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.

The maze and the masses -- Democracy as the rule of the dumb many? -- A selective genealogy of the epistemic argument for democracy -- First mechanism of democratic reason: inclusive deliberation -- Epistemic failures of deliberation -- Second mechanism of democratic reason: majority rule.

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)

Although epistemic values have become widely accepted as part of scientific reasoning, non-epistemic values have been largely relegated to the "external" parts of science (the selection of hypotheses, restrictions on methodologies, and the use of scientific technologies). I argue that because of inductive risk, or the risk of error, non-epistemic values are required in science wherever non-epistemic consequences of error should be considered. I use examples from dioxin studies to illustrate how non-epistemic consequences of error can and should be considered (...) in the internal stages of science: choice of methodology, characterization of data, and interpretation of results. (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.

There is a growing consensus among philosophers of science that core parts of the scientific process involve non-epistemic values. This undermines the traditional foundation for public trust in science. In this article I consider two proposals for justifying public trust in value-laden science. According to the first, scientists can promote trust by being transparent about their value choices. On the second, trust requires that the values of a scientist align with the values of an individual member of the public. I (...) argue that neither of these proposals work and suggest an alternative that does better. When scientists must appeal to values in the course of their research, they should appeal to democratic values: the values of the public or its representatives. (shrink)

This book brings together eleven case studies of inductive risk-the chance that scientific inference is incorrect-that range over a wide variety of scientific contexts and fields. The chapters are designed to illustrate the pervasiveness of inductive risk, assist scientists and policymakers in responding to it, and productively move theoretical discussions of the topic forward.

After raising some minor philosophical points about Kevin Elliott’s A Tapestry of Values (2017), I argue that we should expand on the themes raised in the book and that philosophers of science need to pay as much attention to the loom of science (i.e., the institutional structures which guide the pursuit of science) as the tapestry of science. The loom of science includes such institutional aspects as patents, funding sources, and evaluation regimes that shape how science gets pursued, and that (...) attending to these aspects will enable us to provide more robust guidance on the values that infuse the tapestry of 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)

Drug regulation is fraught with inductive risk. Regulators must make a prediction about whether or not an experimental pharmaceutical will be effective and relatively safe when used by typical patients, and such predictions are based on a complex, indeterminate, and incomplete evidential basis. Such inductive risk has important practical consequences. If regulators reject an experimental drug when it in fact has a favourable benefit/harm profile, then a valuable intervention is denied to the public and a company’s material interests are needlessly (...) thwarted. Conversely, if regulators approve an experimental drug when it in fact has an unfavourable benefit/harm profile, then resources are wasted, people are needlessly harmed, and other potentially more effective treatments are underutilized. Given that such regulatory decisions have these practical consequences, non-epistemic values about the relative importance of these consequences impact the way such regulatory decisions are made (similar to the analysis of laboratory studies on the toxic effects of dioxins presented in Douglas [2000]). To balance the competing demands of the pertinent non-epistemic values, regulators must perform what I call an “inductive risk calculus.” At least in the American context this inductive risk calculus is not well-managed. (shrink)

The focus of this chapter will be on the epistemic and normative questions at issue in debates about cancer screening, with a special focus on mammography as a case study. Such questions include: How do we know who needs to be screened? What are the benefits and harms of cancer screening, and what is the quality of evidence for each? How ought we to measure and compare these benefits and harms? What are the sources of uncertainty about our estimates of (...) benefit and harm? Why are such issues so contested? What are the major drivers of dissent and consensus on the data and their interpretation? How, if at all, do values play a role in debates surrounding mammography screening? In sum: In what ways does inductive risk, broadly conceived, 1 come into play in the science behind cancer screening, and mammography screening in particular? (shrink)