The problem this paper addresses is that scientists have to take normatively charged decisions which can have a significant impact on individual members of the public or the public as a whole. And yet mechanisms to exercise democratic control over them are often absent. Given the normative nature of these choices, this is often perceived to be at odds with basic democratic principles. I show that this problem applies in similar ways to civil service institutions and draw on political philosophy (...) literature on the civil service (e.g. Rosanvallon, 2011; Heath, 2022) to discuss when such normative judgements can nevertheless be said to be democratically legitimate. Concretely, I seek to show that normative judgements in research need not be democratically legitimated in order for science to be democratically legitimate. Indeed, it can be democratically legitimate for scientists to go against the expressed views of the public or political representatives if this is justified in light of, firstly, the role science has been asked to fulfil and, secondly, when it is in line with public institutions’ key principles. This is a counter-position to views currently held in the values in science debate (e.g. by Kitcher, 2011; Intemann, 2015; Schroeder, 2021; Lusk, 2021) which argue that value-laden judgements in science are legitimate if they are aligned with the public’s views or directly decided by public. (shrink)

The underreporting of suspected adverse drug reactions remains a primary issue for contemporary post-market drug surveillance or ‘pharmacovigilance.’ Pharmacovigilance pioneer W.H.W. Inman argued that ‘deadly sins’ committed by clinicians are to blame for underreporting. Of these ‘sins,’ ignorance and lethargy are the most obvious and impactful in causing underreporting. However, recent analyses show that diffidence, insecurity, and indifference additionally play a major role. I aim to augment our understanding of diffidence, insecurity, and indifference by arguing these sins are underwritten by (...) value judgments arising via epistemic risk. I contend that ‘evidence-based’ medicine codifies these sins. (shrink)

Physicist Percy Bridgman has been taken by Heather Douglas to be an exemplar defender of an untenable value-free ideal for science. This picture is complicated by a detailed study of Bridgman's philosophical views of the relation between science and society. The normative autonomy of science, a version of the value-free ideal, is defended. This restriction on the provenance of permissible values in science is given a basis in Bridgman's broader philosophical commitments, most importantly, his view that science is primarily an (...) individual commitment to a set of epistemic norms and values. Considerations of external moral or social values are not, on this view, intrinsic to scientific practice, though they have a broader pragmatic significance. What Bridgman takes as the proper relation between science and society is shown through analysis of his many writings on the topic and consideration of his rarely remarked upon involvement in the most problematic example of "Big Science" of his day: the atomic bomb. A reevaluation of Bridgman's views provides a unique characterization of what is at stake in the values in science debate: the normative autonomy of science. (shrink)

In the science and values literature, scholars have shown how science is influenced and shaped by values, often in opposition to the ‘value free’ ideal of science. In this paper, we aim to contribute to the science and values literature by showing that the relation between science and values flows not only from values into scientific practice, but also from (allegedly neutral) science to values themselves. The extant literature in the ‘science and values’ field focuses by and large on reconstructing, (...) post hoc, how values have influenced science; our reconstruction of the case studies, instead, aims to show that scientific concepts and methods _too, because of specific identifiable characteristics,_ can promote some values rather than (or at the expense of) others. We explain this bidirectional relation in analogy to debates on the normativity of technical artifacts and on feminist approaches in science, and we illustrate our claims with cases from the health sciences and machine learning. While our arguments in this paper also draw on post hoc reconstructions, we intend to show where, in the science in the making, we should engage not only with the question whether a practice is value-laden, but also how specific conceptual and methodological choices can influence values down the road. All in all, these considerations expand the ways in which philosophers can contribute to more value-aware scientific practices. (shrink)

Mainstream views of medical research tell us it should be a fact-based, value-free endeavor: what a scientist (or her funding source) wants or cares about should not influence her findings. At the same time, we also sometimes criticize medical research for failing to embody certain values, e.g. when we criticize pharmaceutical companies for largely ignoring the diseases that affect the global poor. This chapter seeks to reconcile these perspectives by distinguishing appropriate from inappropriate influences of values on medical research. It (...) divides this broad question into two narrower ones, the Role Question (at what points in the research process is value influence potentially acceptable?) and the Content Question (when value influence is potentially acceptable, what specific values should researchers use?), and then draws on the philosophical literature on values in science to explore answers to each of them. (shrink)

Straightening the current ‘value-laden turn’ (VLT) in the philosophical literature on values in science, and reviving the legacy of the value-free ideal of science (VFI), this paper argues that the influence of extra-scientific values should be minimised—not excluded—in the core phase of scientific inquiry where claims are accepted or rejected. Noting that the original arguments for the VFI (ensuring the truth of scientific knowledge, respecting the autonomy of science results users, preserving public trust in science) have not been satisfactorily addressed (...) by proponents of the VLT, it proposes four prerequisites which any model for values in the acceptance/rejection phase of scientific inquiry should respect, coming from the fundamental requirement to distinguish between facts and values: (1) the truth of scientific knowledge must be ensured; (2) the uncertainties associated with scientific claims must be stated clearly; (3) claims accepted into the scientific corpus must be distinguished from claims taken as a basis for action. An additional prerequisite of (4) simplicity and systematicity is desirable, if the model is to be applicable. Methodological documents from international institutions and regulation agencies are used to illustrate the prerequisites. A model combining Betz’s conception (stating uncertainties associated with scientific claims) and Hansson’s corpus model (ensuring the truth of the scientific corpus and distinguishing it from other claims taken as a basis for action) is proposed. Additional prerequisites are finally suggested for future research, stemming from the requirement for philosophy of science to self-reflect on its own values: (5) any model for values in science must be descriptively and normatively relevant; and (6) its consequences must be thoroughly assessed. (shrink)

While the debate on values in science focuses on normative questions on the level of the individual (e.g. should researchers try to make their work as value free as possible?), comparatively little attention has been paid to the institutional and professional norms that researchers are expected to follow. To address this knowledge gap, we conduct a content analysis of leading national codes of conduct for research integrity of European countries, and structure our analysis around the question: do these documents allow (...) for researchers to be influenced by “non-epistemic” (moral, cultural, commercial, political, etc.) values or do they prohibit such influence in compliance with the value-free ideal (VFI) of science? Our results return a complex picture. On the one hand, codes of conduct consider many non-epistemic values to be a legitimate influence on the decision-making of researchers. On the other, most of these documents include what we call _VFI-like positions_: passages claiming that researchers should be free and independent from any external influence. This shows that while many research integrity documents do not fully endorse the VFI, they do not reject it and continue to be implicitly influenced by it. This results in internal tensions and underdetermined guidance on non-epistemic values that may limit some of the uses of research integrity codes, especially for purposes of ethical self-regulation. While codes of conduct cannot be expected to decide how researchers should act in every instance, we do suggest that they acknowledge the challenges of how to integrate non-epistemic values in research in a more explicit fashion. (shrink)

The value-free ideal in science has been criticised as both unattainable and undesirable. We argue that it can be defended as a practical principle guiding scientific research even if the unattainability and undesirability of a value-free end-state are granted. If a goal is unattainable, then one can separate the desirability of accomplishing the goal from the desirability of pursuing it. We articulate a novel value-free ideal, which holds that scientists should act as if science should be value-free, and we argue (...) that even if a purely value-free science is undesirable, this value-free ideal is desirable to pursue. (shrink)

The value-free ideal for science holds that values should not influence the core features of scientific reasoning. We defend the difference-to-inference model of value-permeation, which holds that value-permeation in science is problematic when values make a difference to the inferences made about a hypothesis. This view of value-permeation is superior to existing views, and it suggests a corresponding maxim—namely, that scientists should strive to eliminate differences to inference. This maxim is the basis of a novel value-free ideal for science. -/- (...) . (shrink)

The setting of evidential standards is a core practice of scientific assessment for policy. Persuaded by considerations of inductive risk, philosophers generally agree that the justification of evidential standards must appeal to non-epistemic values but debate whether the balance of non-epistemic reasons favours varying evidential standards versus maintaining fixed high evidential standards in assessment, as both sets of standards promote different and important political virtues of advisory institutions. In this paper, I adjudicate the evidential standards debate by developing a novel (...) argument from justice, drawing on the IPCC’s assessment of climate impacts as a case study. I argue that in assessments marked by background evidential inequality, maintaining fixed high evidential standards results in an unequal distribution of ‘epistemic power’ among stakeholders, producing a ‘powerful assessment’ for the data-rich (a high rate of findings) and a ‘weak assessment’ for the data-poor (a low rate of findings). Where such inequalities of epistemic power disadvantage those in data-poor regions with respect to fundamental interests, such as basic human rights, we have decisive reasons of justice to vary evidential standards. (shrink)

In the last two decades, a robust consensus has emerged among philosophers of science, whereby political, ethical, or social values must play some role in scientific inquiry, and that the ‘value-free ideal’ is thus a misguided conception of science. However, the question of how to distinguish, in a principled way, which values may legitimately influence science remains. This question, which has been dubbed the ‘new demarcation problem,’ has until recently received comparatively less attention from philosophers of science. In this paper, (...) I appeal to Rawls’s theory of justice (1971) on the basis of which I defend a Rawlsian solution to the new demarcation problem. As I argue, the Rawlsian solution places plausible constraints on which values ought to influence scientific inquiry, and, moreover, can be fruitfully applied to concrete cases to determine how the conflicting interests of stakeholders should be balanced. After considering and responding to the objection that Rawls’s theory of justice applies only to the “basic structure” of society, I compare the Rawlsian solution to some other approaches to the new demarcation problem, especially those that emphasize democratic criteria. (shrink)

In recent years, many philosophers of science have rejected the “value-free ideal” for science, arguing that non-epistemic values have a legitimate role to play in scientific inquiry. However, this philosophical position raises the question of how to distinguish between legitimate and illegitimate influences of values in science. In this paper, we argue that those seeking to address this “new” demarcation problem can benefit by drawing lessons from the “old” demarcation problem, in which philosophers tried to find a way of distinguishing (...) between science and non-science. Many of those who worked on this problem ultimately found that efforts to provide necessary and sufficient conditions for defining science failed, and most concluded that the best solution to the problem was to characterize scientific hypotheses, theories, and research programs in terms of some common norms. We suggest that those seeking to distinguish between legitimate and illegitimate value influences on science would do well to adopt a similar approach. Rather than attempting to establish necessary and sufficient conditions for identifying appropriate value influences, it will be more fruitful to evaluate scientific activities based on their adherence to a set of epistemic and ethical norms that can be implemented in scientific practice by means of rules, conventions, policies, and procedures. (shrink)

In this paper I shall defend the idea that there is an abstract and general core meaning of objectivity, and what is seen as a variety of concepts or conceptions of objectivity are in fact criteria of, or means to achieve, objectivity. I shall then discuss the ideal of value-free science and its relation to the objectivity of science; its status can be at best a criterion of, or means for, objectivity. Given this analysis, we can then turn to the (...) problem of inductive risk. Do the value judgements regarding inductive risk really pose a threat to the objectivity of science? I claim that this is not the case because they do not lower the thresholds scientifically postulated for objectivity. I shall conclude the paper with a discussion of under-appreciated influences of values on science, which indeed pose a serious threat to the objectivity of some scientific disciplines. (shrink)

Even if the “value-free ideal of science” (VFI) were an unattainable goal, one could ask: can it be a useful fiction, one that is beneficial for the research community and society? This question is particularly crucial for scholars and institutions concerned with research integrity (RI), as one cannot offer normative guidance to researchers without making some assumptions about what ideal scientific research looks like. Despite the insofar little interaction between scholars studying RI and those working on values in science, the (...) overlap of topics and interests make collaboration between the two fields promising for understanding research and its ethics. Here, we identify—for the use of RI scholars—the non-epistemic reasons (societal, political, professional) for and against the VFI considered in the literature. All of these are concerned with the beneficial or detrimental consequences that endorsing the VFI would have on society, policy-making, or the scientific community, with some authors appealing to the same principles to argue for opposite positions. Though most of the reviewed articles do not endorse the VFI, it is generally agreed that some constraints have to be put on the use of non-epistemic values. Disagreement on the utility of the VFI lies both on the different epistemic-descriptive positions taken by different authors, and on the scarcity of relevant empirical studies. Engaging critically with the reasons here identified and more in general with the values in science debate will help the RI community decide whether the VFI should be included in future codes of conduct. (shrink)

The following paper argues that issues in paradigmatic proposals for solving the new demarcation problem stem from absolutist assumptions about judgments of value legitimacy. Both the problem of uninformativeness (Larroulet Philippi 2020; Fernandez-Pinto 2014, 2015) and the problem of ambiguous judgments of cases (Hicks 2014; Intemann 2017) are explained by an absolutist pretension contained in one of the main aims of these proposals: providing criteria for differentiating legitimate from illegitimate uses of values, without qualification. After presenting the problems and showing (...) how they stem from that common source, we will sketch a way forward, inspired mainly by Joseph Rouse’s Beyond Epistemic Sovereignty (1996), advancing routes that can allow philosophers of science to evade these pitfalls and engage with scientific practice in a more salutary manner. (shrink)

One of the main worries with machine learning model opacity is that we cannot know enough about how the model works to fully understand the decisions they make. But how much is model opacity really a problem? This chapter argues that the problem of machine learning model opacity is entangled with non-epistemic values. The chapter considers three different stages of the machine learning modeling process that corresponds to understanding phenomena: (i) model acceptance and linking the model to the phenomenon, (ii) (...) explanation, and (iii) attributions of understanding. At each of these stages, non-epistemic values can, in part, determine how much machine learning model opacity poses a problem. (shrink)

This paper critically assesses the current debates in philosophy of science that focus on the concept of values. In these debates, it is often assumed that all relevant non-epistemic influences on scientific research can be described as values and, consequently, that science carries social legitimacy if the correct values play their proper role in research. I argue that values are _not_ the only relevant non-epistemic influences on research: not unless our definition of values is so broad that it becomes unmanageable. (...) Other factors also affect the authority and social legitimacy of science. I employ political theorist Iris Marion Young’s concepts of social perspectives, opinions and interests to attempt a differentiation of contextual influences relevant to scientific research. While problems arising from these influences may overlap, they often differ in important ways too. As a consequence, I argue that contextual influences cannot be managed jointly but require distinct and complementary strategies. (shrink)

A general criterion for distinguishing between epistemic and non-epistemic values is that the former promotes the attainment of truth whereas the latter does not. Daniel Steel is a proponent of this criterion, although it was initially proposed by McMullin. There are at least two consequences of this criterion; it always prioritizes epistemic values over non-epistemic values in scientific research, and it overlooks the diverse aims of science, especially the aims of regulatory or policy-oriented science. This criterion assumes the lexical priority (...) of truth or lexical priority of evidence. This paper attempts to show a few inadequacies of this assumption. The paper also demonstrates why epistemic priority over non-epistemic values is a problematic stance and how constraining the role of non-epistemic values as ‘tiebreakers’ may undermine the diverse aims of science. (shrink)

Policy-makers often rely on scientists to inform their decisions. When advising policy-makers, what should scientists say? One view says that scientists ought to say what they have a high credence in. Another view says that scientists ought to say what they expect to lead to good policy outcomes. We explore a third view: scientists ought to say what they expect to make the policy-makers’ credences accurate.

While the Value-Free Ideal of science has suffered compelling criticism, some advocates like Gregor Betz continue to argue that science policy advisors should avoid value judgments by hedging their hypotheses. This approach depends on a mistaken understanding of the relations between facts and values in regulatory science. My case study involves the morning-after pill Plan B and the “Drug Fact” that it “may” prevent implantation. I analyze the operative values, which I call zygote-centrism, responsible for this hedged drug label. Then, (...) I explain my twofold account of value-ladenness, involving the constitutive role of value judgments in science and the social function of facts as political tools. Because this drug fact is ineliminably value-laden in both senses, I conclude that hedged hypotheses are not necessarily value-free. (shrink)

In the last decade, many problematic cases of scientific conduct have been diagnosed; some of which involve outright fraud others are more subtle. These and similar problems can be interpreted as caused by lack of scientific objectivity. The current philosophical theories of objectivity do not provide scientists with conceptualizations that can be effectively put into practice in remedying these issues. We propose a novel way of thinking about objectivity for individual scientists; a negative and dynamic approach.We provide a philosophical conceptualization (...) of objectivity that is informed by empirical research. In particular, it is our intention to take the first steps in providing an empirically and methodologically informed inventory of factors that impair the scientific practice. The inventory will be compiled into a negative conceptualization, which could in principle be used by individual scientists to assess objectivity of scientific practice. We propose a preliminary outline of a usable and testable instrument for indicating the objectivity of scientific practice. (shrink)

Non-epistemic values pervade climate modelling, as is now well documented and widely discussed in the philosophy of climate science. Recently, Parker and Winsberg have drawn attention to what can be termed “epistemic inequality”: this is the risk that climate models might more accurately represent the future climates of the geographical regions prioritised by the values of the modellers. In this paper, we promote value management as a way of overcoming epistemic inequality. We argue that value management can be seriously considered (...) as soon as the value-free ideal and inductive risk arguments commonly used to frame the discussions of value influence in climate science are replaced by alternative social accounts of objectivity. We consider objectivity in Longino's sense as well as strong objectivity in Harding's sense to be relevant options here, because they offer concrete proposals that can guide scientific practice in evaluating and designing so-called multi-model ensembles and, in fine, improve their capacity to quantify and express uncertainty in climate projections. (shrink)

Environmental health research produces scientific knowledge about environmental hazards crucial for public health and environmental justice movements that seek to prevent or reduce exposure to these hazards. The environment in environmental health research is conceptualized as the range of possible social, biological, chemical, and/or physical hazards or risks to human health, some of which merit study due to factors such as their probability and severity, the feasibility of their remediation, and injustice in their distribution. This paper explores the ethics of (...) identifying the relevant environment for environmental health research, as judgments involved in defining an environmental hazard or risk, judgments of that hazard or risk's probability, severity, and/ or injustice, as well as the feasibility of its remediation, all ought to appeal to non-epistemic as well as epistemic values. I illustrate by discussing the case of environmental lead, a housing-related hazard that remains unjustly distributed by race and class and is particularly dangerous to children. Examining a controversy in environmental health research ethics where researchers tested multiple levels of lead abatement in lead-contaminated households, I argue that the broader perspective on the ethics of environmental health research provided in the first part of this paper may have helped prevent this controversy. (shrink)

English summary: This paper uses research on the COVID-19 pandemic as the backdrop for an accessible discussion of the value and status of science, and of the role of valuesin science. In particular, the paper seeks to debunk three common myths or dogmas about scientific research: (i) that there is such a thing as 'scientific proof' of a theory or hypothesis, (ii) that disagreement is necessarily unhealthy or unnatural in science, (iii) and that personal values play no role in scientific (...) research. (shrink)

When it originated in the late 19th century, psychometrics was a field with both a scientific and a social mission: psychometrics provided new methods for research into individual differences, and at the same time, these psychometric instruments were considered a means to create a new social order. In contrast, contemporary psychometrics - due to its highly technical nature and its limited involvement in substantive psychological research - has created the impression of being a value-free discipline. In this article, we develop (...) a contrasting characterization of contemporary psychometrics as a value-laden discipline. We expose four such values: that individual differences are quantitative (rather than qualitative), that measurement should be objective in a specific sense, that test items should be fair, and that utility of a model is more important than its truth. Our goal is not to criticize psychometrics for employing these values, but rather to bring them into the open and to show that these values are not inevitable and are in need of systematic evaluation. (shrink)

Although the impact of so-called “sponsorship bias” has been the subject of increased attention in the philosophy of science, what exactly constitutes its epistemic wrongness is still debated. In this paper, I will argue that neither evidential accounts nor social–epistemological accounts can fully account for the epistemic wrongness of sponsorship bias, but there are good reasons to prefer social–epistemological to evidential accounts. I will defend this claim by examining how both accounts deal with a paradigm case from medical epistemology, recently (...) discussed in a paper by Bennett Holman. I will argue that evidential accounts cannot adequately capture cases of sponsorship bias that involve the manufacturing of certainty because of their neutrality with respect to the role of non-epistemic values in scientific practice. If my argument holds, it further highlights the importance of integrating social and ethical concerns into epistemological analysis, especially in applied contexts. One can only properly grasp sponsorship bias as an epistemological problem if one resists the methodological tendency to analyze social, ethical, and epistemological issues in isolation from each other. (shrink)

In the past few years, social epistemologists have developed several formal models of the social organisation of science. While their robustness and representational adequacy has been analysed at length, the function of these models has begun to be discussed in more general terms only recently. In this article, I will interpret many of the current formal models of the scientific community as representing the latest development of what I will call the ‘Kuhnian project’. These models share with Kuhn a number (...) of questions about the relation between individuals and communities. At the same time, they also inherit some of Kuhn’s problematic characterisations of the scientific community. In particular, current models of the social organisation of science represent the scientific community as essentially value-free. This may put into question both their representational adequacy and their normative ambitions. In the end, it will be shown that the discussion on the formal models of the scientific community may contribute in fruitful ways to the ongoing debates on value judgements in science. (shrink)

Using climate policy debates as a case study, I argue that a certain response to the argument from inductive risk, the hedging defense, runs afoul of a reasonable ethical principle: the no-passing-...

I examine how Heather Douglas’ account of values in science applies to the assessment of actual cases of scientific practice. I focus on the case of applied toxicologists’ acceptance of molecular evidence-gathering methods and evidential sources. I demonstrate that a set of social and institutional processes plays a philosophically significant role in changing toxicologists’ inductive risk judgments about different kinds of evidence. I suggest that Douglas’ inductive risk framework can be integrated with a suitable account of evidence, such as Helen (...) Longino’s contextual empiricism, to address the role of social context in the cases like the one examined here. I introduce such an integrated account and show how Longino’s contextual empiricism and inductive risk framework fruitfully complement each other in analyzing the novel aspects of the toxicology case. (shrink)

This paper has two goals. The first is to fill a gap in the literature on inductive risk by exploring the relevance of the notion of inductive risk to macroeconomics and monetary policy. The second goal is to draw some general lessons about inductive risk from the case discussed. The most important of these lessons is that the notion of inductive risk is no less relevant to the relationship between the proximate and distal goals of policy than it is to (...) the relationship between policies and their goals. (shrink)

Philosophical work on values in science is held back by widespread ambiguity about how values bear on sci entific choices. Here, I disambiguate several ways in which a choice can be value-laden and show that this disambiguation has the potential to solve and dissolve philosophical problems about values in science. First, I characterize four ways in which values relate to choices: values can motivate, justify, cause, or be impacted by the choices we make. Next, I put my proposed taxonomy to (...) work, using it to clarify one version of the argument from inductive risk. The claim that non-epistemic values must play a role in scientific choices that run inductive risk makes most sense as a claim about values being needed to justify such choices. The argument from inductive risk is not unique: many philosophical arguments about values in science can be more clearly understood and assessed by paying close attention to how values and choices are related. (shrink)

Philosophers of science now broadly agree that doing good science involves making non-epistemic value judgments. I call attention to two very different normative standards which can be used to evaluate such judgments: standards grounded in ethics and standards grounded in political philosophy. Though this distinction has not previously been highlighted, I show that the values in science literature contain arguments of each type. I conclude by explaining why this distinction is important. Seeking to determine whether some value-laden determination meets substantive (...) ethical standards is a very different endeavor from seeking to determine if it is politically legitimate. (shrink)

Lloyd analyzes every proposed evolutionary explanation of female orgasm and argues that all but one suffers from serious evidential errors. Lloyd attributes these errors to two main biases: androcentrism and adaptationism. This paper begins by arguing that the explanation Lloyd favors—the by-product account—is guilty of the androcentrism which supposedly implicates the other explanations of female orgasm with numerous evidential discrepancies. This suggests that there is another error afflicting orgasm research in addition to the biases Lloyd identities. I attempt to diagnose (...) and characterize this additional error. In short, I think the error is using an imprecise definition of the trait in question. Further, Lloyd takes her analysis to support Longino’s contextual empiricist model of scientific objectivity. I consider what implications this analysis has for contextual empiricism. Finally, I argue that theorizing about female orgasm should be done from a conceptual engineering approach. (shrink)

Both scientists and philosophers of science have recently emphasized the importance of promoting transparency in science. For scientists, transparency is a way to promote reproducibility, progress, and trust in research. For philosophers of science, transparency can help address the value-ladenness of scientific research in a responsible way. Nevertheless, the concept of transparency is a complex one. Scientists can be transparent about many different things, for many different reasons, on behalf of many different stakeholders. This paper proposes a taxonomy that clarifies (...) the major dimensions along which approaches to transparency can vary. By doing so, it provides several insights that philosophers and other science studies scholars can pursue. In particular, it helps address common objections to pursuing transparency in science, it clarifies major forms of transparency, and it suggests avenues for further research on this topic. (shrink)

I examine ramifications of the widespread view that scientific objectivity gives us a permission to trust scientific knowledge claims. According to a widely accepted account of trust and trustworthiness, trust in scientific knowledge claims involves both reliance on the claims and trust in scientists who present the claims, and trustworthiness depends on expertise, honesty, and social responsibility. Given this account, scientific objectivity turns out to be a hybrid concept with both an epistemic and a moral-political dimension. The epistemic dimension tells (...) us when scientific knowledge claims are reliable, and the moral-political dimension tells us when we can trust scientists to be socially responsible. While the former dimension has received a fair amount of attention, the latter is in need of analysis. I examine what it means for scientists to be socially responsible, that is, to follow “sound” moral and social values in different stages of scientific inquiry. Social responsibility is especially important when scientists function as experts in society. Members of the public and policymakers do not want to rely on scientific research shaped by moral and social values they have good reasons to reject. Moreover, social responsibility is important in social research in which moral and social values can legitimately play many roles. I discuss the strengths and weaknesses of different answers to the question of how social scientists can identify appropriate moral and social values to inform their research. I argue that procedural accounts of social responsibility, such as well-ordered science and deliberative polling, have limitations. (shrink)

The proper role of non-epistemic values such as moral, political, and social values in practices of justification of policy-relevant hypotheses has recently become one of the central questions in philosophy of science. This strand of research has yielded conceptual clarifications and significant insight into the complex and notoriously contentious issue of the proper relationship between science, non-epistemic values, and policymaking. A central part of this discussion revolves around whether scientists should aspire for the value-free ideal, according to which non-epistemic values (...) are unacceptable in the justification of hypotheses. By so doing, scientists can... (shrink)

Introduction to Synthese SI: Systematicity: The Nature of Science?

Social and medical scientists frequently produce empirical generalizations that involve concepts partly defined by value judgments. These generalizations, which have been called ‘mixed claims’, raise interesting questions. Does the presence of them in science imply that science is value-laden? Is the value-ladenness of mixed claims special compared to other kinds of value-ladenness of science? Do we lose epistemically if we reformulate these claims as conditional statements? And if we want to allow mixed claims in science, do we need a new (...) account of how to reconcile values with objectivity? Alexandrova (2017, 2018) offers affirmative answers to these questions. In responding to Alexandrova’s arguments, this discussion note motivates negative ones and in doing so casts new light on mixed claims. (shrink)

What makes science trustworthy to the public? This chapter examines one proposed answer: the trustworthiness of science is based at least in part on its independence from the idiosyncratic values, interests, and ideas of individual scientists. That is, science is trustworthy to the extent that following the scientific process would result in the same conclusions, regardless of the particular scientists involved. We analyze this "idiosyncrasy-free ideal" for science by looking at philosophical debates about inductive risk, focusing on two recent proposals (...) which offer different methods of avoiding idiosyncrasy: the high epistemic standards proposal and the democratic values proposal. (shrink)

For computer simulation models to usefully inform climate risk management, uncertainties in model projections must be explored and characterized. Because doing so requires running the model many ti...

This paper re-interprets the precautionary principle as a ‘social epistemic rule’. First, it argues that sometimes policy-makers should act on claims which have not been scientifically established....

Many philosophers and statisticians argue that risk assessors are morally obligated to evaluate the probabilities and consequences of methodological error, and to base their decisions of whether to adopt a given parameter value, model, or hypothesis on those considerations. This argument is couched within the rubric of null hypothesis testing, which I suggest is a poor descriptive and normative model for risk assessment. Risk regulation is not primarily concerned with evaluating the probability of data conditional upon the null hypothesis, but (...) rather with measuring risks, estimating the consequences of available courses of action and inaction, formally characterising uncertainty, and deciding what to do based upon explicit values and decision criteria. In turn, I defend an ideal of value-neutrality, whereby the core inferential tasks of risk assessment – such as weighing evidence, estimating parameters, and model selection – should be guided by the aim of correspondence to reality. This is not to say that value-judgments be damned, but rather that they should be accounted for within a structured approach to decision analysis, rather than embedded within risk assessment in an informal manner. (shrink)

It is now commonly held that values play a role in scientific judgment, but many arguments for that conclusion are limited. First, many arguments do not show that values are, strictly speaking, indispensable. The role of values could in principle be filled by a random or arbitrary decision. Second, many arguments concern scientific theories and concepts which have obvious practical consequences, thus suggesting or at least leaving open the possibility that abstruse sciences without such a connection could be value-free. Third, (...) many arguments concern the role values play in inferring from evidence, thus taking evidence as given. This paper argues that these limitations do not hold in general. There are values involved in every scientific judgment. They cannot even conceivably be replaced by a coin toss, they arise as much for exotic as for practical sciences, and they are at issue as much for observation as for explicit inference. (shrink)

Many philosophers have challenged the ideal of value-free science on the grounds that social or moral values are relevant to inferential thresholds. But given this view, how precisely and to what extent should scientists adjust their inferential thresholds in light of nonepistemic values? We suggest that signal detection theory provides a useful framework for addressing this question. Moreover, this approach opens up further avenues for philosophical inquiry and has important implications for philosophical debates concerning inductive risk. For example, the signal (...) detection theory framework entails that considerations of inductive risk and inferential-threshold placement cannot be conducted in isolation from base-rate information. (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)

This paper discusses ethical issues surrounding Integrated Assessment Models (IAMs) of the economic effects of climate change, and how climate economists acting as policy advisors ought to represent the uncertain possibility of catastrophe. Some climate economists, especially Martin Weitzman, have argued for a precautionary approach where avoiding catastrophe should structure climate economists’ welfare analysis. This paper details ethical arguments that justify this approach, showing how Weitzman’s “fat tail” probabilities of climate catastrophe pose ethical problems for widely used IAMs. The main (...) claim is that economists who ignore or downplay catastrophic risks in their representations of uncertainty likely fall afoul of ethical constraints on scientists acting as policy advisors. Such scientists have duties to honestly articulate uncertainties and manage (some) inductive risks, or the risks of being wrong in different ways. (shrink)

Innovative research on decision making under ‘deep uncertainty’ is underway in applied fields such as engineering and operational research, largely outside the view of normative theorists grounded in decision theory. Applied methods and tools for decision support under deep uncertainty go beyond standard decision theory in the attention that they give to the structuring of decisions. Decision structuring is an important part of a broader philosophy of managing uncertainty in decision making, and normative decision theorists can both learn from, and (...) contribute to, the growing deep uncertainty decision support literature. (shrink)

Inmaculada de Melo-Martín and Kristen Intemann consider whether, from the perspective of the argument from inductive risk, ethical and political values might be logically, epistemically, pragmatically, or ethically necessary in the “core” of scientific reasoning. In each case, they argue that there are significant conceptual problems. In this comment, employing regulatory uses of high-throughput toxicology at the US Environmental Protection Agency as a case study, I respond to some of their claims about the notion of “pragmatic necessity.” I conclude that, (...) while an inductive risk framework has some significant limitations, it is still conceptually and rhetorically valuable. (shrink)