Heather Douglas

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

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.

There is considerable disagreement about the epistemic value of novel predictive success, i.e. when a scientist predicts an unexpected phenomenon, experiments are conducted, and the prediction proves to be accurate. We survey the field on this question, noting both fully articulated views such as weak and strong predictivism, and more nascent views, such as pluralist reasons for the instrumental value of prediction. By examining the various reasons offered for the value of prediction across a range of inferential contexts , we can see that neither weak nor strong predictivism captures all of the reasons for valuing prediction available. A third path is presented, Pluralist Instrumental Predictivism; PIP for short

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 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

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].

Although a strict dichotomy between facts and values is no longer accepted, less attention has been paid to the roles values should play in our acceptance of factual statements, or scientific descriptive claims. This paper argues that values, whether cognitive or ethical, should never preclude or direct belief on their own. Our wanting something to be true will not make it so. Instead, values should only be used to consider whether the available evidence provides sufficient warrant for a claim. This argument is made for all relevant values, including cognitive, ethical, and social values. The rational integrity of science depends not on excluding some values and including others in the reasoning process, but of constraining all values to their proper role in belief acceptance.

How should we understand scientific progress? Kuhn famously discussed science as its own internally driven venture, structured by paradigms. He also famously had a problem describing progress in science, as problem-solving ability failed to provide a clear rubric across paradigm change—paradigm changes tossed out problems as well as solving them. I argue here that much of Kuhn’s inability to articulate a clear view of scientific progress stems from his focus on pure science and a neglect of applied science. I trace the history of the distinction between pure and applied science, showing how the distinction came about, the rhetorical uses to which the distinction has been put, and how pure science came to be both more valued by scientists and philosophers. I argue that the distinction between pure and applied science does not stand up to philosophical scrutiny, and that once we relinquish it, we can provide Kuhn with a clear sense of scientific progress. It is not one, though, that will ultimately prove acceptable. For that, societal evaluations of scientific work are needed.

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.

Weighing complex sets of evidence (i.e., from multiple disciplines and often divergent in implications) is increasingly central to properly informed decision-making. Determining “where the weight of evidence lies” is essential both for making maximal use of available evidence and figuring out what to make of such evidence. Weighing evidence in this sense requires an approach that can handle a wide range of evidential sources (completeness), that can combine the evidence with rigor, and that can do so in a way other experts can assess and critique (transparency). But the democratic context in need of weight-of-evidence analysis also places additional constraints on the process, including communicability of the process to the general public, the need for an approach that can be used across a broad range of contexts (scope), and timeliness of process (practicality). I will compare qualitative and quantitative approaches with respect to both traditional epistemic criteria and criteria that arise from the democratic context, and argue that a qualitative explanatory approach can best meet the criteria and elucidate how to utilize the other approaches. This should not be surprising, as the approach I argue for is the one that most closely tracks general scientific reasoning.

The moral terrain of science, the full range of ethical considerations that are part of the scientific endeavor, has not been mapped. Without such a map, we cannot examine the responsibilities of scientists to see if the institutions of science are adequately constructed. This paper attempts such a map by describing four dimensions of the terrain: (1) the bases to which scientists are responsible (scientific reasoning, the scientific community, and the broader society); (2) the nature of the responsibility (general or role); (3) the level of responsibility (minimum demand or ideal); and (4) who bears the responsibility (the individual or the community). Such a map will be used to elucidate the recent debate over the publication of studies concerning H5N1 flu virus

In the debate over the role of science in environmental policy, it is often assumed that science can and should be clearly demarcated from policy. In this paper, I will argue that neither is the case. The difficulty of actually differentiating the scientific arena from the policy arena becomes apparent the moment one attempts to actually locate the boundary. For example, it is unclear whether scientific summaries to be used by regulatory agencies are in the realm of science or policy. If science, then should the authors consider the regulatory implications of uncertainties? If policy, then what is the relevance of a peer review of the document solely by scientists? This descriptive problem is only accentuated by a normative problem: should we try to keep the two realms distinct? The traditional answer has been yes, for the primary reason that the science should not be infected by the social and ethical values so prevalent in the policy realm. I will argue that, to the contrary, social and ethical values are desirable components of scientific reasoning. Indeed, on closer examination, the norms for valuesin reasoning are the same for science and policy. If I am correct, the pressure to delineate science from policy abates.

Philosophy of science was once a much more socially engaged endeavor, and can be so again. After a look back at philosophy of science in the 1930s-1950s, I turn to discuss the current potential for returning to a more engaged philosophy of science. Although philosophers of science have much to offer scientists and the public, I am skeptical that much can be gained by philosophers importing off-the-shelf discussions from philosophy of science to science and society. Such efforts will likely look like efforts to do applied ethics by merely applying ethical theories to particular contexts and problems. While some insight can be gained by these kinds of endeavors, the most interesting and pressing problems for the actual practitioners and users of science are rarely addressed. Instead, I recommend that philosophers of science engage seriously and regularly with scientists and/or the users of science in order to gain an understanding of the conceptual issues on the ground. From such engagement, flaws in the traditional philosophical frameworks, and how such flaws can be remedied, become apparent. Serious engagement with the contexts of science thus provides the most fruit for philosophy of science per se and for the practitioners whom the philosophers aim to assist. And if one focuses on contexts where science has its most social relevance, these efforts can help to provide the thing that philosophy of science now lacks: a full-bodied philosophy of science in society

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...

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.

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?

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.