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)

While it is widely acknowledged that science is not “free” of non-epistemic values, there is disagreement about the roles that values can appropriately play. Several have argued that non-epistemic values can play important roles in modeling decisions, particularly in addressing uncertainties ; Risbey 2007; Biddle and Winsberg 2010; Winsberg : 111-137, 2012); van der Sluijs 359-389, 2012). On the other hand, such values can lead to bias ; Bray ; Oreskes and Conway 2010). Thus, it is important to identify when (...) it is legitimate to appeal to non-epistemic values in modeling decisions. An approach is defended here whereby such value judgments are legitimate when they promote democratically endorsed epistemological and social aims of research. This framework accounts for why it is legitimate to appeal to non-epistemic values in a range of modeling decisions, while addressing concerns that the presence of such values will lead to bias or give scientists disproportionate power in deciding what values ought to be endorsed. (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)

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)

We call attention to an underappreciated way in which non-epistemic values influence evidence evaluation in science. Our argument draws upon some well-known features of scientific modeling. We show that, when scientific models stand in for background knowledge in Bayesian and other probabilistic methods for evidence evaluation, conclusions can be influenced by the non-epistemic values that shaped the setting of priorities in model development. Moreover, it is often infeasible to correct for this influence. We further suggest that, while this value influence (...) is not particularly prone to the problem of wishful thinking, it could have problematic non-epistemic consequences in some cases. (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)

The aim of this article is to argue that ontological choices in scientific practice undermine common formulations of the value-free ideal in science. First, I argue that the truth values of scientific statements depend on ontological choices. For example, statements about entities such as species, race, memory, intelligence, depression, or obesity are true or false relative to the choice of a biological, psychological, or medical ontology. Second, I show that ontological choices often depend on non-epistemic values. On the basis of (...) these premises, I argue that it is often neither possible nor desirable to evaluate scientific statements independently of non-epistemic values. Finally, I suggest that considerations of ontological choices do not only challenge the value-free ideal but also help to specify positive roles of non-epistemic values in an often neglected area of scientific practice. (shrink)

The argument from inductive risk has been embraced by many as a successful account of the role of values in science that challenges the value-free ideal. We argue that it is not obvious that the argument from inductive risk actually undermines the value-free ideal. This is because the inductive risk argument endorses an assumption held by proponents of the value-free ideal: that contextual values never play an appropriate role in determining evidence. We show that challenging the value-free ideal ultimately requires (...) rejecting this assumption. (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)

The aim of this article is to argue that ontological choices in scientific practice undermine common formulations of the value-free ideal in science. First, I argue that the truth values of scientific statements depend on ontological choices. For example, statements about entities such as species, race, memory, intelligence, depression, or obesity are true or false relative to the choice of a biological, psychological, or medical ontology. Second, I show that ontological choices often depend on non-epistemic values. On the basis of (...) these premises, I argue that it is often neither possible nor desirable to evaluate scientific statements independently of non-epistemic values. Finally, I suggest that considerations of ontological choices do not only challenge the value-free ideal but also help to specify positive roles of non-epistemic values in an often neglected area of scientific practice. (shrink)

This paper discusses a crisis of accountability that arises when scientific collaborations are massively epistemically distributed. We argue that social models of epistemic collaboration, which are social analogs to what Patrick Suppes called a “model of the experiment,” must play a role in creating accountability in these contexts. We also argue that these social models must accommodate the fact that the various agents in a collaborative project often have ineliminable, messy, and conflicting interests and values; any story about accountability in (...) a massively distributed collaboration must therefore involve models of such interests and values and their methodological and epistemic effects. (shrink)

Recent rival attempts in the philosophy of science to put forward a general theory of the properties that all (and only) natural kinds across the sciences possess may have proven to be futile. Instead, I develop a general methodological framework for how to philosophically study kinds. Any kind has to be investigated and articulated together with the human aims that motivate referring to this kind, where different kinds in the same scientific domain can answer to different concrete aims. My core (...) contention is that non-epistemic aims, including environmental, ethical, and political aims, matter as well. This is defended and illustrated based on several examples of kinds, with particular attention to the role of social-political aims: species, race, gender, as well as personality disorders and oppositional defiant disorder as psychiatric kinds. Such non-epistemic aims and values need not always be those personally favoured by scientists, but may have to reflect values that matter to relevant societal stakeholders. Despite the general agenda to study ‘kinds,’ I argue that philosophers should stop using the term ‘natural kinds,’ as this label obscures the relevance of humans interests and the way in which many kinds are based on contingent social processes subject to human responsibility. (shrink)

Philosophers continue to debate both the actual and the ideal roles of values in science. Recently, Eric Winsberg has offered a novel, model-based challenge to those who argue that the internal workings of science can and should be kept free from the influence of social values. He contends that model-based assignments of probability to hypotheses about future climate change are unavoidably influenced by social values. I raise two objections to Winsberg’s argument, neither of which can wholly undermine its conclusion but (...) each of which suggests that his argument exaggerates the influence of social values on estimates of uncertainty in climate prediction. I then show how a more traditional challenge to the value-free ideal seems tailor-made for the climate context. (shrink)

I address options for providing scientific policy advice and explore the relation between scientific knowledge and political, economic and moral values. I argue that such nonepistemic values are essential for establishing the significance of questions and the relevance of evidence, while, on the other hand, such social choices are the prerogative of society. This tension can be resolved by recognizing social values and identifying them as separate premises or as commissions while withholding commitment to them, and by elaborating a plurality (...) of policy packages that envisage the implementation of different social goals. There are limits to upholding the value-free ideal in scientific research. But by following the mentioned strategy, science can give useful policy advice by leaving the value-free ideal largely intact. Such scientific restraint avoids the risk of appearing to illegitimately impose values on the public and could make the advice given more trustworthy. (shrink)

Philosophers of science, particularly those working on science and values, often talk about the need for science to be socially responsible. However, what this means is not clear. In this paper, we review the contributions of philosophers of science to the debate over socially responsible science and explore the dimensions that a fruitful account of socially responsible science should address. Our review shows that offering a comprehensive account is difficult. We contend that broad calls for socially responsible science that fail (...) to attend to relevant dimensions are not the solution, as they preclude meaningful changes to research institutions and practices. We conclude that narrower, more explicit accounts are more likely to lead to substantive transformation. (shrink)

Ghostwriting scandals are pervasive in industry-funded biomedical research, and most responses to them have presumed that they represent a sharp transgression of the norms of scientific authorship. I argue that in fact, ghostwriting represents a continuous extension of current socially accepted authorship practices. I claim that the radically collaborative, decentralized, interdisciplinary research that forms the gold standard in medicine is in an important sense unauthored, and that this poses a serious problem in applied social epistemology. It is no easy matter (...) to find procedural or architectural solutions that can secure epistemic trust and accountability for collaborative publishing in biomedicine. (shrink)

Philosophers of science have paid close attention to climate simulations as means of projecting the severity and effects of climate change, but have neglected the full diversity of methods in climate science. This paper shows the philosophical richness of another method in climate science: the practice of using paleoclimate analogues to inform our climate projections. First, I argue that the use of paleoclimate analogues can offer important insights to philosophers of the historical sciences. Rather than using the present as a (...) guide to the past, as is common in the historical sciences, paleoclimate analogues involve using the past as a guide to the future. I thereby distinguish different methods in the historical sciences and argue that these distinctions bear on debates over whether the historical sciences can produce generalizations or predictions. Second, I suggest that paleoclimate analogues might actually be considered a type of climate model, and, as such, their use expands on common characterizations of models to include those that are full-scale, naturally occurring, and non-manipulable. (shrink)

The United Kingdom Climate Impacts Programme’s UKCP09 project makes high-resolution projections of the climate out to 2100 by post-processing the outputs of a large-scale global climate model. The aim of this paper is to describe and analyse the methodology used and then urge some caution. Given the acknowledged systematic, shared errors of all current climate models, treating model outputs as decision-relevant projections can be significantly misleading. In extrapolatory situations, such as projections of future climate change, there is little reason to (...) expect that post-processing of model outputs can correct for the consequences of such errors. This casts doubt on our ability, today, to make trustworthy probabilistic projections at high resolution out to the end of the century. (shrink)

This article critically examines a recent philosophical debate on the role of values in climate change forecasts, such as those found in assessment reports of the Intergovernmental Panel on Climate Change. On one side, several philosophers insist that the argument from inductive risk, as developed by Rudner and Douglas among others, applies to this case. AIR aims to show that ethical value judgments should influence decisions about what is sufficient evidence for accepting scientific hypotheses that have implications for policy issues. (...) Advocates of extending AIR to climate science claim that values are deeply... (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 article examines the relevance of survey data of scientists’ attitudes about science and values to case studies in philosophy of science. We describe two methodological challenges confronting such case studies: 1) small samples, and 2) potential for bias in selection, emphasis, and interpretation. Examples are given to illustrate that these challenges can arise for case studies in the science and values literature. We propose that these challenges can be mitigated through an approach in which case studies and survey methods (...) are viewed as complementary, and use data from the Toolbox Dialogue Initiative to illustrate this claim. (shrink)

Scientific models can be performative: they can causally affect the phenomena they are intended to represent. The existing literature offers two responses. The appraisal view emphasizes that performativity can sometimes be a good-making model attribute, e.g., when predictions steer the public’s behavior in desirable ways. The mitigation view seeks to endogenize agents’ behavioral response to model-issued forecasts to get rid of performativity instead. This paper argues that neither approach is fully compelling: the appraisal view encounters severe concerns about moral values (...) illegitimately encroaching on how modelers construct and use models, while the mitigation view fails to acknowledge that endogenization is itself a choice that involves substantive value-judgments relating to the desirability of certain social outcomes. (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)

Wendy S. Parker and I have advanced an inductive-risk approach to the provision of climate information that relies on the contextual values of information users. This approach aims to improve the e...

I examine the construction and evaluation of machine learning binary classification models. These models are increasingly used for societal applications such as classifying patients into two categories according to the presence or absence of a certain disease like cancer and heart disease. I argue that the construction of ML classification models involves an optimisation process aiming at the minimization of the inductive risk associated with the intended uses of these models. I also argue that the construction of these models is (...) underdetermined by the available data, and that this makes it necessary for ML modellers to make social value judgments in determining the error costs used in ML optimization. I thus suggest that the assessment of the inductive risk with respect to the social values of the intended users is an integral part of the construction and evaluation of ML classification models. I also discuss the implications of this conclusion for the philosophical debate concerning inductive risk. (shrink)

In this paper I argue for a distinction between subjective and value laden aspects of judgements showing why equating the former with the latter has the potential to confuse matters when the goal is uncovering the influence of political influences on scientific practice. I will focus on three separate but interrelated issues. The first concerns the issue of ‘verification’ in computational modelling. This is a practice that involves a number of formal techniques but as I show, even these allegedly objective (...) methods ultimately rely on subjective estimation and evaluation of different types of parameters. This has implications for my second point which relates to uncertainty quantification—an assessment of the degree of uncertainty present in a particular modelling scenario. I argue that while this practice also involves subjective elements, in no way does that detract from its status as an epistemic exercise. Finally I discuss the relation between accuracy and uncertainty and how each relates to judgements that embody social/ethical/political concerns, in particular those associated with high consequence systems. (shrink)

Mathematical models are often expected to provide not only predictions about the phenomenon that they represent, but also explanations. These explanations are answers to why-questions and particularly answers to why the predicted phenomenon should occur. For instance, models can be used to calculate when the next total solar eclipse will happen, and then to explain why it will take place on July 2, 2019. In this regard we can obtain explanations from a model if we can solve the model equations (...) which govern the phenomenon under study. But some equations have no explicit solution or are too complicated to solve. In these cases it is difficult for a... (shrink)

Projections of future climate change cannot rely on a single model. It has become common to rely on multiple simulations generated by Multi-Model Ensembles (MMEs), especially to quantify the uncertainty about what would constitute an adequate model structure. But, as Parker points out (2018), one of the remaining philosophically interesting questions is: “How can ensemble studies be designed so that they probe uncertainty in desired ways?” This paper offers two interpretations of what General Circulation Models (GCMs) are and how MMEs (...) made of GCMs should be designed. In the first interpretation, models are combinations of modules and parameterisations; an MME is obtained by “plugging and playing” with interchangeable modules and parameterisations. In the second interpretation, models are aggregations of expert judgements that result from a history of epistemic decisions made by scientists about the choice of representations; an MME is a sampling of expert judgements from modelling teams. We argue that, while the two interpretations involve distinct domains from philosophy of science and social epistemology, they both could be used in a complementary manner in order to explore ways of designing better MMEs. (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)

We give an overview of the practice of developing and using complex climate models, as seen from experiences in a major climate modelling center and through participation in the Coupled Model Intercomparison Project. We discuss the construction and calibration of models; their evaluation, especially through use of out-of-sample tests; and their exploitation in multi-model ensembles to identify biases and make predictions. We stress that adequacy or utility of climate models is best assessed via their skill against more naïve predictions. The (...) framework we use for making inferences about reality using simulations is naturally Bayesian, and has many points of contact with more familiar examples of scientific epistemology. While the use of complex simulations in science is a development that changes much in how science is done in practice, we argue that the concepts being applied fit very much into traditional practices of the scientific method, albeit those more often associated with laboratory work. (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)

The assessments issued by the Intergovernmental Panel on Climate Change (IPCC) aim to provide policy-makers with an objective source of information about the various causes of climate change, the projected consequences for the environment and human affairs, and the options for adaptation and mitigation. But what, in this context, is meant by ‘objective’? In practice, in an effort to address internal and external criticisms, the IPCC has regularly revised its methodological procedures; some of these procedures seem to meet the requirements (...) of objectivity, at least as understood in a specific sense, but the relationship between objectivity and value-neutrality requires further investigation. The aim of this paper is to offer an appropriate philosophical account of objectivity, reconcilable with the fact that the IPCC is not value-free. I argue that Sandra Harding’s notion of strong objectivity is particularly well suited to this goal, and I examine the extent to which the current IPCC procedures match her account. (shrink)

This paper investigates the case of enzyme classification to evaluate different ideals for regulating values in science. I show that epistemic and non-epistemic considerations are inevitably and untraceably entangled in enzyme classification, and argue that this has significant implications for the two main kinds of views on values in science, namely, Epistemic Priority Views and Joint Satisfaction Views. More precisely, I argue that the case of enzyme classification poses a problem for the usability and descriptive accuracy of these two views. (...) The paper ends by suggesting that these two views provide different but complementary perspectives, and that both are useful for evaluating values in science. (shrink)

Using past episodes of climate change as a source of evidence to inform our projections about contemporary climate change requires establishing the extent to which episodes in the deep past are analogous to the current crisis. However, many scientists claim that contemporary rates of climate change (e.g., rates of carbon emissions or temperature change) are unprecedented, including compared to episodes in the deep past. If so, this would limit the utility of paleoclimate analogues. In this paper, I show how a (...) data adjustment procedure called “temporal scaling,” which must be applied to both contemporary and past rate data, complicates the claim that contemporary rates are truly unprecedented. On top of giving actionable recommendations to scientists, this paper advances the philosophical literature concerning the use of models that are known to be somewhat disanalogous to their target systems. (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)

While no one denies that science depends on epistemic values, many philosophers of science have wrestled with the appropriate role of non-epistemic values, such as social, ethical, and political values. Recently, philosophers of science have overwhelmingly accepted that non-epistemic values should play a legitimate role in science. The recent philosophical debate has shifted from the value-free ideal in science to questions about how science should incorporate non-epistemic values. This article engages with such questions through an exploration of the environmental sciences. (...) These sciences are a mosaic of diverse fields characterized by interdisciplinarity, problem-orientation, policy-directedness, and ubiquitous nonepistemic values. This article addresses a frequently voiced concern about many environmental science practices: that they ‘crowd out’ or displace significant non-epistemic values by either (1) entailing some non-epistemic values, rather than others, or by (2) obscuring discussion of non-epistemic values altogether. With three detailed case studies e monetizing nature, nature-society dualism, and ecosystem health e we show that the alleged problem of crowding out emerges from active debates within the environmental sciences. In each case, critics charge that the scientific practice in question displaces nonepistemic values in at least one of the two senses distinguished above. We show that crowding out is neither necessary nor always harmful when it occurs. However, we do see these putative objections to the application of environmental science as teaching valuable lessons about what matters for successful environmental science, all things considered. Given the significant role that many environmental scientists see for non-epistemic values in their fields, we argue that these cases motivate lessons about the importance of value-flexibility (that practices can accommodate a plurality of non-epistemic values), transparency about value-based decisions that inform practice, and environmental pragmatism. (shrink)

Between the fourth and the recent fifth IPCC report, science as well as policy making have made great advances in dealing with uncertainties in global climate models. However, the uncertainties public decision making has to deal with go well beyond what is currently addressed by policy makers and climatologists alike. It is shown in this paper that within an anthropocentric framework, a whole hierarchy of models from various scientific disciplines is needed for political decisions as regards climate change. Via what (...) is sometimes referred to as ‘uncertainty cascade’ in the technical literature, the uncertainties of various models accumulate in the input to political decision making. This paper aims to chart the uncertainties in the multi-disciplinary enterprise of current climate modeling in broad strokes. It is shown that the uncertainty cascade makes it impossible to quantify uncertainties in the form of probability estimates. Moreover the paper highlights how global climate models fail to provide probability estimates. A better treatment of the uncertainties of climate predictions on the political level would require an overhaul of the current IPCC practice that separates the various scientific fields in various working groups. (shrink)

This is the second of three parts of an introduction to the philosophy of climate science. In this second part about modelling climate change, the topics of climate modelling, confirmation of climate models, the limits of climate projections, uncertainty and finally model ensembles will be discussed.

Given the complexity of most phenomena, we have to delegate much epistemic work to other knowers and we must find reasons for relying on these specific knowers and not others. In our societies, these other knowers are often called experts and we rely on their epistemic authority more and more. For many complex phenomena such as climate change, genetically modified crops, and immunization, the experts that are called upon are scientific experts. For that reason, finding good reasons and justification for (...) deferring to their knowledge is of paramount societal importance. As we shall see, many have analyzed this epistemic dependence on scientific experts and have tried to show in what contexts are there good... (shrink)

The argument from inductive risk is considered to be one of the strongest challenges for value-free science. A great part of its appeal lies in the idea that even an ideal epistemic agent—the “perfect scientist” or “scientist qua scientist”—cannot escape inductive risk. In this paper, I scrutinize this ambition by stipulating an idealized Bayesian decision setting. I argue that inductive risk does not show that the “perfect scientist” must, descriptively speaking, make non-epistemic value-judgements, at least not in a way that (...) undermines the value-free ideal. However, the argument is more successful in showing that there are cases where the “perfect scientist” should, normatively speaking, use non-epistemic values. I also show that this is possible without creating problems of illegitimate prescription and wishful thinking. Thus, while inductive risk does not refute value-freedom completely, it still represents a powerful critique of value-free science. (shrink)

Current debates over inductive risk and the role of values in science have largely revolved around the question of the moral responsibilities of scientists: Do scientists have the duty to consider the potential non-epistemic consequences of theories they advocate and, if yes, what values should be taken into account in decision-making? The paper discusses two different – though potentially complementary – responses to this question: a) H. Douglas’s view that scientists should avoid causing reckless or negligent harm to others as (...) a result of the decisions they make and b) K. Elliott’s Multiple Goals Criterion. Drawing from the case of potential coronavirus transmission by sharing the Holy Communion that recently divided Greek society and medical experts, it shows the tensions emerging between autonomy and the moral responsibilities of scientists, when the boundaries of science are blurred and the epistemic goal of truth is inconsistent with alternative goals. It argues that the balance attempted between scientific principles and religious beliefs was unattainable and concludes that the need to distinguish between epistemic and non-epistemic values, which is traditionally related to the ideal of value free science, should be reconsidered and even prioritized among the responsibilities of scientists. (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)

Practice-centric and theory-centric approaches in philosophy of science are described and contrasted. The contrast is developed through an examination of their different treatments of the underdetermination problem. The practice-centric approach is illustrated by a summary of comparative research on approaches in the biology of behavior. The practice-centric approach is defended against charges that it encourages skepticism regarding the sciences.