Heather Douglas

This chapter begins by explaining why nonepistemic values are logically needed for reasoning in science, even in the internal stages of the process. It then bolsters the point with an examination of ways to block this necessity, all of which prove unsatisfactory. Finally, it argues that rejection of the value-free ideal does not demolish science's objectivity and that we have plenty of remaining resources with which to understand and evaluate the objectivity of science. By understanding science as value laden, we can better understand the nature of scientific controversy in many cases and even help speed resolution of those controversies.

The terms “objectivity” and “objective” are among the most used yet ill-defined terms in the philosophy of science and epistemology. Common to all the various usages is the rhetorical force of “I endorse this and you should too,” or to put it more mildly, that one should trust the outcome of the objectivity-producing process. The persuasive endorsement and call to trust provide some conceptual coherence to objectivity, but the reference to objectivity is hopefully not merely an attempt at persuasive endorsement. What, in addition to epistemological endorsement, does objectivity carry with it? Drawing on recent historical and philosophical work, I articulate eight operationally accessible and distinct senses of objectivity. While there are links among these senses, providing cohesion to the concept, I argue that none of the eight senses is strictly reducible to the others, giving objectivity its irreducible complexity.

Elijah Millgram’s book The Great Endarkenment takes philosophy to task for failing to note the kinds of creatures we are (serial hyperspecializers) and what that means for philosophy. In this commentary, I will complicate the picture he draws, while suggesting a more hopeful path forward. First, I argue that we are not actually serial hyperspecializers. Nevertheless, we are hyperspecializers, and this is the main source of the looming endarkenment. I will suggest that a proper understanding of expertise, particularly the requirement that experts (at least experts whose success is not readily assessable) be required to explicate their judgments helps to mitigate the threat of siloed expertise and endarkenment. Further, I argue that grappling directly with the institutional structures that encourage narrow and isolated hyperspecialists in academia can be a way to avoid endarkenment problems. The current landscape of academia, with its valorization of narrow disciplinary expertise, is neither necessary nor sustainable. In order to change this landscape, we need to understand how current incentives construct epistemic niches, and what we might change in order to reshape the ecology of academia.

While the Value-Free Ideal (VFI) had many precursors, it became a solidified bulwark of normative claims about scientific reasoning and practice in the mid-twentieth century. Since then, it has played a central role in the philosophy of science, first as a basic presupposition of how science should work, then as a target for critique, and now as a target for replacement. In this paper, we will argue that a narrow focus on the VFI is misguided, because the VFI coalesced in the midst of other important shifts in the relationship between science and society. In particular, the mid-twentieth century saw the acceptance of the “social contract for science,” a tacit agreement between scientists and government officials, and more broadly between science and society. It was built around three core concepts: a distinction between basic and applied science, a conception of scientific freedom that limited social responsibility for scientists, and a justification for public funding of basic science in the form of the linear model. Within the conceptual framework of the social contract for science, it is clearer both (1) why the VFI was adopted, (2) why it is difficult to replace the VFI within the old social contract, and (3) how we need to revise the social contract for science in order to replace the VFI.

Replacing the value-free ideal (VFI) for science requires attention to the broader understanding of how science in society should function. In public spaces, science needed to project the VFI in norms for science advising, science education, and science communication. This resulted in the independent science advisor model and a focus on science literacy for science education and communication. Attending to these broader implications of the VFI which structure science and society relationships is crucial if we are to properly replace the VFI with a better ideal.

A recent case in the Northern Territory of Australia has raised the issues of intra-racial rape and the legal recognition of traditional marriages between Indigenous people. The defendant in the Jamilmira case was charged with statutory rape of a 15-year-old girl. He argued that the girl’s status as his promised wife should lead to mitigation of his sentence. Members of the Northern Territory judiciary and others in the community were divided in their response to his claim. Ultimately the case led to reform of the law in relation to the recognition of traditional marriage, a response which outraged some members of the Indigenous community. In this article I examine the various representations of culture and individuals that were utilised by ‘the law’ and how these representations informed the legal response. In the process I question the limits of my own role as a ‘white middle-class feminist’ in the context of explorations of law and culture. Is there a space to become involved in these debates without being complicit in fostering racism and prejudice and without reverting to stereotypes and cultural arrogance?

In this response to Robert Hudson’s article, “Should We Strive to Make Science Bias-Free? A Philosophical Assessment of the Reproducibility Crisis,” we identify three ways in which he misrepresents our work: he conflates value-ladenness with bias; he describes our view as one in which values are the same as evidential factors; and he creates a false dichotomy between two ways that values could be considered in science for policy. We share Hudson’s concerns about promoting scientific reproducibility and reducing bias in science, but we reject his view that the value-free ideal provides helpful guidance for addressing these issues.

Science is one of the most important forces in contemporary society. The most reliable source of knowledge about the world, science shapes the technological possibilities before us, informs public policy, and is crucial to measuring the efficacy of public policy. Yet it is not a simple repository of facts on which we can draw. It is an ongoing process of evidence gathering, discovery, contestation, and criticism. I will argue that an understanding of the nature of science and the scientific process should be the central goal for scientific literacy, rather than a grasp of specific facts. With this understanding of science as a backdrop, the paper then turns to modes for citizen engagement with science. This paper articulates different ways citizens can engage with science, including four avenues for legitimate contestation of scientific claims. I then look more closely at contestation of science on the basis of values. That science can be legitimately contested by non-experts on a range of grounds means that science communication should not just aim at getting citizens to accept scientific claims, but rather to engage in a more robust two-way conversation about science.

Elijah Millgram’s book The Great Endarkenment takes philosophy to task for failing to note the kinds of creatures we are (serial hyperspecializers) and what that means for philosophy. In this commentary, I will complicate the picture he draws, while suggesting a more hopeful path forward. First, I argue that we are not actually serial hyperspecializers. Nevertheless, we are hyperspecializers, and this is the main source of the looming endarkenment. I will suggest that a proper understanding of expertise, particularly the requirement that experts (at least experts whose success is not readily assessable) be required to explicate their judgments helps to mitigate the threat of siloed expertise and endarkenment. Further, I argue that grappling directly with the institutional structures that encourage narrow and isolated hyperspecialists in academia can be a way to avoid endarkenment problems. The current landscape of academia, with its valorization of narrow disciplinary expertise, is neither necessary nor sustainable. In order to change this landscape, we need to understand how current incentives construct epistemic niches, and what we might change in order to reshape the ecology of academia.

The importance of science for guiding policy decisions has been an increasingly central feature of policy-making for much of the past century. But which science we have available to us and what counts as adequate science for policy-making shapes substantially the specific impact science has on policy decisions. Policy influences which science we pursue and how we pursue it in practice, as well as how science ultimately informs policy. Values inform our choices in these areas, as values shape the research agendas scientists pursue, the issues debated as we decide on policy, and what counts as sufficient warrant in any given case. And what we value is shaped by our empirical understanding of what is, what is...

The risk regulation process has been traditionally conceived as having two components: a consultation of the experts concerning the magnitude of risk and a negotiated decision on whether and how to reduce that risk. The first component is generally thought to be free of the contentious value judgments that often characterize the second component. In examining the recent controversy over dioxin regulation, I argue that the first component is not value-free. I review three areas of science important to dioxin regulation: epidemiological studies, laboratory animal studies, and biochemical studies. I show how problems of interpretation arise for each area of science that prevent a clear-cut answer to the question: what dose of dioxins is safe for humans? Because of significant uncertainties in how to interpret these studies, there is significant risk that one will err in the interpretation. In order to judge what risk of error to accept, one needs to consider and weigh the consequences of one's judgments, whether epistemic or non-epistemic. Weighing non-epistemic consequences requires the use of non-epistemic values. Thus, non-epistemic values, or the kind that are important in risk management, have an important and legitimate role to play in the judgments required to perform and interpret the dioxin studies. The risk assessment component of the risk regulation process cannot be claimed to be value-free and the process must be altered to accommodate a value-laden science.

Although prediction has been largely absent from discussions of explanation for the past 40 years, theories of explanation can gain much from a reintroduction. I review the history that divorced prediction from explanation, examine the proliferation of models of explanation that followed, and argue that accounts of explanation have been impoverished by the neglect of prediction. Instead of a revival of the symmetry thesis, I suggest that explanation should be understood as a cognitive tool that assists us in generating new predictions. This view of explanation and prediction clarifies what makes an explanation scientific and why inference to the best explanation makes sense in science. *Received August 2009; revised September 2009. †To contact the author, please write to: Department of Philosophy, University of Tennessee, 801 McClung Tower, Knoxville, TN 37920‐0480; e‐mail: [email protected].

The terms ``objectivity'''' and ``objective'''' are among the mostused yet ill-defined terms in the philosophy of science and epistemology. Common to all thevarious usages is the rhetorical force of ``I endorse this and you should too'''', orto put it more mildly, that one should trust the outcome of the objectivity-producing process.The persuasive endorsement and call to trust provide some conceptual coherenceto objectivity, but the reference to objectivity is hopefully not merely an attemptat persuasive endorsement. What, in addition to epistemological endorsement,does objectivity carry with it? Drawing on recent historical and philosophical work,I articulate eight operationally accessible and distinct senses of objectivity.While there are links among these senses, providing cohesion to the concept, I argue thatnone of the eight senses is strictly reducible to the others, giving objectivity itsirreducible complexity.

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.