A reading is offered of Carl Hempel’s and Thomas Kuhn’s positions on, and disagreements about, rationality in science that relates these issues to the debate between W.V. Quine and Rudolf Carnap on the analytic/synthetic distinction.

Abstract Criteria of scientific value are of different kinds. This paper concerns ultimate criteria, i.e. the axiology of science. Most ultimate criteria are multi?dimensional. This gives rise to an aggregation problem, which cannot be adequately solved with reference to attitudes and behaviour within the scientific community. Therefore, in many cases, there is no fact of the matter as to whether one theory is better than another. This, in turn, creates problems for methodology.

This article discusses Sven Ove Hansson’s corpus model for the influence of values (in particular, non-epistemic ones) in the hypothesis acceptance/rejection phase of scientific inquiry. This corpus model is based on Hansson’s concepts of scientific corpus and science ‘in the large sense’. I first present Hansson’s corpus model of value influence with some introductory comments about its origins, a detailed presentation of the model with a new terminology, an analysis of its limits, and an appreciation of its handling of controversial (...) non-epistemic values. I conclude that it is a very good candidate for managing value influence, because contrary to other models in the literature it is fairly simple, it provides a universal and systematic procedure for dealing with values, and it syste- matically preserves the epistemic integrity of science. I then study some difficulties associated with the model’s central feature of taking the maximum level of evidence required by the applications of a claim in order for the latter to enter the scientific corpus: the difficulty to identify this maximum requirement; the non-optimality of this requirement with respect to other less demanding requirements; the potentially detrimental consequences of the preference for false negatives over false positives on which it relies; and the issue of whether there can nevertheless be requirements higher than this maximum. I show that these issues may potentially challenge the corpus model. Finally, I call for empirical work (in particular, an investigation of scientists’ and engineers’ own normative views) in order to better assess these issues. (shrink)

The argument from inductive risk is considered to be one of the strongest challenges for value-free science. A great part of its appeal lies in the idea that even an ideal epistemic agent—the “perfect scientist” or “scientist qua scientist”—cannot escape inductive risk. In this paper, I scrutinize this ambition by stipulating an idealized Bayesian decision setting. I argue that inductive risk does not show that the “perfect scientist” must, descriptively speaking, make non-epistemic value-judgements, at least not in a way that (...) undermines the value-free ideal. However, the argument is more successful in showing that there are cases where the “perfect scientist” should, normatively speaking, use non-epistemic values. I also show that this is possible without creating problems of illegitimate prescription and wishful thinking. Thus, while inductive risk does not refute value-freedom completely, it still represents a powerful critique of value-free science. (shrink)

Two metascientific concepts that have been ― and still are ― object of philosophical analysis are the concepts of model and theory. But while the concept of scientific theory was one of the concepts to which philosophers of science devoted most attention during the 20th century, it is only in recent decades that the concept of scientific model has come to occupy a central position in philosophical reflection. However, it has done so in such a way that, at present, as (...) Jim Bogen states in the back cover of the book Scientific Models in the Philosophy of Science, by Daniela Bailer-Jones, “[t]he standard philosophical literature on the role of models in scientific reasoning is voluminous, disorganized, and confusing”. In spite of this, one of the axes that would allow us to organize at least part of this literature, and with which Bailer-Jones’ book closes, is that which is identified as one of the “contemporary philosophical issues: how theories and models relate to each other” (Bailer-Jones 2009, p. 208).That is why, in this introduction to the special issues of Metatheoria devoted to the topic of “Models and Theories in Biology”, we will present the main advances that have been made in the philosophical analysis of the concepts of model and theory in general and in biology in particular, and we will also do the same with the answers that have been given to the problem of "how theories and models relate to each other”. (shrink)

The paper deals with the interrelations between the philosophy, sociology and historiography of science in Thomas Kuhn’s theory of scientific development. First, the historiography of science provides the basis for both the philosophy and sociology of science in the sense that the fundamental questions of both disciplines depend on the principles of the form of historiography employed. Second, the fusion of the sociology and philosophy of science, as advocated by Kuhn, is discussed. This fusion consists essentially in a replacement of (...) methodological rules by cognitive values that influence the decisions of scientific communities. As a consequence, the question of the rationality of theory choice arises, both with respect to the actual decisions and to the possible justification of cognitive values and their change. (shrink)

Summary The paper deals with the interrelations among philosophy, sociology, and historiography of science in Thomas Kuhn's theory of scientific development. First, historiography of science provides the basis for both philosophy and sociology of science in the sense that the fundamental questions of both disciplines depend on the principles of the form of historiography employed. Second, the fusion of sociology and philosophy of science, as advocated by Kuhn, is discussed. This fusion consists essentially in a replacement of methodological rules by (...) cognitive values that influence the decisions of scientific communities. As a consequence, the question of the rationality of theory choice arises, both with respect to the actual decisions and to the possible justification of cognitive values and their change. (shrink)

According to a widespread view, Thomas Kuhn’s model of scientific development would relegate rationality to a second plane, openly flirting with irrationalist positions. The intent of this article is to clarify this aspect of his thinking and refute this common interpretation. I begin by analysing the nature of values in Kuhn’s model and how they are connected to rationality. For Kuhn, a theory is chosen rationally when: i) the evaluation is based on values characteristic of science; ii) a theory is (...) considered better the more it manifests these values; and iii) the scientist chooses the best-evaluated theory. The second part of this article deals with the thesis of the variability of values. According to Kuhn, the examples through which epistemic values are presented vary for each person, and for this reason individuals interpret these criteria differently. Consequently, two scientists, using the same values, can come to a rational disagreement over which theory to choose. Finally, I point out the limitations of this notion of rationality for the explanation of consensus formation, and the corresponding demand for a sociological theory that reconnects individual rationality with convergence of opinions. (shrink)

A aceitação ou a escolha de uma teoria científica por parte de uma comunidade científica é um evento ou processo central na dinâmica científica. É, também, um evento ou processo complexo –já que dele participam as teorias, a experiência e alguma forma de relação inferencial entre a teoria e a experiência.

Much of the literature on values in science is limited in its perspective because it focuses on the role of values in individual scientists’ decision making, thereby ignoring the context of scientific collaboration. I examine the epistemic structure of scientific collaboration and argue that it gives rise to two arguments showing that moral and social values can legitimately play a role in scientists’ decision to accept something as scientific knowledge. In the case of scientific collaboration some moral and social values (...) are properly understood to be extrinsic epistemic values, that is, values that promote the attainment of scientific knowledge. (shrink)

In addition to purely practical values, cognitive values also figure into scientific deliberations. One way of introducing cognitive values is to consider the cognitive value that accrues to the act of accepting a hypothesis. Although such values may have a role to play, such a role does not exhaust the significance of cognitive values in scientific decision-making. This paper makes a plea for consideration of epistemic value —that is, value attaching to a state of belief—and defends the notion of cognitive (...) epistemic value against some criticisms that have been raised. A stability requirement for epistemic value functions is argued for on the basis of considerations of diachronic coherence. This stability requirement is sufficient to obtain the Value of Learning Theorem, which says that the expected utility of cost-free learning cannot be negative. This holds also for cognitive epistemic values, provided that the stability requirement is met. (shrink)

: As a response to the critics of feminist science studies I argue that it is possible to formulate empirical hypotheses about gender ideology in the practice of the physical sciences without (1) reinforcing stereotypes about women and mathematical sciences or (2) assuming at the outset that the area of physics under investigation is methodologically suspect. I will then critically evaluate two case studies of gender ideology in the practice of the physical sciences. The case studies fail to show that (...) gender ideologies have influenced the practice of the physical sciences in a profound way--not because it is impossible to conceive how gender ideologies could influence the practice of the physical sciences even in a profound way--but because they do not provide the right kind of evidence. This, however, leaves open the possibility that future studies might provide such evidence. (shrink)

For any normative domain, we can theorize about what is good in that domain. Such theories include utilitarianism, a view about what is good morally. But there are many domains other than the moral; these include the prudential, the aesthetic, and the intellectual or epistemic. In this last domain, it is good to be knowledgeable and bad to ignore evidence, quite apart from the morality, prudence, and aesthetics of these things. This dissertation builds a theory that stands to the epistemic (...) domain as utilitarianism stands to the moral domain. It builds an epistemic value theory. (shrink)

Lists foreground multiplicity: both of objects to be pursued and, for distant objects, of far-flung networks enabling their pursuit. The future-oriented or projective list stretches such networks not only around the world but forward through time. Research agendas are one kind of future-oriented, projective list. Sketching how such lists have functioned over time, from Francis Bacon's “The New World of Sciences, or Desiderata” to today's desiderata lists, suggests how an early modern model of imperial expansion has shaped, in unintended ways, (...) a scientific rhetoric of collaborative advance on shared targets. (shrink)

The function and legitimacy of values in decision making is a critically important issue in the contemporary analysis of science. It is particularly relevant for some of the more application-oriented areas of science, specifically decision-oriented science in the field of regulation of technological risks. Our main objective in this paper is to assess the diversity of roles that non-cognitive values related to decision making can adopt in the kinds of scientific activity that underlie risk regulation. We start out, first, by (...) analyzing the issue of values with the help of a framework taken from the wider philosophical debate on science and values. Second, we study the principal conceptualizations used by scholars who have applied them to numerous case studies. Third, we appraise the links between those conceptualizations and learning processes in decision-oriented science. In this, we recur to the concept of methodological learning, i.e., learning about the best methodologies for generating knowledge that is useful for science-based regulatory decisions. The main result of our analysis is that non-cognitive values can contribute to methodological improvements in science in three principal ways: as basis for critical analysis, for contextualizing methodologies, and for establishing the burden of proof. (shrink)

Once an experiment is done, the observations have been made and the data have been analyzed, what should scientists communicate to the world at large, and how should they do it? This, I will argue, is an intricate question, and one that philosophers can make a contribution to. I will illustrate these points by reference to the debate between Fisher and Neyman & Pearson in the 1950s, which I take to be, at heart, a debate about norms of scientific communication. (...) I will argue that scientists need a richer set of tools for communicating epistemic states that may be very nuanced, and will point to way in which philosophers can contribute. (shrink)

Science is praxis relevant to the extent that it guides goal-directed action by telling us how to act in order to achieve the goals. Investigations aiming at high praxis relevance are performed in various disciplines under names such as clinical trials, evaluation research, intervention research and social experiments. In this contribution, the notion of (direct) praxis relevance is delineated, and it is distinguished from related properties of science such as those of being applied and being practically useful in a wider (...) sense. Recommendations for the achievement of praxis relevance are offered in the form of five principles: the prerogative of direct experiments, minimized theory-induced uncertainty, multiple approximations, causal chain decomposition and successive improvements. (shrink)