In this paper, I argue that the ultimate argument for Scientific Realism, also known as the No-Miracles Argument (NMA), ultimately fails as an abductive defence of Epistemic Scientific Realism (ESR), where (ESR) is the thesis that successful theories of mature sciences are approximately true. The NMA is supposed to be an Inference to the Best Explanation (IBE) that purports to explain the success of science. However, the explanation offered as the best explanation for success, namely (ESR), fails to yield independently (...) testable predictions that alternative explanations for success do not yield. If this is correct, then there seems to be no good reason to prefer (ESR) over alternative explanations for success. (shrink)

This book offers a superbly clear analysis of the standard arguments for and against scientific realism. In surveying claims on both sides of the debate, Kukla organizes them in ways that expose unnoticed connections. He identifies broad patterns of error, reconciles seemingly incompatible positions, and discovers unoccupied positions with the potential to influence further debate. Kukla's overall assessment is that neither the realists nor the antirealists may claim a decisive victory.

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.

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)

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)

Debates about scientific realism are closely connected to almost everything else in the philosophy of science, for they concern the very nature of scientific knowledge. Scientific realism is a positive epistemic attitude toward the content of our best theories and models, recommending belief in both observable and unobservable aspects of the world described by the sciences. This epistemic attitude has important metaphysical and semantic dimensions, and these various commitments are contested by a number of rival epistemologies of science, known collectively (...) as forms of scientific antirealism. This article explains what scientific realism is, outlines its main variants, considers the most common arguments for and against the position, and contrasts it with its most important antirealist counterparts. (shrink)

In this book K. Brad Wray provides a comprehensive survey of the arguments against scientific realism. In addition to presenting logical considerations that undermine the realists' inferences to the likely truth or approximate truth of our theories, he provides a thorough assessment of the evidence from the history of science. He also examines grounds for a defence of anti-realism, including an anti-realist explanation for the success of our current theories, an account of why false theories can be empirically successful, and (...) an explanation for why we should expect radical changes of theory in the future. His arguments are supported and illustrated by cases from the history of science, including a sustained study of the Copernican Revolution, and a study of the revolution in early twentieth century chemistry, when chemists came to classify elements by their atomic number rather than by their atomic weight. (shrink)

Broadly speaking, the contemporary scientific realist is concerned to justify belief in what we might call theoretical truth, which includes truth based on ampliative inference and truth about unobservables. Many, if not most, contemporary realists say scientific realism should be treated as ‘an overarching scientific hypothesis’ (Putnam 1978, p. 18). In its most basic form, the realist hypothesis states that theories enjoying general predictive success are true. This hypothesis becomes a hypothesis to be tested. To justify our belief in the (...) realist hypothesis, realists commonly put forward an argument known as the ‘no-miracles argument’. With respect to the basic hypothesis this argument can be stated as follows: it would be a miracle were our theories as successful as they are, were they not true; the only possible explanation for the general predictive success of our scientific theories is that they are true. (shrink)

Proponents of the no-miracles argument contend that scientific realism is “the only philosophy that doesn’t make the success of science a miracle.” Bas van Fraassen argued, however, that the success of our best theories can be explained in Darwinian terms—by the fact they are survivors of a winnowing process in which unsuccessful theories are rejected. Critics of this selectionist explanation complain that while it may account for the fact we have chosen successful theories, it does not explain why any particular (...) one of those theories succeeds. Against this I defend the claim that if selectionists manage to account for the former, they have no burden to account for the latter; the success of any particular one of our best theories might as well be an extraordinary coincidence. I refer to this enhanced selectionist reply as “coincidentalism” and argue that it is a serious but underappreciated response to the no-miracles argument. More generally, I argue the considerations raised in favor of this response show that versions of the no-miracles argument focusing on the success of particular theories are misguided. (shrink)

Debates about scientific realism are closely connected to almost everything else in the philosophy of science, for they concern the very nature of scientific knowledge. Scientific realism is a positive epistemic attitude toward the content of our best theories and models, recommending belief in both observable and unobservable aspects of the world described by the sciences. This epistemic attitude has important metaphysical and semantic dimensions, and these various commitments are contested by a number of rival epistemologies of science, known collectively (...) as forms of scientific antirealism. This article explains what scientific realism is, outlines its main variants, considers the most common arguments for and against the position, and contrasts it with its most important antirealist counterparts. (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)

Why be a scientific realist? The predominant motivation is explanationist: we need realism to understand the successfulness of science. Why be an antirealist? The predominant motivation is skeptical: theory systematically exceeds the reach of empirical warrant. Antirealists deny that explanatory power is evidential; realists deny that the reach of empirical warrant summarily terminates at the boundary of the observable. But these counterarguments are mere protection of philosophical stances to which the adversaries independently incline.

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)

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)

Debates about scientific realism are closely connected to almost everything else in the philosophy of science, for they concern the very nature of scientific knowledge. Scientific realism is a positive epistemic attitude toward the content of our best theories and models, recommending belief in both observable and unobservable aspects of the world described by the sciences. This epistemic attitude has important metaphysical and semantic dimensions, and these various commitments are contested by a number of rival epistemologies of science, known collectively (...) as forms of scientific antirealism. This article explains what scientific realism is, outlines its main variants, considers the most common arguments for and against the position, and contrasts it with its most important antirealist counterparts. (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)

Research on animal behavior is typically organized according to a combination of two influential frameworks: Ernst Mayr’s distinction between proximate and ultimate causes, and Niko Tinbergen’s “four questions”. My aim is to debunk two common interpretive misconceptions about Mayr’s proximate–ultimate distinction and its relationship to Tinbergen’s four questions, and to offer a new interpretation that avoids both. The first misconception is that the proximate–ultimate distinction maps cleanly onto Tinbergen’s four questions, marking a boundary between Tinbergen’s evolutionary and survival value questions (...) versus developmental and mechanistic questions. The second is that Mayr’s proximate–ultimate distinction is meant to rule out the relevance of proximate causes to evolutionary explanations. I argue that neither is plausible given the text and Mayr’s philosophical aims, namely, to argue that evolutionary biology cannot be reduced to either the physical sciences or to other areas of biology. Through a reconstruction of Mayr’s anti-reductionist argument, I develop an interpretation according to which the proximate–ultimate distinction marks two ways that teleological reasoning can be naturalistically grounded in biology, corresponding to Mayr’s distinction between teleonomic and adapted systems. Mayr distinguishes reduction, which the proximate–ultimate distinction is meant to block, from analysis, through which he allows that proximate causes, causes that are neither proximate nor ultimate, and chance can all contribute to evolutionary explanations. I conclude by suggesting some ways in which the interpretation defended here reframes our understanding of Mayr’s disagreements with some evolutionary-developmental biologists. (shrink)