1. Deductive and Inductive Inference. Within the traditional treatments of scientific method, e.g., in and, it was customary to divide scientific inference into two parts: deductive and inductive. Deductive inference was taken to mean the activity of deducing theorems from postulates and definitions, whereas inductive inference represented the activity of constructing a general statement from a set of particular “facts.” Deductive inference was relegated to the mathematical sciences, and inductive inference to the empirical sciences. As a consequence, the whole of (...) science was split into two quite distinct parts: deductive science was conceived to start with precise axioms, postulates, and definitions, and its method consisted in drawing inferences from these “givens” in such a way that if the original assumptions are taken as true, then the theorems must be taken as true also. The obligation behind this “must” of the mathematical sciences was an obligation based on strict rules of deductive inference; in the earlier analyses, it was supposed that these rules were all aspects of the general theory of the syllogism, as it was described in an almost complete form in but in later work the rules have been formalized in more general terms. Inductive inference, on the other hand, was supposed to start with observed facts; these facts, or “data,” were presumably given by the senses, and described particular aspects of the external world. If the facts were given in a certain way, then the empirical scientist could “infer” a generalized description; this generalization had the characteristic that if it were granted as true, then all the facts could be deduced as consequences. The inductive process admittedly does not lead to unique generalizations, and the philosopher of science searched for other defining characteristics of good inference, such as “simplicity” and “convenience.” These empirical generalizations were taken to be “descriptions of the phenomenal world of the scientist”; a further inductive step might be taken by constructing a set of very general principles out of the more specialized generalizations within specific research problems. These “higher” inductive inferences were regarded as “theories,” which could be studied by themselves within the method of deductive inference. The scientist was then described as “checking” theory by determining whether or not the predicted consequences deduced from theory actually hold in the phenomenal world. (shrink)

Kevin Elliott and others separate two common arguments for the legitimacy of societal values in scientific reasoning as the gap and the error arguments. This article poses two questions: How are these two arguments related, and what can we learn from their interrelation? I contend that we can better understand the error argument as nested within the gap because the error is a limited case of the gap with narrower features. Furthermore, this nestedness provides philosophers with conceptual tools for analyzing (...) more robustly how values pervade science. (shrink)

I address options for providing scientific policy advice and explore the relation between scientific knowledge and political, economic and moral values. I argue that such nonepistemic values are essential for establishing the significance of questions and the relevance of evidence, while, on the other hand, such social choices are the prerogative of society. This tension can be resolved by recognizing social values and identifying them as separate premises or as commissions while withholding commitment to them, and by elaborating a plurality (...) of policy packages that envisage the implementation of different social goals. There are limits to upholding the value-free ideal in scientific research. But by following the mentioned strategy, science can give useful policy advice by leaving the value-free ideal largely intact. Such scientific restraint avoids the risk of appearing to illegitimately impose values on the public and could make the advice given more trustworthy. (shrink)

This Element introduces the philosophical literature on values in science by examining four questions: How do values influence science? Should we actively incorporate values in science? How can we manage values in science responsibly? What are some next steps for those who want to help promote responsible roles for values in science? It explores arguments for and against the “value-free ideal” for science and concludes that it should be rejected. Nonetheless, this does not mean that value influences are always acceptable. (...) The Element explores a range of strategies for distinguishing between appropriate and inappropriate value influences. It concludes by proposing an approach for managing values in science that relies on justifying, prioritising, and implementing norms for scientific research practices and institutions. (shrink)

: A central claim of Longino's contextual empiricism is that scientific inquiry, even when "properly conducted", lacks the capacity to screen out the influence of contextual values on its results. I'll show first that Longino's attack against the epistemic integrity of science suffers from fatal empirical weaknesses. Second I'll explain why Longino's practical proposition for suppressing biases in science, drawn from her contextual empiricism, is too demanding and, therefore, unable to serve its purpose. Finally, drawing on Bourdieu's sociological analysis of (...) scientific communities, I'll sketch an alternative view of scientific practice reconciling a thoroughly social view of science (such as Longino's) with a defense of its epistemic integrity. (shrink)

The question of the relationship of the making of value judgments in a typically ethical sense to the methods and procedures of science has been discussed in the literature at least to that point which e. e. cummings somewhere refers to as “The Mystical Moment of Dullness.” Nevertheless, albeit with some trepidation, I feel that something more may fruitfully be said on the subject.

The role of values in scientific research has become an important topic of discussion in both scholarly and popular debates. Pundits across the political spectrum worry that research on topics like climate change, evolutionary theory, vaccine safety, and genetically modified foods has become overly politicized. At the same time, it is clear that values play an important role in science by limiting unethical forms of research and by deciding what areas of research have the greatest relevance for society. Deciding how (...) to distinguish legitimate and illegitimate influences of values in scientific research is a matter of vital importance.Recently, philosophers of science have written a great deal on this topic, but most of their work has been directed toward a scholarly audience. This book makes the contemporary philosophical literature on science and values accessible to a wide readership. It examines case studies from a variety of research areas, including climate science, anthropology, chemical risk assessment, ecology, neurobiology, biomedical research, and agriculture. These cases show that values have necessary roles to play in identifying research topics, choosing research questions, determining the aims of inquiry, responding to uncertainty, and deciding how to communicate information. Kevin Elliott focuses not just on describing roles for values but also on determining when their influences are actually appropriate. He emphasizes several conditions for incorporating values in a legitimate fashion, and highlights multiple strategies for fostering engagement between stakeholders so that value influences can be subjected to careful and critical scrutiny. (shrink)

The distinction between basic and applied research is notoriously vague, despite its frequent use in science studies and in science policy. In most cases it is based on such pragmatic factors as the knowledge and intentions of the investigator or the type of research institute. Sometimes the validity of the distinction is denied altogether. This paper suggests that there are two ways of distinguishing systematically between basic and applied research: (i) in terms of the utilities that define the aims of (...) inquiry, and (ii) by reference to the structure of the relevant knowledge claims. An important type of applied research aims at results that are expressed by techical norms (in von Wright's sense): if you wish to achieveA, and you believe you are in a situationB, then you should doX. This conception of design sciences allows us to re-evaluate many issues in the history, philosophy, and ethics of science. (shrink)

Forty-three years ago Max Weber observed that “the belief in the value of scientific truth is not derived from nature but is a product of definite cultures.” We may now add: and this belief is readily transmuted into doubt or disbelief. The persistent development of science occurs only in societies of a certain order, subject to a peculiar complex of tacit presuppositions and institutional constraints. What is for us a normal phenomenon which demands no explanation and secures many ‘self-evident’ cultural (...) values, has been in other times and still is in many places abnormal and infrequent. The continuity of science requires the active participation of interested and capable persons in scientific pursuits. This support of science is assured only by appropriate cultural conditions. It is, then, important to examine those controls which motivate scientific careers, which select and give prestige to certain scientific disciplines and reject or blur others. It will become evident that changes in institutional structure may curtail, modify or possibly prevent the pursuit of science. (shrink)

A century ago, nearly all of those who wrote about the nature of science would have been in agreement that science ought to be “value‐free.” This had been a particular emphasis on the part of the first positivists, as it would later be on the part of their twentieth‐century successors. Science, so it was said, deals with facts, and facts and values are irreducibly distinct. Facts are objective; they are what we seek in our knowledge of the world. Values are (...) subjective; they bear the mark of human interest; they are the radically individual products of feeling and desire. Fact and value cannot, therefore, mix. Value cannot be inferred from fact; fact ought not be influenced by value. There were philosophers, notably some in the Kantian tradition, who viewed the relation of the human individual to the universalist aspirations of science rather differently. But the legacy of three centuries of largely empiricist reflection on the “new” sciences ushered in by Galileo and his successors was as unqualified in its distrust of value as in its extolling of the virtues of fact (see galileo). (shrink)

Abstract: Philosophy is often conceived in the Anglophone world today as a subject that focuses on questions in particular “core areas,” pre-eminently epistemology and metaphysics. This article argues that the contemporary conception is a new version of the scholastic “self-indulgence for the few” of which Dewey complained nearly a century ago. Philosophical questions evolve, and a first task for philosophers is to address issues that arise for their own times. The article suggests that a renewal of philosophy today should turn (...) the contemporary conception inside out, attending to and developing further the valuable work being done on the supposed “periphery” and attending to the “core areas” only insofar as is necessary to address genuinely significant questions. (shrink)

While it is widely acknowledged that science is not “free” of non-epistemic values, there is disagreement about the roles that values can appropriately play. Several have argued that non-epistemic values can play important roles in modeling decisions, particularly in addressing uncertainties ; Risbey 2007; Biddle and Winsberg 2010; Winsberg : 111-137, 2012); van der Sluijs 359-389, 2012). On the other hand, such values can lead to bias ; Bray ; Oreskes and Conway 2010). Thus, it is important to identify when (...) it is legitimate to appeal to non-epistemic values in modeling decisions. An approach is defended here whereby such value judgments are legitimate when they promote democratically endorsed epistemological and social aims of research. This framework accounts for why it is legitimate to appeal to non-epistemic values in a range of modeling decisions, while addressing concerns that the presence of such values will lead to bias or give scientists disproportionate power in deciding what values ought to be endorsed. (shrink)

There is now a general consensus amongst philosophers in the values in science literature that values necessarily play a role in core areas of scientific inquiry. We argue that attention should now be turned from debating the value-free ideal to delineating legitimate from illegitimate influences of values in science, a project we dub “The New Demarcation Problem.” First, we review past attempts to demarcate the uses of values and propose a categorization of the strategies by where they seek to draw (...) legitimacy from. Next, we propose a set of desiderata for what we take to be a satisfactory solution and present a case study where conflicting sets of values clearly impinge on science, but where the legitimacy of their influence is ambiguous. We use these desiderata and the case study to illustrate what we take to be the strengths and weaknesses of current strategies. To be clear, our goal is not to answer the question we pose, but to articulate a framework within which a solution can be judged. (shrink)

The controversy over the old ideal of “value-free science” has cooled significantly over the past decade. Many philosophers of science now agree that even ethical and political values may play a substantial role in all aspects of scientific inquiry. Consequently, in the last few years, work in science and values has become more specific: Which values may influence science, and in which ways? Or, how do we distinguish illegitimate from illegitimate kinds of influence? In this paper, I argue that this (...) problem requires philosophers of science to take a new direction. I present two case studies in the influence of values on scientific inquiry: feminist values in archaeology and commercial values in pharmaceutical research. I offer a preliminary assessment of these cases, that the influence of values was legitimate in the feminist case, but not in the pharmaceutical case. I then turn to three major approaches to distinguish legitimate from illegitimate influences of values, including the distinction between epistemic and non-epistemic values and Heather Douglas’ distinction between direct and indirect roles for values. I argue that none of these three approaches gives an adequate analysis of the two cases. In the concluding section, I briefly sketch my own approach, which draws more heavily on ethics than the others, and is more promising as a solution to the current problem. This is the new direction in which I think science and values should move. (shrink)

It is argued that we need a richer version of Bayesian decision theory, admitting both subjective and objective probabilities and providing rational criteria for choice of our prior probabilities. We also need a theory of tentative acceptance of empirical hypotheses. There is a discussion of subjective and of objective probabilities and of the relationship between them, as well as a discussion of the criteria used in choosing our prior probabilities, such as the principles of indifference and of maximum entropy, and (...) the simplicity ranking of alternative hypotheses. (shrink)

The technological sciences have at least six defining characteristics that distinguish them from the other sciences. They have human-made rather than natural objects as their study objects, include the practice of engineering design, define their study objects in functional terms, evaluate these study objects with category-specified value statements, employ less far-reaching idealizations than the natural sciences, and do not need an exact mathematical solution when a sufficiently close approximation is available. In combination, the six characteristics are sufficient to show that (...) the technological sciences are neither branches nor applications of the natural sciences, but form a different group of sciences with specific characteristics of their own.Keywords: Technological sciences; Technology; Functional concepts; Idealization; Design. (shrink)

In pure science, the standard approach to non-epistemic values is to exclude them as far as possible from scientific deliberations. When science is applied to practical decisions, non-epistemic values cannot be excluded. Instead, they have to be combined with scientific information in a way that leads to practically optimal decisions. A normative model is proposed for the processing of information in both pure and applied science. A general-purpose corpus of scientific knowledge, with high entry requirements, has a central role in (...) this model. Due to its high entry requirements, the information that it contains is sufficiently reliable for the vast majority of practical purposes. However, for some purposes, the corpus needs to be supplemented with additional information, such as scientific indications of danger that do not satisfy the entry requirements for the corpus. The role of non-epistemic values in the evaluation of scientific information should, as far as possible, be limited to determining the level of evidence required for various types of practical decisions. (shrink)

The role of scientists as experts is crucial to public policymaking. However, the expert role is contested and unsettled in both public and scholarly discourse. In this paper, I provide a systematic account of the role of scientists as experts in policymaking by examining whether there are any normatively relevant differences between this role and the role of scientists as researchers. Two different interpretations can be given of how the two roles relate to each other. The separability view states that (...) there is a normatively relevant difference between the two roles, whereas the inseparability view denies that there is such a difference. Based on a systematic analysis of the central aspects of the role of scientists as experts – that is, its aim, context, mode of output, and standards, I propose a moderate version of the separability view. Whereas the aim of scientific research is typically to produce new knowledge through the use of scientific method for evaluation and dissemination in internal settings, the aim of the expert is to provide policymakers and the public with relevant and applicable knowledge that can premise political reasoning and deliberation. (shrink)

In recent papers and a book, Heather Douglas has expanded on the well-known argument from inductive risk, thereby launching an influential contemporary critique of the value-free ideal for science. This paper distills Douglas’s critique into four major claims. The first three claims provide a significant challenge to the value-free ideal for science. However, the fourth claim, which delineates her positive proposal to regulate values in science by distinguishing direct and indirect roles for values, is ambiguous between two interpretations, and both (...) have weaknesses. Fortunately, two elements of Douglas’s work that have previously received much less emphasis provide resources for developing a more promising approach for regulating values in science. (shrink)

_Current Controversies in Values and Science_ asks ten philosophers to debate five questions that are driving contemporary work in this important area of philosophy of science. The book is perfect for the advanced student, building up her knowledge of the foundations of the field while also engaging its most cutting-edge questions. Introductions and annotated bibliographies for each debate, preliminary descriptions of each chapter, study questions, and a supplemental guide to further controversies involving values in science help provide clearer and richer (...) snapshots of active controversies for all readers._ _. (shrink)

Douglas proposes a new ideal in which values serve an essential function throughout scientific inquiry, but where the role values play is constrained at key points, protecting the integrity and objectivity of science.

A feminist primer for philosophers of science -- The legacy of twentieth century philosophy of science -- What feminist science studies can offer -- Challenges from every direction -- The prospects of twenty-first century philosophy of science.