Any serious student attempting to better understand the nature, methods, and justification of science will value Alex Rosenberg's and Lee McIntyre's updated and substantially revised Fourth Edition of Philosophy of Science: A Contemporary Introduction. Weaving lucid explanations with clear analyses, the volume is as a much-used, thematically-oriented introduction to the field.

This chapter shows that the experimental philosophy has much to offer to philosophy of science by reviewing the existing experimental‐philosophy work in the philosophy of science and by defending it against an important criticism. A natural way of extending experimental philosophy methods to the philosophy of science is to survey scientists’ judgments. The chapter presents two projects in the philosophy of science that can benefit from such surveys: analyzing the scientific concepts found in particular scientific communities and studying scientific cognition. (...) It explains how surveying lay people's judgments can bear on issues in the philosophy of science. The chapter examines the possible contributions of bibliometric, ethnographic and cliometric methods to the philosophy of science. Ethnographic methods are particularly useful to study the social structure of science, the nature and role of social norms in the production of scientific knowledge, and the discovery heuristics at work in everyday scientific practice. (shrink)

In his new foreword to this edition, Hilary Putnam forcefully rejects these nativist claims.

What do appeals to case studies accomplish? Consider the dilemma: On the one hand, if the case is selected because it exemplifies the philosophical point, then it is not clear that the historical data hasn't been manipulated to fit the point. On the other hand, if one starts with a case study, it is not clear where to go from there—for it is unreasonable to generalize from one case or even two or three.

Interdisciplinary research within the field of sustainability studies often faces incompatible ontological assumptions deriving from natural and social sciences. The importance of this fact is often underrated and sometimes leads to the wrong strategies. We distinguish between two broad approaches in interdisciplinarity: unificationism and pluralism. Unificationism seeks unification and perceives disciplinary boundaries as conventional, representing no long-term obstacle to progress, whereas pluralism emphasizes more ephemeral and transient interdisciplinary connections and underscores the autonomy of the disciplines with respect to one another. (...) Both approaches have their merits and pitfalls. Unification runs the risk of scientific imperialism, while pluralism can result in insurmountable barriers between disciplines. We made a comparison of eight distinct interdisciplinary attempts at integration of knowledge across social and natural sciences. The comparison was carried out as four pairwise comparisons: environmental economics versus ecological economics, environmental history versus historical ecology, resilience theory versus political ecology, and socio-biology versus actor-network theory. We conclude by showing that none of these prominent eight interdisciplinary fields in and of itself manages to provide, in a satisfactory way, such an integrated understanding of sustainability. We argue for pluralism and advocate complex ways of articulating divergent ontological assumptions. This is not equivalent to pursuing knowledge unification either through scientific imperialism or by catering to the requirements of narrow practical utility. It means prioritizing interdisciplinary integration by simultaneously acknowledging the role of societal and natural factors in accounting for sustainability issues. (shrink)

Interdisciplinary research within the field of sustainability studies often faces incompatible ontological assumptions deriving from natural and social sciences. The importance of this fact is often underrated and sometimes leads to the wrong strategies. We distinguish between two broad approaches in interdisciplinarity: unificationism and pluralism. Unificationism seeks unification and perceives disciplinary boundaries as conventional, representing no long-term obstacle to progress, whereas pluralism emphasizes more ephemeral and transient interdisciplinary connections and underscores the autonomy of the disciplines with respect to one another. (...) Both approaches have their merits and pitfalls. Unification runs the risk of scientific imperialism, while pluralism can result in insurmountable barriers between disciplines. We made a comparison of eight distinct interdisciplinary attempts at integration of knowledge across social and natural sciences. The comparison was carried out as four pairwise comparisons: environmental economics versus ecological economics, environmental history versus historical ecology, resilience theory versus political ecology, and socio-biology versus actor-network theory. We conclude by showing that none of these prominent eight interdisciplinary fields in and of itself manages to provide, in a satisfactory way, such an integrated understanding of sustainability. We argue for pluralism and advocate complex ways of articulating divergent ontological assumptions. This is not equivalent to pursuing knowledge unification either through scientific imperialism or by catering to the requirements of narrow practical utility. It means prioritizing interdisciplinary integration by simultaneously acknowledging the role of societal and natural factors in accounting for sustainability issues. (shrink)

According to the antirealist argument known as the pessimistic induction, the history of science is a graveyard of dead scientific theories and abandoned theoretical posits. Support for this pessimistic picture of the history of science usually comes from a few case histories, such as the demise of the phlogiston theory and the abandonment of caloric as the substance of heat. In this article, I wish to take a new approach to examining the ‘history of science as a graveyard of theories’ (...) picture. Using JSTOR Data for Research and Springer Exemplar, I present new lines of evidence that are at odds with this pessimistic picture of the history of science. When rigorously tested against the historical record of science, I submit, the pessimistic picture of the history of science as a graveyard of dead theories and abandoned posits may turn out to be no more than a philosophers’ myth. (shrink)

In this paper, I consider the pessimistic induction construed as a deductive argument (specifically, reductio ad absurdum) and as an inductive argument (specifically, inductive generalization). I argue that both formulations of the pessimistic induction are fallacious. I also consider another possible interpretation of the pessimistic induction, namely, as pointing to counterexamples to the scientific realist’s thesis that success is a reliable mark of (approximate) truth. I argue that this interpretation of the pessimistic induction fails, too. If this is correct, then (...) the pessimistic induction is an utter failure that should be abandoned by scientific anti-realists. (shrink)

There is an ongoing methodological debate in philosophy of science concerning the use of case studies as evidence for and/or against theories about science. In this paper, I aim to make a contribution to this debate by taking an empirical approach. I present the results of a systematic survey of the PhilSci-Archive, which suggest that a sizeable proportion of papers in philosophy of science contain appeals to case studies, as indicated by the occurrence of the indicator words “case study” and/or (...) “case studies.” These results are confirmed by data mined from the JSTOR database on research articles published in leading journals in the field: Philosophy of Science, the British Journal for the Philosophy of Science (BJPS), and the Journal for General Philosophy of Science (JGPS), as well as the Proceedings of the Biennial Meeting of the Philosophy of Science Association (PSA). The data also show upward trends in appeals to case studies in articles published in Philosophy of Science, the BJPS, and the JGPS. The empirical work I have done for this paper provides philosophers of science who are wary of the use of case studies as evidence for and/or against theories about science with a way to do philosophy of science that is informed by data rather than case studies. (shrink)

Is knowledge in the natural sciences discovered or constructed? For objectivists, scientific knowledge is discovered through investigations into a mind-independent, natural world. For constructivists, such knowledge is produced through negotiations among members of a professional guild. I examine the clash between the two positions and propose that scientific knowledge is the concurrent outcome from investigations into a natural world and from consensus reached through negotiations of a professional guild. Specifically, I introduce the general methodological notion, instituting science, which incorporates both (...) the discovery and the construction processes in the generation of scientific knowledge. To that end, I use a case study from the biomedical sciences to illustrate the notion. I conclude with a discussion of how this methodological notion helps to address the debate between objectivists and constructivists over the generation of scientific knowledge, and of how it compares with others who have also attempted to address the debate. (shrink)

It is widely believed that if a piece of evidence for a theory was known at the time the theory was proposed, then it does not confirm the theory as strongly as it would if the evidence had been discovered after the theory was proposed. I shall call this view the predictivist thesis. Those who have endorsed it include Leibniz (1678), Huygens (1690, preface), Whewell (1847 vol. 2, p. 64f.), Peirce (1883), Duhem (1914, ch. II, §5), Popper (1965, p. 241f.), (...) Lakatos (1970, p. 123), and Kuhn (1977, p. 322). On the other hand, the thesis has been rejected by a number of philosophers, including Mill (1872 bk. III, ch. 14, §6), Keynes (1921, p. 305), Rosenkrantz (1977, p. 169f.), Horwich (1982, pp. 108-117) and Schlesinger (1987). Others, while not rejecting the predictivist thesis, nevertheless regard the justification of the thesis as problematic; these include Hempel (1966, p. 38) and Gardner (1982). (shrink)

In his seminal The Poverty of Historicism Sir Karl Popper deployed a number of arguments to prick the pretensions of those who thought that they were, or could come to be, in possession of knowledge of the future. These ‘historicists’ assumed that they could lay bare the law of evolution of a society, and that their possession of knowledge of such a law justified political action which had the aim of removing obstacles to the progress of history. In arguing against (...) historicism Popper was clearly motivated by his interest in removing the intellectual backing for such revolutionary political practice. My first reading of PH was in the company of people who were extremely dismissive of the anti-revolutionary message, and who tended to argue that if that was the conclusion of Popper's theoretical argument, then obviously the argument was flawed. Within their context, that of the implementation of apartheid policy in South Africa, there was much to be said for this attitude. There is no doubt that Popper's message was insufficiently contextualised, or rather that he did not signpost very clearly whether he intended the anti-revolutionary political prescription to have limited or universal application. In this paper I want to reconsider some of these issues, particularly whether the truth of anti-historicism, in the sense intended by Popper, has such conservative consequences for political action. (shrink)

has offered a lovely example to motivate the intuition that a successful prediction has a kind of confirmatory significance that an accommodation lacks. This paper scrutinizes Maher's example. It argues that once the example is tweaked, the intuitive difference there between prediction and accommodation disappears. This suggests that the apparent superiority of prediction to accommodation is actually a side effect of an important difference between the hypotheses that tend to arise in each case.

Three related intuitions are explicated in this paper. The first is the idea that there must be some kind of probabilistic version of the HD-method, a ‘Hypothetico-Probabilistic (HP-) method’, in terms of something like probabilistic consequences, instead of deductive consequences. According to the second intuition, the comparative application of this method should also be functional for some probabilistic kind of empirical progress, and according to the third intuition this should be functional for something like probabilistic truth approximation. In all three (...) cases, the guiding idea is to explicate these intuitions by explicating the crucial notions as appropriate ‘concretizations’ of their deductive analogs, being ‘idealizations’. It turns out that the comparative version of the proposed HP-method amounts to the likelihood comparison (LC-) method applied to the cumulated evidence. This method turns out to be not only functional for probabilistic empirical progress but also for probabilistic truth approximation. The latter is based on a probabilistic threshold theorem constituting for this reason the analog of the deductive success theorem. (shrink)

Three related intuitions are explicated in this paper. The first is the idea that there must be some kind of probabilistic version of the HD-method, a 'Hypothetico-Probabilistic method', in terms of something like probabilistic consequences, instead of deductive consequences. According to the second intuition, the comparative application of this method should also be functional for some probabilistic kind of empirical progress, and according to the third intuition this should be functional for something like probabilistic truth approximation. In all three cases, (...) the guiding idea is to explicate these intuitions by explicating the crucial notions as appropriate 'concretizations' of their deductive analogs, being 'idealizations'. It turns out that the comparative version of the proposed HP-method amounts to the likelihood comparison method applied to the cumulated evidence. This method turns out to be not only functional for probabilistic empirical progress but also for probabilistic truth approximation. The latter is based on a probabilistic threshold theorem constituting for this reason the analog of the deductive success theorem. (shrink)

This paper addresses the question of what the nature of science is. I will first make a few preliminary historical and systematic remarks. Next, I shall give an answer to the question that has to be qualified, clarified and justified. Finally, I will compare my answer with alternative answers and draw consequences for the demarcation problem.

In Systematicity, Paul Hoyningen-Huene answers the question "What is science?" by proposing that scientific knowledge is primarily distinguished from other forms of knowledge, especially everyday knowledge, by being more systematic. "Science" is here understood in the broadest possible sense, encompassing not only the natural sciences but also mathematics, the social sciences, and the humanities. The author develops his thesis in nine dimensions in which it is claimed that science is more systematic than other forms of knowledge: regarding descriptions, explanations, predictions, (...) the defense of knowledge claims, critical discourse, epistemic connectedness, an ideal of completeness, knowledge generation, and the representation of knowledge. He compares his view with positions on the question held by philosophers from Aristotle to Nicholas Rescher. The book concludes with an exploration of some consequences of Hoyningen-Huene's view concerning the genesis and dynamics of science, the relationship of science and common sense, normative implications of the thesis, and the demarcation criterion between science and pseudo-science. (shrink)

There is widespread recognition at universities that a proper understanding of science is needed for all undergraduates. Good jobs are increasingly found in fields related to Science, Technology, Engineering, and Medicine, and science now enters almost all aspects of our daily lives. For these reasons, scientific literacy and an understanding of scientific methodology are a foundational part of any undergraduate education. Recipes for Science provides an accessible introduction to the main concepts and methods of scientific reasoning. With the help of (...) an array of contemporary and historical examples, definitions, visual aids, and exercises for active learning, the textbook helps to increase students’ scientific literacy. The first part of the book covers the definitive features of science: naturalism, experimentation, modeling, and the merits and shortcomings of both activities. The second part covers the main forms of inference in science: deductive, inductive, abductive, probabilistic, statistical, and causal. The book concludes with a discussion of explanation, theorizing and theory-change, and the relationship between science and society. The textbook is designed to be adaptable to a wide variety of different kinds of courses. In any of these different uses, the book helps students better navigate our scientific, 21st-century world, and it lays the foundation for more advanced undergraduate coursework in a wide variety of liberal arts and science courses. Selling Points Helps students develop scientific literacy—an essential aspect of _any_ undergraduate education in the 21 st century, including a broad understanding of scientific reasoning, methods, and concepts Written for all beginning college students: preparing science majors for more focused work in particular science; introducing the humanities’ investigations of science; and helping non-science majors become more sophisticated consumers of scientific information Provides an abundance of both contemporary and historical examples Covers reasoning strategies and norms applicable in all fields of physical, life, and social sciences, _as well as_ strategies and norms distinctive of specific sciences Includes visual aids to clarify and illustrate ideas Provides text boxes with related topics and helpful definitions of key terms, and includes a final Glossary with all key terms Includes Exercises for Active Learning at the end of each chapter, which will ensure full student engagement and mastery of the information include earlier in the chapter Provides annotated ‘For Further Reading’ sections at the end of each chapter, guiding students to the best primary and secondary sources available Offers a Companion Website, with: For Students: direct links to many of the primary sources discussed in the text, student self-check assessments, a bank of exam questions, and ideas for extended out-of-class projects For Instructors: a password-protected Teacher’s Manual, which provides student exam questions with answers, extensive lecture notes, classroom-ready Power Point presentations, and sample syllabi Extensive Curricular Development materials, helping any instructor who needs to create a Scientific Reasoning Course, ex nihilo. (shrink)

In response to parts I-III of G Rosen's "What is Constructive Empiricism?", "Philosophical Studies", 74, 1994, 143-178, this paper examines several construals of the position of constructive empiricism. At issue, in part, is the equation of intentional aspects of science with the intentions and opinions of scientists. In addition it is necessary to distinguish the constructive empiricist -- a philosopher holding that acceptance of theories in science need not involve belief that they are true -- from the scientific agnostic' who (...) accepts but does not believe current science. What is at stake for empiricism is a view of science that will admit it as a paradigm for rational inquiry. (shrink)

We report the results of a study that investigated the views of researchers working in seven scientific disciplines and in history and philosophy of science in regard to four hypothesized dimensions of scientific realism. Among other things, we found that natural scientists tended to express more strongly realist views than social scientists, that history and philosophy of science scholars tended to express more antirealist views than natural scientists, that van Fraassen’s characterization of scientific realism failed to cluster with more standard (...) characterizations, and that those who endorsed the pessimistic induction were no more or less likely to endorse antirealism. (shrink)

Is life a purely physical process? What is human nature? Which of our traits is essential to us? In this volume, Daniel McShea and Alex Rosenberg – a biologist and a philosopher, respectively – join forces to create a new gateway to the philosophy of biology; making the major issues accessible and relevant to biologists and philosophers alike. Exploring concepts such as supervenience; the controversies about genocentrism and genetic determinism; and the debate about major transitions central to contemporary thinking about (...) macroevolution; the authors lay out the broad terms in which we should assess the impact of biology on human capacities, social institutions and ethical values. (shrink)

The second edition of a unique introductory text, offering an account of the logical tradition in philosophy and its influence on contemporary scientific disciplines. Thinking Things Through offers a broad, historical, and rigorous introduction to the logical tradition in philosophy and its contemporary significance. It is unique among introductory philosophy texts in that it considers both the historical development and modern fruition of a few central questions. It traces the influence of philosophical ideas and arguments on modern logic, statistics, decision (...) theory, computer science, cognitive science, and public policy. The text offers an account of the history of speculation and argument, and the development of theories of deductive and probabilistic reasoning. It considers whether and how new knowledge of the world is possible at all, investigates rational decision making and causality, explores the nature of mind, and considers ethical theories. Suggestions for reading, both historical and contemporary, accompany most chapters. This second edition includes four new chapters, on decision theory and causal relations, moral and political theories, “moral tools” such as game theory and voting theory, and ethical theories and their relation to real-world issues. Examples have been updated throughout, and some new material has been added. It is suitable for use in advanced undergraduate and beginning graduate classes in philosophy, and as an ancillary text for students in computer science and the natural sciences. (shrink)

This user-friendly text covers key issues in the philosophy of science in an accessible and philosophically serious way. It will prove valuable to students studying philosophy of science as well as science students. Prize-winning author Alex Rosenberg explores the philosophical problems that science raises by its very nature and method. He skilfully demonstrates that scientific explanation, laws, causation, theory, models, evidence, reductionism, probability, teleology, realism and instrumentalism actually pose the same questions that Plato, Aristotle, Descartes, Hume, Kant and their successors (...) have grappled with for centuries. (shrink)

A widely endorsed thesis in the philosophy of science holds that if evidence for a hypothesis was not known when the hypothesis was proposed, then that evidence confirms the hypothesis more strongly than would otherwise be the case. The thesis has been thought to be inconsistent with Bayesian confirmation theory, but the arguments offered for that view are fallacious. This paper shows how the special value of prediction can in fact be given Bayesian explanation. The explanation involves consideration of the (...) reliability of the method by which the hypothesis was discovered, and thus reveals an intimate connection between the 'logic of discovery' and confirmation theory. (shrink)