining a significant (...) list of successes. I propose a related non-realist explanation of success that appears to be the most suitable among those considered. (shrink)

How do we go about weighing evidence, testing hypotheses, and making inferences? The model of " inference to the best explanation " -- that we infer the hypothesis that would, if correct, provide the best explanation of the available evidence--offers a compelling account of inferences both in science and in ordinary life. Widely cited by epistemologists and philosophers of science, IBE has nonetheless remained little more than a slogan. Now this influential work has been thoroughly revised and updated, and features (...) a new introduction and two new chapters. Inference to the Best Explanation is an unrivaled exposition of a theory of particular interest in the fields both of epistemology and the philosophy of science. (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)

Leplin attempts to reinstate the common sense idea that theoretical knowledge is achievable, indeed that its achievement is part of the means to progress in empirical knowledge. He sketches the genesis of the skeptical position, then introduces his argument for Minimalist Scientific Realism -- the requirement that novel predicitons be explained, and the claim that only realism about scientific theories can explain the importance of novel prediction.

This essay contains a partial exploration of some key concepts associated with the epistemology of realist philosophies of science. It shows that neither reference nor approximate truth will do the explanatory jobs that realists expect of them. Equally, several widely-held realist theses about the nature of inter-theoretic relations and scientific progress are scrutinized and found wanting. Finally, it is argued that the history of science, far from confirming scientific realism, decisively confutes several extant versions of avowedly 'naturalistic' forms of scientific (...) realism. (shrink)

The problem of scientific disregard is the problem of accounting for why some putative theories that appear to be well-supported by empirical evidence nevertheless play no role in the scientific enterprise. Laudan and Leplin suggest (and Hoefer and Rosenberg concur) that at least some of these putative theories fail to be genuine theoretical rivals because they lack some non-empirical property of theoreticity. This solution also supports their repudiation of the thesis of underdetermination. I argue that the attempt to provide criteria (...) of theoreticity fails, that there is a Bayesian solution to the problem of scientific disregard that fares better, and that this successful solution supports a distinctively Bayesian version of the underdetermination thesis. (shrink)

The instrumentalist argument from the underdetermination of theories by data runs as follows: (1) every theory has empirically equivalent rivals; (2) the only warrant for believing one theory over another is its possession of a greater measure of empirical virtue; (3) therefore belief in any theory is arbitrary. In this paper, I examine the status of the first premise. Several arguments against the universal availability of empirically equivalent theoretical rivals are criticized, and four algorithms for producing empirically equivalent rivals are (...) defended. I conclude that the case for the first premise of the argument from underdetermination is very strong. The disposition of the argument itself depends on the fate of the second premise. (shrink)

Scientific realists have argued that the truth(likeness) of our theories provides the only explanation for the success of science. I consider alternative explanations proposed by antirealists. I endorse Leplin's contention that neither van Fraassen's Darwinist explanation nor Laudan's methodological explanation provides the sort of explanatory alternative which is called for in this debate. Fine's suggestion--that the empirical adequacy of our theories already explains their success--is more promising for antirealists. Leplin claims that this putative explanation collapses into realism on one reading (...) and into vacuity on another reading. But his analysis conflates three doctrines into two, and one of the three avoids both realism and vacuity. (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)

The No-Miracles Argument has a natural representation as a probabilistic argument. As such, it commits the base-rate fallacy. In this article, I argue that a recent attempt to show that there is still a serviceable version that avoids the base-rate fallacy fails, and with it all realistic hope of resuscitating the argument.

This book offers a comprehensive and accessible introduction to the epistemology of science. It not only introduces readers to the general epistemological discussion of the nature of knowledge, but also provides key insights into the particular nuances of scientific knowledge. No prior knowledge of philosophy or science is assumed by The Nature of Scientific Knowledge. Nevertheless, the reader is taken on a journey through several core concepts of epistemology and philosophy of science that not only explores the characteristics of the (...) scientific knowledge of individuals but also the way that the development of scientific knowledge is a particularly social endeavor. The topics covered in this book are of keen interest to students of epistemology and philosophy of science as well as science educators interested in the nature of scientific knowledge. In fact, as a result of its clear and engaging approach to understanding scientific knowledge The Nature of Scientific Knowledge is a book that anyone interested in scientific knowledge, knowledge in general, and any of a myriad of related concepts would be well advised to study closely. (shrink)

Among the most serious challenges to scientific realism are arguments for the underdetermination of theory by evidence. This paper defends a version of scientific realism against what is perhaps the most influential recent argument of this sort, viz. Kyle Stanford’s New Induction over the History of Science. An essential part of the defense consists in a probabilistic analysis of the slogan “absence of evidence is not evidence of absence”. On this basis it is argued that the likelihood of a theory (...) being underdetermined depends crucially on social and historical factors, such as the structure of scientific communities and the time that has passed since the theory first became accepted. This is then shown to serve as the epistemological foundation for a version of scientific realism which avoids Stanford’s New Induction in a principled and non-question-begging way. (shrink)

One of the arguments advanced in favor of scientific realism is the 'miracle argument'. It says that for the anti-realist the predictive success of science appears as an utter miracle. This argument indeed has some prima facie plausibility, provided that it is sharpened by construing "predictive success" as prediction of previously unknown laws and the occurrence of a consilience of inductions. Still, the history of science teaches us that it is possible to arrive at predictive success in this sense by (...) employing radically non-referring theoretical mechanisms. The 'miracle argument' is thus unsound. Rather, the capacity of a theory to generate predictive success can be traced back to its "classificativity correspondence.". (shrink)

Abstract: Laudan (1984) distinguishes between two senses of success for scientific theories: (i) that a particular theory is successful, and (ii) that the methods for picking out approximately true theories are successful. These two senses of success are reflected in two different ways that the no miracles argument for scientific realism (NMA) may be set out. First, I set out a (traditional) version of NMA that considers the success of particular theories. I then consider a more recent formulation of NMA (...) (Psillos, 1999). This version of NMA is aimed at making us believe that our methods for picking out approximately true theories are reliable. I shall argue that the success of the latter argument is dependent on the success of the first. Therefore, even though Psillos presents a new formulation of NMA, the evidential support for it is no stronger than the evidential support for the original version. (shrink)

I argue that van Fraassen’s selectionist explanation for the success of science is superior to the realists’ explanation. Whereas realists argue that our current theories are successful because they accurately reflect the structure of the world, the selectionist claims that our current theories are successful because unsuccessful theories have been eliminated. I argue that, unlike the explanation proposed by the realist, the selectionist explanation can also account for the failures of once successful theories and the fact that sometimes two competing (...) theories are both equally successful. (shrink)

The miracle argument for scientific realism can be cast in two forms: according to the miraculous theory argument, realism is the only position which does not make the empirical successes of particular theories miraculous. According to the miraculous choice argument, realism is the only position which does not render the fact that empirically successful theories have been chosen a miracle. A vast literature discusses the miraculous theory argument, but the miraculous choice argument has been unjustifiably neglected. I raise two objections (...) to Richard Boyd's defense of the latter: (1) we have no miracle free account of the emergence of take-off theories and (2) the anti-realist can account for the non-miraculous choice of empirically successful theories by attributing mere empirical adequacy to background theory. I argue that the availability of extra-empirical criteria that are arguably truth conductive but not theory-laden suffices to answer (1), and the unavailability of extra-empirical criteria that are conductive to empirical adequacy but not necessarily to truth (and are also not theory-laden) constitutes to reply to (2). The prospects for a realist victory are at least somewhat promising, on a controversial assumption about the rate at which empirically successful theories emerge. (shrink)

Scientific realists have argued that the truth of our theories provides the only explanation for the success of science. I consider alternative explanations proposed by antirealists. I endorse Leplin's contention that neither van Fraassen's Darwinist explanation nor Laudan's methodological explanation provides the sort of explanatory alternative which is called for in this debate. Fine's suggestion--that the empirical adequacy of our theories already explains their success--is more promising for antirealists. Leplin claims that this putative explanation collapses into realism on one reading (...) and into vacuity on another reading. But his analysis conflates three doctrines into two, and one of the three avoids both realism and vacuity. (shrink)

An enduring question in the philosophy of science is the question of whether a scientific theory deserves more credit for its successful predictions than it does for accommodating data that was already known when the theory was developed. In The Paradox of Predictivism, Eric Barnes argues that the successful prediction of evidence testifies to the general credibility of the predictor in a way that evidence does not when the evidence is used in the process of endorsing the theory. He illustrates (...) his argument with an important episode from nineteenth-century chemistry, Mendeleev's Periodic Law and its successful predictions of the existence of various elements. The consequences of this account of predictivism for the realist/anti-realist debate are considerable, and strengthen the status of the 'no miracle' argument for scientific realism. Barnes's important and original contribution to the debate will interest a wide range of readers in philosophy of science. (shrink)

In the mid-eighteenth century David Hume argued that successful prediction tells us nothing about the truth of the predicting theory. But physical theory routinely predicts the values of observable magnitudes within very small ranges of error. The chance of this sort of predictive success without a true theory suggests that Hume's argument is flawed. However, Colin Howson argues that there is no flaw and examines the implications of this disturbing conclusion; he also offers a solution to one of the central (...) problems of Western philosophy, the problem of induction. (shrink)

"This book is an attempt at a not too technical scientists' philosophy of science" - Preface.

Scientific Realism is the optimistic view that modern science is on the right track: that the world really is the way our best scientific theories describe it to be. In his book, Stathis Psillos gives us a detailed and comprehensive study, which restores the intuitive plausibility of scientific realism. We see that throughout the twentieth century, scientific realism has been challenged by philosophical positions from all angles: from reductive empiricism, to instrumentalism and modern skeptical empiricism. Scientific Realism explains that the (...) history of science does not undermine the notion of scientific realism, and instead makes it reasonable to accept scientific as the best philosophical account of science, its empirical success, its progress and its practice. Anyone wishing to gain a deeper understanding of the state of modern science and why scientific realism is plausible, should read this book. (shrink)

The essays in this volume represent an approach to human knowledge that has had a profound influence on many recent thinkers. Popper breaks with a traditional commonsense theory of knowledge that can be traced back to Aristotle. A realist and fallibilist, he argues closely and in simple language that scientific knowledge, once stated in human language, is no longer part of ourselves but a separate entity that grows through critical selection.