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

Recently, invasion biologists have argued that some of the skepticism expressed in the scientific and lay literatures about the risks of invasive species and other aspects of the consensus within invasion biology is a kind of science denialism. This paper presents an argument that, while some claims made by skeptics of invasion biology share important features with paradigm cases of science denialism, others express legitimate ethical concerns that, even if one disagrees, should not be dismissed as denialist. Further, this case (...) illustrates a more general point about ethical disagreement within sciences like invasion biology that constitutively pursue non-epistemic goals and values. While philosophers of science have argued that epistemic disagreement within science can be productive as heterogeneous epistemic communities “hedge their bets,” the case of invasion biology shows how non-epistemic or ethical disagreement within sciences, while carrying significant risks, can also be epistemically and non-epistemically valuable. (shrink)

Experimental modeling is the construction of theoretical models hand in hand with experimental activity. As explained in Section 1, experimental modeling starts with claims about phenomena that use abstract concepts, concepts whose conditions of realization are not yet specified; and it ends with a concrete model of the phenomenon, a model that can be tested against data. This paper argues that this process from abstract concepts to concrete models involves judgments of relevance, which are irreducibly normative. In Section 2, we (...) show, on the basis of several case studies, how these judgments contribute to the determination of the conditions of realization of the abstract concepts and, at the same time, of the quantities that characterize the phenomenon under study. Then, in Section 3, we compare this view on modeling with other approaches that also have acknowledged the role of relevance judgments in science. To conclude, in Section 4, we discuss the possibility of a plurality of relevance judgments and introduce a distinction between locally and generally relevant factors. (shrink)

Scientific evidence and scientific values under risk and uncertainty are strictly connected from the point of view of Peirce’s pragmaticism. In addition, economy and statistics play a key role in both choosing and testing hypotheses. Hence we may show also the connection between the methodology of the economy of research and statistical frequentism, both originating from pragmaticism. The connection is drawn by the regulative principles of synechism, tychism and uberty. These principles are values that have both epistemic and non-epistemic dimension. (...) They concern both the decisions to test a hypothesis as well as inductive risk. The validity of this result stems from the values cost–benefit analysis imposes on scientific inquiry. Values associated with the economy of research are important not only in the pre-test phases of generating hypotheses but also when hypotheses are effectively tested. Peirce took these economic considerations to leave room for an interpretation of probability which is not only a frequentist and propensity-theoretic but also a conceptualist one referring to degrees of belief. We show that this leeway nonetheless agrees with the theory of the economy of scientific methods. (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)

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)

This article argues that the controversy over genetically modified crops is best understood not in terms of the supposed bias, dishonesty, irrationality, or ignorance on the part of proponents or critics, but rather in terms of differences in values. To do this, the article draws on and extends recent work of the role of values and interests in science, focusing particularly on inductive risk and epistemic risk, and it shows how the GMO debate can help to further our understanding of (...) the various epistemic risks that are present in science and how these risks might be managed. (shrink)

While dissent is key to successful science, it is not always beneficial. By requiring scientists to respond to objections, epistemically detrimental dissent (EDD) consumes resources that could be better devoted to furthering scientific discovery. Moreover, bad-faith dissent can create a chilling effect on certain lines of inquiry and make settled controversies seem open to debate. Such dissent results in harm to scientific progress and the public policy that depends on this science. Biddle and Leuschner propose four criteria that draw on (...) inductive risk as a method for separating this EDD from beneficial dissent while de Melo-Martín and Intemann reject this approach for failing to capture paradigmatic instances of EDD. Against de Melo-Martín and Intemann’s objections, I propose the inductive risk account can be saved and strengthened through the following modifications: (1) removing the requirement that the four conditions of EDD be jointly satisfied, (2) requiring that each criterion be measured as a matter of degree rather than as a binary, and (3) requiring that the four criteria are measured holistically. These modifications not only mitigate the criticisms but produce five benefits over Biddle and Leuschner’s account, including: (1) capturing paradigmatic instances of EDD, (2) reflecting the degree to which an instance of EDD is problematic, (3) capturing the interactions between criteria, (4) avoiding legitimizing inappropriate dissent, and (5) reflecting changes to the epistemic standing of dissent. As such, I argue that the modified IndRA provides a powerful tool for identifying EDD and strengthening science. (shrink)

. Science at the interface with society is regarded with mistrust among parts of the public. Scientific judgments on matters of practical concern are not infrequently suspected of being incompetent and biased. I discuss two proposals for remedying this deficiency. The first aims at strengthening the independence of science and suggests increasing the distance to political and economic powers. The drawback is that this runs the risk of locking science in an academic ivory tower. The second proposal favors “counter-politicization” in (...) that research is strongly focused on projects “in the public interest,” that is, on projects whose expected results will benefit all those concerned by these results. The disadvantage is that the future use of research findings cannot be delineated reliably in advance. I argue that the underlying problem is the perceived lack of relevance and reliability and that pluralism is an important step toward its solution. Pluralism serves to stimulate a more inclusive research agenda and strengthens the well-testedness of scientific approaches. However, pluralism also prevents the emergence of clear-cut practical suggestions. Accordingly, pluralism is part of the solution to the credibility crisis of science, but also part of the problem. In order for science to be suitable as a guide for practice, the leeway of scientific options needs to be narrowed – in spite of uncertainty in epistemic respect. This reduction can be achieved by appeal to criteria that do not focus on the epistemic credentials of the suggestions but on their appropriateness in practical respect. (shrink)

The increasing success of the evidence-based policy movement is raising the demand of empirically informed decision making. As arguably any policy decision happens under conditions of uncertainty, following our best available evidence to reduce the uncertainty seems a requirement of good decision making. However, not all the uncertainty faced by decision makers can be resolved by evidence. In this paper, we build on a philosophical analysis of uncertainty to identify the boundaries of scientific advice in policy decision making. We start (...) by introducing a distinction between empirical and non-empirical types of uncertainty, and we explore the role of two non-empirical uncertainties in the context of policy making. We argue that the authority of scientific advisors is limited to empirical uncertainty and cannot extend beyond it. While the appeal of evidence-based policy rests on a view of scientific advice as limited to empirical uncertainty, in practice there is a risk of over reliance on experts beyond the legitimate scope of their authority. We conclude by applying our framework to a real-world case of evidence-based policy, where experts have overstepped their boundaries by ignoring non-empirical types of uncertainty. (shrink)

A popular view in philosophy of science contends that scientific reasoning is objective to the extent that the appraisal of scientific hypotheses is not influenced by moral, political, economic, or social values, but only by the available evidence. A large body of results in the psychology of motivated-reasoning has put pressure on the empirical adequacy of this view. The present study extends this body of results by providing direct evidence that the moral offensiveness of a scientific hypothesis biases explanatory judgment (...) along several dimensions, even when prior credence in the hypothesis is controlled for. Furthermore, it is shown that this bias is insensitive to an economic incentive to be accurate in the evaluation of the evidence. These results contribute to call into question the attainability of the ideal of a value-free science. (shrink)

Having offered the “argument from bad lot”, Bas van Fraassen has raised an important criticism on the Inference to the Best Explanation (IBE) and challenged scientific realism. Regardless of scientific realism, and given the reliance of today's scientific methods on IBE, this criticism poses a deeper threat to the validity of scientific enquiry. In this article, we will try to provide a way to deal with this threat, according to the structure of the scientific community. Some structural features of the (...) contemporary scientific community have caused the scientific enquiry to be limited to the science derived from the Western tradition and deprived it of the theoretical opportunities of various traditions. The main claim of this article is that paying attention to different traditions together to produce science is a good way to expand scientific enquiry and deal with the mentioned threat. In the first section, we will depict how the argument from bad lot threatens the validity of scientific enquiry. In the second section, we discuss the close relationship between science and tradition, and then examine the status of this relationship in the contemporary scientific society. The final section is devoted to proposing the idea of pluralism regarding the use of the theoretical opportunities of different traditions in scientific enquiry, as a proposed solution to counter this threat. (shrink)

A number of areas of biology raise questions about what is of value in the natural environment and how we ought to behave towards it: conservation biology, environmental science, and ecology, to name a few. Based on my experience teaching students from these and similar majors, I argue that the field of environmental ethics has much to teach these students. They come to me with pent-up questions and a feeling that more is needed to fully engage in their subjects, and (...) I believe some exposure to environmental ethics can help focus their interests and goals. I identify three primary areas in which environmental ethics can con- tribute to their education. The first is an examination of who (or what) should be considered to be part of our moral community (i.e., the community to whom we owe direct duties). Is it humans only? Or does it include all sentient life? Or all life? Or ecosystems considered holistically? Often, readings implicitly assume one or more of these answers; the goal is to make the student more sensitive to these implicit claims and to get them to think about the different reasons that support them. The second area, related to the first, is the application of the different answers concerning the extent of the ethical community to real environmental issues and problems. Students need to be aware of how the different answers concerning the moral community can imply conflicting answers for how we should act in certain cases and to think about ways to move toward conflict resolution. The third area in which environmental ethics can contribute is a more conceptual one, focusing on central concepts such as biodiversity, sustainability, species, and ecosystems. Exploring and evaluating various meanings of these terms will make students more reflective and thoughtful citizens and biologists, sensitive to the implications that different conceptual choices make. (shrink)

This paper examines the conditions of trustworthy science advice mechanisms, in which scientists have a mandated role to inform public policymaking. Based on the literature on epistemic trust and public trust in science, we argue that possession of relevant expertise, justified moral and political considerations, as well as proper institutional design are conditions for trustworthy science advice. In order to assess these conditions further, we explore the case of temporary advisory committees in Norway. These committees exemplify a de facto trusted (...) and seemingly well-functioning science advice mechanism. Still, this mechanism turns out to poorly realize some central conditions of trustworthy science advice. From this we draw three lessons. Firstly, it remains crucial to distinguish between well-placed and de facto trust. Secondly, some conditions of trustworthy science advice seem more significant than others and there are thresholds for realizing each condition. Thirdly, not only does the institutional design and organization of science advice matter more than often recognized; the trust and trustworthiness of the broader social and political context and institutional environment make a difference as well. (shrink)

The argument from inductive risk claims that judgments about the moral severity of errors are relevant to decisions about what should count as sufficient evidence for accepting claims. While this idea has been explored in connection with evidence required for the approval of pharmaceuticals, the role of inductive risk in the post-approval process has been largely neglected. In this article, we examine the ethics of inductive risk in connection with revisions to the product monograph for OxyContin in Canada, which understates (...) the risks of addiction and abuse associated with this drug. Using the concept of inductive risk, we consider what evidence should have been sufficient for Health Canada to revise the product monograph for OxyContin. Given the stakes involved, we argue that a less strict standard of evidence would have been appropriate, yet HC in fact took the opposite course, insisting upon a higher standard of evidence than it normally requires. In addition to providing a novel perspective on the opioid crisis in Canada, this article contributes to existing philosophical work by demonstrating that inductive risks in the post-approval stage are important and linked to pre-approval inductive risks. (shrink)

Simple extrapolation is the orthodox approach to extrapolating from clinical trials in evidence-based medicine: extrapolate the relative effect size from the trial unless there is a compelling reason not to do so. I argue that this method relies on a myth and a fallacy. The myth of simple extrapolation is the idea that the relative risk is a ‘golden ratio’ that is usually transportable due to some special mathematical or theoretical property. The fallacy of simple extrapolation is an unjustified argument (...) from ignorance: we conclude that the relative effect size is transportable in the absence of evidence to the contrary. In short, simple extrapolation is a deeply problematic solution to the problem of extrapolation. (shrink)

There has been much debate about whether the concept of disease articulated in Boorse’s biostatistical theory is value-neutral or value-laden. Here, I want to examine whether this debate matters. I suggest that there are two basic respects in which value-ladenness might be important: it could threaten either scientific legitimacy or moral permissibility. I argue that value-ladenness does not threaten the scientific legitimacy of our disease-concept because the concept makes little difference to the formulation and testing of scientific hypotheses. Likewise, even (...) if our disease-concept is value-laden, this does not show it is morally impermissible. To determine its permissibility, we must regard it as a tool to structure social institutions. Seen in that way, whether our disease-concept is morally permissible is a consequentialist matter and depends exquisitely on unanswered empirical questions. (shrink)

Scientific risk evaluations are constructed by specific evidence, value judgements and biological background assumptions. The latter are the framework-setting suppositions we apply in order to understand some new phenomenon. That background assumptions co-determine choice of methodology, data interpretation, and choice of relevant evidence is an uncontroversial claim in modern basic science. Furthermore, it is commonly accepted that, unless explicated, disagreements in background assumptions can lead to misunderstanding as well as miscommunication. Here, we extend the discussion on background assumptions from basic (...) science to the debate over genetically modified (GM) plants risk assessment. In this realm, while the different political, social and economic values are often mentioned, the identity and role of background assumptions at play are rarely examined. We use an example from the debate over risk assessment of stacked genetically modified plants (GM stacks), obtained by applying conventional breeding techniques to GM plants. There are two main regulatory practices of GM stacks: (i) regulate as conventional hybrids and (ii) regulate as new GM plants. We analyzed eight papers representative of these positions and found that, in all cases, additional premises are needed to reach the stated conclusions. We suggest that these premises play the role of biological background assumptions and argue that the most effective way toward a unified framework for risk analysis and regulation of GM stacks is by explicating and examining the biological background assumptions of each position. Once explicated, it is possible to either evaluate which background assumptions best reflect contemporary biological knowledge, or to apply Douglas' 'inductive risk' argument. (shrink)

In this paper I analyze the process by which modelers in systems biology arrive at an adequate representation of the biological structures thought to underlie data gathered from high-throughput experiments. Contrary to views that causal claims and explanations are rare in systems biology, I argue that in many studies of gene regulatory networks modelers aim at a representation of causal structure. In addressing modeling challenges, they draw on assumptions informed by theory and pragmatic considerations in a manner that is guided (...) by an interventionist conception of causal structure. While doubts have been raised about the applicability of this notion of causality to complex biological systems, it is here seen to be an adequate guide to inquiry. (shrink)

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)

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...

The relevance of scientific knowledge for science and technology policy and regulation has led to a growing debate about the role of values. This article contributes to the clarification of what specific functions cognitive and noncognitive values adopt in knowledge generation and decisions, and what consequences the operation of values has for policy making and regulation. For our analysis, we differentiate between three different types of decision approaches, each of which shows a particular constellation of cognitive and noncognitive values. Our (...) objectives are to present a structured analysis of the varying functions that different kinds of values can adopt, as well as the value-related tensions and trade-offs they give rise to. We argue that the operation of noncognitive values in scientific knowledge generation, policy, and regulatory decision making can be understood as an enabling factor, rather than a limiting one. (shrink)

This paper argues that research on normative issues in the life sciences will benefit from a tighter integration of philosophy of science. We examine research on ethical, legal and social issues in the life sciences (“ELSI”) and discuss three illustrative examples of normative issues that arise in different areas of the life sciences. These examples show that important normative questions are highly dependent on epistemic issues which so far have not been addressed sufficiently in ELSI, RRI and related areas of (...) research. Accordingly, we argue for the integration of research on the epistemic aspects of the relevant areas of science into ELSI research to provide a better basis for addressing normative questions. (shrink)

Efforts to promote responsible conduct of research (RCR) should take into consideration how scientists already conceptualize the relationship between ethics and science. In this study, we investigated how scientists relate ethics and science by analyzing the values expressed in interviews with fifteen science faculty members at a large midwestern university. We identified the values the scientists appealed to when discussing research ethics, how explicitly they related their values to ethics, and the relationships between the values they appealed to. We found (...) that the scientists in our study appealed to epistemic and ethical values with about the same frequency, and much more often than any other type of value. We also found that they explicitly associated epistemic values with ethical values. Participants were more likely to describe epistemic and ethical values as supporting each other, rather than trading off with each other. This suggests that many scientists already have a sophisticated understanding of the relationship between ethics and science, which may be an important resource for RCR training interventions. (shrink)

The UK-based deliberations that led up to the legalisation of two new ‘mitochondrial donation’ techniques in 2015, and which continued after that time as regulatory details were determined, featured a division of advisory labour that is common when decisions are made about new technologies. An expert panel was convened by the Human Fertilisation and Embryology Authority, charged with assessing the scientific and technical aspects of these techniques. Meanwhile, the Nuffield Council on Bioethics addressed the ethical issues. While this division of (...) labour was undertaken in the name of thoroughness, I argue here that it can have the unintended consequence that hybrid questions that simultaneously involve ethical and technical aspects—especially questions about where to set evidential thresholds for the acceptance of new technology—do not receive enough attention. (shrink)

Against the ideal of value-free science I argue that science is not––and cannot be––value-free and that relevant values are both cognitive and moral. I develop an argument by indicating various aspects of the value-ladenness of science. The recognition of the value-ladenness of science requires rethinking our understanding of the rationality and responsibility of science. Its rationality cannot be seen as merely instrumental––as it was seen by the ideal of value-free science––for this would result in limiting the autonomy of science and (...) reducing scientists to “minds to hire”. The scientific rationality must be seen as practical rationality which takes into account the full horizon of values. The scientific responsibility must also be broaden in scope and type. On this basis I draw three practical conclusions concerning the organization of research and training of young scientists, appealing to Plato’s claim that those most capable of healing are also those most capable of harming. (shrink)

Although the presence of cognitive values in science has been accepted for half a century, until recently it was claimed that the presence of non-cognitive values threatened the rationality and objectivity of science and it was a sign of a scientist’s weakness. This view appeared to be correct when cognitive and non-cognitive values were treated dichotomously, and science was seen as a set of theories and procedures. The analysis of science as a social practice shows however that this dichotomy cannot (...) be maintained and that the scientist, when planning and conducting research, makes assumptions which include value judgments encompassing certain non-cognitive values. Ignoring the presence of non-cognitive values does not secure objectivity and rationality of science. On the contrary, since they are constitutive elements of scientific research, pretending that they do not work in research exposes science to ideologization. Rational subordination of science to them becomes a vehicle and a warrant of not only rationality but also objectivity and social responsibility of science. This in turn allows us to restore the proper place of science in culture. (shrink)

Cet article défend l’idée que l’on peut distinguer quatre niveaux d’analyse au sein des sciences sociales (y compris l’économie) – à savoir, a) un niveau descriptif statistique, b) un niveau explicatif causal, c) un niveau explicatif téléologique, et d) un niveau téléologique prescriptif. Généralement, les sciences sociales ne considèrent que les niveaux a) et b). L’exclusion du niveau c) peut conduire à considérer comme des « anomalies » certains comportements qui ne sont pas compatibles avec des théories comme celle du (...) choix rationnel ou celle de l’utilité espérée – à savoir, des théories qui adoptent une attitude dite de « rationalité instrumentale ». Inclure le niveau c) dans la réflexion implique de considérer la « rationalité pratique » et cela rend ces anomalies « raisonnables ». L’article prend pour cadre théorique la notion de causalité et la téléologie d’Aristote. La première section introduit ces notions, tandis que la deuxième section explore les points de vue contemporains sur la causalité et la téléologie. La troisième section introduit des arguments pour établir la légitimité de l’usage des valeurs en sciences sociales. Cette étape est nécessaire, car les causes finales des explications téléologiques dans le domaine des choses humaines sont bien, en définitive, des valeurs. Ces discussions ouvrent la voie à l’introduction, dans la quatrième et dernière section, des quatre niveaux analytiques susmentionnés. Plus précisément, dans le cas de l’économie, cette discussion se fonde sur la classification des disciplines économiques chez Carl Menger. (shrink)

Mitä tiedollista hyötyä tieteilijöille voi olla tutkimusyhteistyöstä taiteilijoiden kanssa? Taiteilijoiden kanssa työskennelleet tieteilijät usein kyllä pitävät kokemusta kiehtovana, mutta sen hyötyjen tarkka kuvaaminen vaikuttaa vaikealta. Monialaisen yhteistyön odotetaan usein lisäävän tutkimuksen yhteiskunnallista vaikuttavuutta, mutta odotus ei sovellu juuri tieteilijöiden ja taiteilijoiden yhteistyöhön kovinkaan hyvin. Selkeytän sosiaalisessa epistemologiassa ja feministisessä tieteenfilosofiassa esitettyjen ajatusten ja argumenttien sekä kahden tapausesimerkin avulla tapoja, joilla tieteilijöiden yhteistyö taiteilijoiden kanssa voi olla tiedollisesti hedelmällistä. Taiteen ja taiteellisen tutkimuksen keinoin voi joskus tuottaa tietoa. Tiedollisesti tärkeämpänä pidän kuitenkin (...) sitä, miten taide voi tarjota huomaamatta jääneitä näkökulmia sekä tutkimuskohteeseen että tutkimuksen tekemisen tapaan, ja tiedollisesti hyödyllistä kritiikkiä. (shrink)

When discussing scientific objectivity, many philosophers of science have recently focused on accounts that can be applied in practice when assessing the objectivity of something. It has become clear that in different contexts, objectivity is realized in different ways, and the many senses of objectivity recognized in the recent literature seem to be conceptually distinct. I argue that these diverse ‘applicable’ senses of scientific objectivity have more in common than has thus far been recognized. I combine arguments from philosophical discussions (...) of trust, from negative accounts of objectivity, and from the recent literature on epistemic risks. When we call X objective, we endorse it: we say that we rely on X, and that others should do so too. But the word ‘objective’ is reserved for a specific type of reliance: it is based on the belief that important epistemic risks arising from our imperfections as epistemic agents have been effectively averted. All the positive senses of objectivity identify either some risk of this type, or some efficient strategy for averting one or more such risks. (shrink)

Questions of objectivity involve many general philosophy of science issues; when directed toward the social sciences, even more complex issues surface about the status of the social sciences, e.g. can they be sciences as are the natural sciences? This paper does not take on this mass of issues directly, but instead argues for more restricted theses, in particular that questions about objectivity in the social sciences are often usefully seen as local empirical issues. I look at arguments around underdetermination, value (...) ladenness, the indeterminancy or nonquantitative nature of social science categories or attributes, and traditional ontological debates over materialism and idealism. I show that in all these cases some of the key issues about objectivity are specific empirical issues in the social sciences. (shrink)

Unlike drugs and medical devices, for which long standing and continuously improving quality assurance/quality control infrastructures exist, many nano-based products lack well-defined standards that are useful to manufacturers and regulators. Inherent variabilities in nanoparticle sizes and shapes, their large surface-to-volume ratios, and their mesoscale interactions with subcellular structures, suggest new complexities and challenges that must be met before widespread application of nanomedicines can be expected.

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)

The trustworthiness of nutrition science has been questioned recently. According to the critics, the food industry has corrupted scientists in the field. I argue that the worries that commercialization threatens the epistemic trustworthiness of nutrition science are indeed well-founded. However, it is problematic that the discussion has revolved around how funding can threaten the integrity of researchers and the methodological quality of the studies. By extending Wilholt’s :233–253, 2013) account of epistemic trustworthiness, I argue that when assessing the epistemic trustworthiness (...) of research that forms the basis for different health policy measures, it is necessary to evaluate research at the macro-level and whether agenda setting advances the goals that are assigned to the field. The prevalence of commercial funding becomes problematic if it leads to a situation where the body of available evidence that is used for making health policy decisions does not reflect the shared sense of what epistemic and non-epistemic goals of the inquiry are important. (shrink)

Several types of inferences are employed in the diagnosis and prognosis of patients with brain injuries and disorders of consciousness. These inferences introduce unavoidable uncertainty, and can be evaluated in light of inductive risk: the epistemic and nonepistemic risks of being wrong. This article considers several ethically significant inductive risks generated by and interacting with inferences about patients with disorders of consciousness, and argues for prescriptive measures to manage and mitigate inductive risk in the context of disorders of consciousness.

One of the most important issues in the philosophy of science in recent decades is to assess the permissibility of the involvement of background and non-scientific factors in science and to place them next to evidence or to involve them in the process of weighing evidence. Proponents of the value-free science ideal have considered any intervention of this kind as a blow to the objectivity of science and slipping in the process of science. One of the important arguments in criticizing (...) this ideal is that of inductive risk, according to which any scientific statement or hypothesis and theory based on the common scientific method,is subject to possible shortcomings that are sometimes so detrimental that it is essential to prevent them and repair the process of hypothesis or scientific theorizing. Therefore, due to the possibility of errors in non-perceptual consequences, non-perceptual factors, including moral, social, and political values, should be involved in the process of science and these factors determine what assumptions or theories are accepted to avoid those consequences. For the first, Hempel presents the argument as below: Based on certain evidence as well as the scientific rules governing the research question, the probable results are: The hypothesis is accepted according to scientific rules and is, in fact, true. The hypothesis is rejected on the basis of scientific rules and is, in fact, false. The hypothesis is accepted according to scientific rules, but it should, in fact, be false. The hypothesis is rejected onthe basis of scientific rules, but it should, in fact, be true. The first two hypotheses are the results of scientific processes, but the last two hypotheses are probabilities that induction will occur.So both epistemologically and practically, we may have unpleasant consequences that must be remedied by reconstructing the rules of accepting or rejecting scientific assumptions.Hempel’s solution is to involve values in the process of science, so that, although values lack a logical connection with hypotheses, their role in the rules of accepting hypotheses to avoid scientific errors and scientific consequences is justified. The argument is expressed today in a new form as follows: It is a common method in induction science. There is a possibility of error in induction. Scientific error leads to unfortunate individual and social consequences in the practical field. The possible consequences of this can be overcome with unscientific values. The hypothesis must be organized in such a way that it results in the least error. After the alternative assumptions, a case should be selected that has the least adverse consequences. So values can affect the process of science in a permissible and reasonable way. Some of the most important drawbacks of this argument are: Interference of two scientific and practical fields: In this argument, the position of practice has been used for the field of science and the criterion of applying theory and hypothesis has been included in its epistemic justification level. Lack of guarantee of objectivity of theories: If the criterion of objectivity is determined outside the position of opinion, there will be no guarantee that the theories will reveal reality. Basically, the meaning of objectivity is that it should not rely on any personal desires or uses. (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-...

Is it possible to redress a wrong specifically in one’s capacity as a knower? Epistemic justice has largely been conceived of as either an ideal goal guiding present and future societal endeavours, or a set of ameliorative character virtues. Yet there is also a backward-looking component of epistemic justice, which has so far been neglected. I argue that exercises of our cognitive and epistemic capacities can constitute moral redress for wrong actions and wrongful harms for which we are responsible. Epistemic (...) redress can take non-doxastic forms, but can also involve the formation of new beliefs. Acts of epistemic redress can redress not only epistemic but also non-epistemic wrongs. In the practice of natural science, epistemic redress can play legitimate and necessary roles both within and outside the core procedures of scientific reasoning, without compromising science’s truth-orientated epistemic credentials. When it plays these roles, it can contribute to generating restitutive knowledge. (shrink)