The goal of this paper is to develop a counterfactual theory of explanation. The CTE provides a monist framework for causal and non-causal explanations, according to which both causal and non-causal explanations are explanatory by virtue of revealing counterfactual dependencies between the explanandum and the explanans. I argue that the CTE is applicable to two paradigmatic examples of non-causal explanations: Euler’s explanation and renormalization group explanations of universality.

Traditionally, cognitive values have been thought of as a collective pool of considerations in science that frequently trade against each other. I argue here that a finer-grained account of the value of cognitive values can help reduce such tensions. I separate the values into groups, minimal epistemic criteria, pragmatic considerations, and genuine epistemic assurance, based in part on the distinction between values that describe theories per se and values that describe theory-evidence relationships. This allows us to clarify why these values (...) are central to science and what role they should play, while reducing the tensions among them. (shrink)

We propose a new definition of actual causes, using structural equations to model counterfactuals. We show that the definition yields a plausible and elegant account of causation that handles well examples which have caused problems for other definitions and resolves major difficulties in the traditional account.

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)

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)

Private companies provide by far the most funding for scientific research and development. Nevertheless, relatively little attention has been paid to the dynamics of industry‐funded research by philosophers of science. This paper addresses this gap by providing an overview of the major strengths and weaknesses of industry research funding, together with the existing recommendations for addressing the weaknesses. It is designed to provide a starting point for future philosophical work that explores the features of industry‐funded research, avenues for addressing concerns, (...) and strategies for making research funded by the private sector as fruitful as possible. (shrink)

My intention is to cast light on the characteristics of epistemic or fundamental research (in contrast to application-oriented research). I contrast a Baconian notion of objectivity, expressing a correspondence of the views of scientists to the facts, with a pluralist notion, involving a critical debate between conflicting approaches. These conflicts include substantive hypotheses or theories but extend to values as well. I claim that a plurality of epistemic values serves to accomplish a non-Baconian form of objectivity that is apt to (...) preserve most of the intuitions tied to the objectivity of science. For instance, pluralism is the only way to cope with the challenge of preference bias. Furthermore, the plurality of epistemic values cannot be substantially reduced by exploring the empirical success of scientific theories distinguished in light of particular such values. However, in addition to pluralism at the level of theories and value-commitments alike, scientific research is also characterized by a joint striving for consensus which I trace back to a shared epistemic attitude. This attitude manifests itself, e.g., in the willingness of scientists to subject their claims to empirical scrutiny and to respect rational argument. This shared epistemic attitude is embodied in rules adopted by the scientific community concerning general principles of dealing with knowledge claims. My contention is that pluralism and consensus formation can be brought into harmony by placing them at different levels of consideration: at the level of scientific reasoning and at the level of social conventions regarding how to deal with claims put forward within the scientific community. (shrink)

When interests and preferences of researchers or their sponsors cause bias in experimental design, data interpretation or dissemination of research results, we normally think of it as an epistemic shortcoming. But as a result of the debate on science and values, the idea that all extra-scientific influences on research could be singled out and separated from pure science is now widely believed to be an illusion. I argue that nonetheless, there are cases in which research is rightfully regarded as epistemologically (...) deficient due to the influence of preferences on its outcomes. I present examples from biomedical research and offer an analysis in terms of social epistemology. (shrink)

The aim of this paper is to address the neglected but important problem of differentiating between epistemically beneficial and epistemically detrimental dissent. By “dissent,” we refer to the act of objecting to a particular conclusion, especially one that is widely held. While dissent in science can clearly be beneficial, there might be some instances of dissent that not only fail to contribute to scientific progress, but actually impede it. Potential examples of this include the tobacco industry’s funding of studies that (...) questioned the link between smoking and lung cancer, and the attempt by the petroleum industry and other groups to cast doubt upon the conclusion that human consumption of fossil fuels contributes to global climate change. The problem of distinguishing between good and bad dissent is important because of the growing tendency of some stakeholders to attempt to delay political action by ’manufacturing doubt’. Our discussion in this paper focuses on climate science. This field, in our view, is rife with instances of bad dissent. On the basis of our discussion of climate science, we articulate a set of sufficient conditions for epistemically problematic dissent in general, which we call “the inductive risk account of epistemically detrimental dissent.”. (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)

Biased research occurs frequently in the sciences. In this paper, I will focus on one particular kind of biased research: research that is subject to sponsorship bias. I will address the following epistemological question: what precisely is epistemically wrong with biased research of this kind? I will defend the evidential account of epistemic wrongness: that is, research affected by sponsorship bias is epistemically wrong if and only if the researchers in question make false claims about the evidential support of some (...) hypothesis H by data E. I will argue that the evidential account captures the epistemic wrongness of three paradigmatic types of sponsorship bias. (shrink)

The whole drug industry campaign for mood drugs in the 1950s was to broaden to absurd limits the definition of illness.... If the facts in these ads were not untruths, then their implications often were.1Sponsorship bias occurs when a funder of scientific research has a vested interest in what claims the research supports, which consequently shapes the research or the reporting of its results to align with that interest. This article examines the relationship between sponsorship bias and misleading claims, understood (...) as claims that are not necessarily false but which encourage those exposed to them to infer false conclusions. Such claims are important insofar as being common in examples of alleged sponsorship... (shrink)

Critics of the ideal of value‐free science often assume that they must reject the distinction between epistemic and nonepistemic values. I argue that this assumption is mistaken and that the distinction can be used to clarify and defend the argument from inductive risk, which challenges the value‐free ideal. I develop the idea that the characteristic feature of epistemic values is that they promote, either intrinsically or extrinsically, the attainment of truths. This proposal is shown to answer common objections to the (...) distinction and provide a principled basis for separating legitimate from illegitimate influences of nonepistemic values in scientific inference. *Received June 2009; revised September 2009. †To contact the author, please write to: 503 S. Kedzie Hall, Michigan State University, East Lansing, MI 48824‐1032; e‐mail: [email protected]. (shrink)