K. Brad Wray

This paper argues that the field of chemistry underwent a significant change of theory in the early twentieth century, when atomic number replaced atomic weight as the principle for ordering and identifying the chemical elements. It is a classic case of a Kuhnian revolution. In the process of addressing anomalies, chemists who were trained to see elements as defined by their atomic weight discovered that their theoretical assumptions were impediments to understanding the chemical world. The only way to normalize the anomalies was to introduce new concepts, and a new conceptual understanding of what it is to be an element. In the process of making these changes, a new scientific lexicon emerged, one that took atomic number to be the defining feature of a chemical element.

This chapter discusses Kuhn’s conception of the history of science by focussing on two respects in which Kuhn is an historicist historian and philosopher of science. I identify two distinct, but related, aspects of historicism in the work of Hegel and show how these are also found in Kuhn’s work. First, Kuhn held tradition to be important for understanding scientific change and that the tradition from which a scientific idea originates must be understood in evaluating that idea. This makes Kuhn a historicist in a sense we may call conservative. Secondly, Kuhn held that there is a pattern to the development of science. In the light of the fact that he held scientific change to be law-like, we can call this second aspect of Kuhn’s historicism determinist. I discuss the relationship of Kuhn’s historicist historiography to the philosophical purposes he had for his history of science, namely to refute a conception of scientific progress as driven towards increasing truth by something like ‘the scientific method’. I argue that while this determinism refutes certain positivist conceptions of scientific change, it also requires internalism—the view that the causes of scientific change come from within science, not from outside. Consequently, Kuhn’s historiography of science contrasts with that implicit in much of post-Kuhnian science studies

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.

I examine two challenges that collaborative research raises for science. First, collaborative research threatens the motivation of scientists. As a result, I argue, collaborative research may have adverse effects on what sorts of things scientists can effectively investigate. Second, collaborative research makes it more difficult to hold scientists accountable. I argue that the authors of multi-authored articles are aptly described as plural subjects, corporate bodies that are more than the sum of the individuals involved. Though journal editors do not currently conceive of the authors of multi-authored articles this way, this conception provides us with the conceptual resources to make sense of how collaborating scientists behave.Keywords: Collaborative research; Authorship; Multi-authored articles; Responsibility; Reward system; Plural subject

By means of a citation analysis I aim to determine which scholarly journals are most important in the sub-field of philosophy of science. My analysis shows that the six most important journals in the sub-field are Philosophy of Science , British Journal for the Philosophy of Science , Journal of Philosophy , Synthese , Studies in History and Philosophy of Science , and Erkenntnis . Given the data presented in this study, there is little evidence that there is such a field as the history and philosophy of science (HPS). Rather, philosophy of science is most properly conceived of as a sub-field of philosophy.

Social epistemology is a wide-ranging field of study concerned with investigating how various social factors, practices, and institutions affect our prospects of gaining and spreading knowledge. Philosophers working in social epistemology have focused on a range of topics, including trust and testimony, the effects of social location on knowing, and whether or not groups of people can have knowledge that is not reducible to the knowledge of the individual members of the group. Much of the work in social epistemology is not concerned specifically with science and scientists but, rather, with knowing agents in general. This chapter will be concerned narrowly with the social epistemology of scientific knowledge. After a brief discussion of Thomas Kuhn's contribution to the social epistemology of science, the chapter addresses the following issues: the ideal epistemic community; collaboration and trust; social values and bias; and science policy and expertise. The chapter ends with a brief discussion of methodology in the social epistemology of science.

I revisit an older defense of scientific realism, the methodological defense, a defense developed by both Popper and Feyerabend. The methodological defense of realism concerns the attitude of scientists, not philosophers of science. The methodological defense is as follows: a commitment to realism leads scientists to pursue the truth, which in turn is apt to put them in a better position to get at the truth. In contrast, anti-realists lack the tenacity required to develop a theory to its fullest. As a consequence, they are less likely to get at the truth. My aim is to show that the methodological defense is flawed. I argue that a commitment to realism does not always benefit science, and that there is reason to believe that a research community with both realists and anti-realists in it may be better suited to advancing science. A case study of the Copernican Revolution in astronomy supports this claim.

Otto Neurath compared science to a ship at sea on which the sailors have to repair their vessel as they keep it afloat. Metascience is a ship of a similar sort. Do not worry. There are no repairs to report. But changes are being made at Metascience on an ongoing basis, even as we work to meet our production deadlines. With this, our second issue, we would like to announce some further changes with the journal.Ties Nijseen and Christi Lue who have long been responsible for many of the matters related to Metascience are handing over the responsibilities to Lucy Fleet. Ties has been the Publishing Editor for Metascience since 2009, and Christi has supported him as editorial assistant since 2012. Ties and Christi are still with Springer, but they have taken on other projects. We would like to take this opportunity to thank them for their years of service to Metascience.Lucy will be our new Publishing Editor. She has worked for Springer for 11 years. She is, in addition, ..

I evaluate the extent to which we could learn something about how we should be conducting collaborative research in science from the research on groupthink. I argue that Solomon has set us in the wrong direction, failing to recognize that the consensus in scientific specialties is not the result of deliberation. But the attention to the structure of problem-solving that has emerged in the groupthink research conducted by psychologists can help us see when deliberation could lead to problems for a research team. I argue that whenever we need to generate alternative solutions or proposals, groupthink is a genuine threat, and research teams would be wise to allow individuals opportunities to work alone. But the benefits of team work emerge when scientists seek to evaluate the various proposals generated, and determine a course of action. Then the group is less prone is groupthink, and the interaction of group members can be an epistemic asset.

David Hull accounts for the success of science in terms of an invisible hand mechanism, arguing that it is difficult to reconcile scientists' self-interestedness or their desire for recognition with traditional philosophical explanations for the success of science. I argue that we have less reason to invoke an invisible hand mechanism to explain the success of science than Hull implies, and that many of the practices and institutions constitutive of science are intentionally designed by scientists with an eye to realizing the very goals that Hull believes need to be explained by reference to an invisible hand mechanism. Thus, I reduce the scope of Hull's invisible hand explanation and supplement it by appealing to a hidden hand explanation

I examine whether or not it is apt to attribute knowledge to groups of scientists. I argue that though research teams can be aptly described as having knowledge, communities of scientists identified with research fields, and the scientific community as a whole are not capable of knowing. Scientists involved in research teams are dependent on each other, and are organized in a manner to advance a goal. Such teams also adopt views that may not be identical to the views of the individual members of the group.

I aim to clarify the relationship between the success of a theory and the truth of that theory. This has been a central issue in the debates between realists and anti-realists. Realists assume that success is a reliable indicator of truth, but the details about the respects in which success is a reliable indicator or test of truth have been largely left to our intuitions. Lewis (Synthese 129:371–380, 2001) provides a clear proposal of how success and truth might be connected, comparing a test of success of our theories to medical tests with low rates of false positives and false negatives. But, contrary to what Lewis claims, I argue that it is not enough for the realist to undercut the claim that success is not a reliable indicator of truth. Rather, the realist must show that our current best theories are likely true. Further, I argue that tests in science are unlike medical tests in a number of important ways

I present a history of Kuhn’s discovery of paradigms, one that takes account of the complexity of the discovery process. Rather than emerging fully formed in Structure , the concept paradigm emerged through a series of phases. Early criticism of Structure revealed that the role of paradigms was unclear. It was only as Kuhn responded to criticism that he finally articulated a precise understanding of the concept paradigm. In a series of publications in the 1970s, he settled on a conception of a paradigm as a concrete exemplar that functions as a guide to future research

I examine the value and limitations of Kuhn’s Structure of Scientific Revolutions. In the interests of developing a social epistemology of science, I argue that we should draw on Kuhn’s later work, published in The Road since Structure. There, Kuhn draws attention to the important role that specialty formation plays in resolving crises in science, a topic he did not discuss in Structure. I argue that we need to develop a better understanding of specialty research communities. Kuhn’s later work provides a research agenda for those who want to study scientific specialization. I briefly discuss some recent studies that promise to provide valuable insight into the social structure of science

Jon Elster and Daniel Little have criticized social scientists for appealing to a mechanism of social selection in functional explanations of social practices. Both believe that there is no such mechanism operative in the social world. I develop and defend an account of functional explanation in which a mechanism of social selection figures centrally. In addition to developing an account of social selection, I clarify what functional hypotheses purport to claim, and re-examine the role of agents’ intentions in functional explanations in an effort to show why a mechanism of social selection is indispensable to adequate functional explanations.

My aim is to evaluate a new realist strategy for addressing the pessimistic induction, Ludwig Fahrbach’s (Synthese 180:139–155, 2011) appeal to the exponential growth of science. Fahrbach aims to show that, given the exponential growth of science, the history of science supports realism. I argue that Fahrbach is mistaken. I aim to show that earlier generations of scientists could construct a similar argument, but one that aims to show that the theories that they accepted are likely true. The problem with this is that from our perspective on the history of science we know their argument is flawed. Consequently, we should not be impressed or persuaded by Fahrbach’s argument. Fahrbach has failed to identify a difference that matters between today’s theories and past theories. But realists need to find such a difference if they are to undermine the pessimistic induction

Studies of epistemic communities and collaborative research in the social sciences have deepened the understanding of how science works, and more specifically how the social dimensions of scientific practice both enable and impede social scientists in realizing their epistemic goals. Two types of studies of epistemic communities are distinguished: general theories of epistemic communities aim to construct accounts of theoretical change applicable to all social scientific specialties, whereas historical studies emphasize the contingencies that affect specific social scientific disciplines, subfields, or institutions. Although collaborative research plays a less pronounced role in the social sciences than in the natural sciences, collaboration has enabled social scientists to investigate topics that would otherwise be difficult to investigate

It has often been remarked that science is a young man's game. Thomas Kuhn, for example, claims that revolutionary changes in science are almost always initiated by either young scientists or those new to a field. I subject Kuhn's hypothesis to testing. I examine 24 revolutionary scientific figures mentioned in The Structure of Scientific Revolutions to determine if young scientists are more likely to make revolutionary discoveries than older scientists. My analysis suggests that middle-aged scientists are responsible for initiating more scientific revolutions than young scientists, given the proportion of each group in the total population of scientists. I argue that the popular myth about the correlation between youth and scientific discovery fails to take into account the proportion of young scientists in the population of scientists.