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)

Tracking technology has been heralded as transformative for animal ecology. In this paper I examine what changes are taking place, showing how current animal movement research is a field ripe for philosophical investigation. I focus first on how the devices alter the limitations and biases of traditional field observation, making observation of animal movement and behaviour possible in more detail, for more varied species, and under a broader variety of conditions, as well as restricting the influence of human presence and (...) observer bias. I reconstruct these as shifts in scope, objectivity, accuracy and fruitfulness. The second transformation is slightly less obvious but equally significant for animal ecology. Tracking devices generate complex data that demands both statistical and biological expertise, which has led to increasingly frequent and intensive collaborations between statisticians and biologists. Based on interviews, I examine how researchers in these interdisciplinary collaborations negotiate the collection, analysis and interpretation of movement data, integrating research interests, methodological constraints, previous field observations, and background theory. Tracking technology is therefore also shifting which disciplinary considerations are brought to bear on research into animal movement and behaviour and how this research is conducted. (shrink)

The anti-psychiatry movement of the 20th century has notably denounced the role of values and social norms in the shaping of psychiatric categories. Recent activist movements also recognize that psychiatry is value-laden, however, they do not fight for a value-free psychiatry. On the contrary, some activist movements of the 21st century advocate for self-advocacy in sciences of mental health in order to reach a more accurate understanding of psychiatric categories/mental distress. By aiming at such epistemic gain, they depart from the (...) anti-psychiatry movement. Through the analysis of the epistemic and political influence of two of these movements – Neurodiversity and the Mad Studies, we show how this new activism has taken a scientific turn compatible with current philosophical scientific frameworks, while still developing a critical approach on psychiatry. (shrink)

Large-scale language technologies are increasingly used in various forms of communication with humans across different contexts. One particular use case for these technologies is conversational agents, which output natural language text in response to prompts and queries. This mode of engagement raises a number of social and ethical questions. For example, what does it mean to align conversational agents with human norms or values? Which norms or values should they be aligned with? And how can this be accomplished? In this (...) paper, we propose a number of steps that help answer these questions. We start by developing a philosophical analysis of the building blocks of linguistic communication between conversational agents and human interlocutors. We then use this analysis to identify and formulate ideal norms of conversation that can govern successful linguistic communication between humans and conversational agents. Furthermore, we explore how these norms can be used to align conversational agents with human values across a range of different discursive domains. We conclude by discussing the practical implications of our proposal for the design of conversational agents that are aligned with these norms and values. (shrink)

It is an open question whether well-being ought to primarily be understood as a temporal concept or whether it only makes sense to talk about a person’s well-being over their whole lifetime. In this article, I argue that how this principled philosophical disagreement is settled does not have substantive practical implications for well-being science and well-being policy. Trying to measure lifetime well-being directly is extremely challenging as well as unhelpful for guiding well-being public policy, while temporal well-being is both an (...) adequate indirect measure of lifetime well-being, and an adequate focus for the purposes of improving well-being through public policy. Consequently, even if what we ought to care about is lifetime well-being, we should use temporal measures of well-being and focus on temporal well-being policies. (shrink)

We analyse the issue of using prior information in frequentist statistical inference. For that purpose, we scrutinise different kinds of sampling designs in Jerzy Neyman’s theory to reveal a variety of ways to explicitly and objectively engage with prior information. Further, we turn to the debate on sampling paradigms (design-based vs. model-based approaches) to argue that Neyman’s theory supports an argument for the intermediate approach in the frequentism vs. Bayesianism debate. We also demonstrate that Neyman’s theory, by allowing non-epistemic values (...) to influence evidence collection and formulation of statistical conclusions, does not compromise the epistemic reliability of the procedures and may improve it. This undermines the value-free ideal of scientific inference. (shrink)

Social scientists, political scientists and philosophers debate key concepts such as democracy, power and autonomy. Contested concepts like these pose questions: Are terms such as “democracy” hopelessly ambiguous? How can two theorists defend alternative accounts of democracy without talking past each other? How can we understand debates in which theorists disagree about what democracy is? This paper first discusses the popular strategy to answer these questions by appealing to Rawls’s distinction between concepts and conceptions. According to this approach, defenders of (...) rival conceptions of, e.g. justice can disagree without talking past each other because they share the concept of justice. It is argued that this idea is attractive but limited in application and that it fails to do justice to the dynamic and normative aspects of concept formation. Reflective equilibrium is then suggested as an alternative approach. It replaces the static contrast between a conceptual ‘core’ and competing conceptions by a dynamic perspective of concept formation as a partly normative undertaking: pre-theoretic language use and commitments can provide a shared starting point for developing alternative accounts which yield different concepts of, e.g. justice. This perspective provides a new understanding of how it is possible that different theorists defend rival accounts of, e.g. justice, without talking past each other. (shrink)

Non-epistemic values play important roles in classificatory practice, such that philosophical accounts of kinds and classification should be able to accommodate them. Available accounts fail to do so, however. Our aim is to fill this lacuna by showing how non-epistemic values feature in scientific classification, and how they can be incorporated into a philosophical theory of classification and kinds. To achieve this, we present a novel account of kinds and classification, discuss examples from biological classification where non-epistemic values play decisive (...) roles, and show how this account accommodates the role of non-epistemic values. (shrink)

There is now a general consensus amongst philosophers in the values in science literature that values necessarily play a role in core areas of scientific inquiry. We argue that attention should now be turned from debating the value-free ideal to delineating legitimate from illegitimate influences of values in science, a project we dub “The New Demarcation Problem.” First, we review past attempts to demarcate the uses of values and propose a categorization of the strategies by where they seek to draw (...) legitimacy from. Next, we propose a set of desiderata for what we take to be a satisfactory solution and present a case study where conflicting sets of values clearly impinge on science, but where the legitimacy of their influence is ambiguous. We use these desiderata and the case study to illustrate what we take to be the strengths and weaknesses of current strategies. To be clear, our goal is not to answer the question we pose, but to articulate a framework within which a solution can be judged. (shrink)

Criticism is a staple of the scientific enterprise and of the social epistemology of science. Philosophical discussions of criticism have traditionally focused on its roles in relation to objectivity, confirmation, and theory choice. However, attention to criticism and to criticizability should also inform our thinking about scientific pursuits: the allocation of resources with the aim of developing scientific tools and ideas. In this paper, we offer an account of scientific pursuitworthiness which takes criticizability as its starting point. We call this (...) the apokritic model of pursuit. Its core ideas are that pursuits are practices governed by norms for asking and answering questions, and that criticism arises from the breach of these norms. We illustrate and advertise our approach using examples from institutional grant review, neuroscience, and sociology. We show that the apokritic model can unify several indices of criticizability, that it can account for the importance of criticizing pursuits in scientific practice, and that it can offer ameliorative advice to erstwhile pursuers. (shrink)

This dissertation explores the influence of time constraints on different research practices. The first two parts present case studies, which serve as a basis for discussing the epistemological and ethical implications of temporal limitations in scientific research. Part I is a case study on gravitational wave research, conducted by the LIGO Scientific Collaboration. This exemplifies fundamental research – without immediate societal applications, open-ended in terms of timeline and in terms of research goals. It is based, in part, on qualitative interviews (...) conducted with gravitational wave physicists. I show that considerations about time and speed play a role in every stage of research: goal setting, method design, and the evaluation and communication of results. Part II provides a case study on translational medicine, an approach explicitly dedicated to accelerating research in order to develop and implement new therapies. This epitomizes applied research with high social stakes, motivated by non-epistemic goals. Here, epistemic trade-offs between speed and reliability intersect with ethical trade-offs between different types of harms. In Part III, the insights from both of these case studies are used as the basis for a more general discussion concerning the pragmatic aspects of epistemic practices, especially in relation to current debates centered on the role of values in science. A particular focus is on the value of speed and the ability to generate reliable results, either via choice of methods, or via decisions about which goals to set, as well as decisions about when to stop further testing. The primary thesis of the dissertation is that pragmatic considerations stemming from limitations of resources are a necessary feature of the pursuit of epistemic aims, and that the epistemic is thus inherently pragmatic. (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)

I want to combine two hitherto largely independent research projects, scientific understanding and mechanistic explanations. Understanding is not only achieved by answering why-questions, that is, by providing scientific explanations, but also by answering what-questions, that is, by providing what I call scientific descriptions. Based on this distinction, I develop three forms of understanding: understanding-what, understanding-why, and understanding-how. I argue that understanding-how is a particularly deep form of understanding, because it is based on mechanistic explanations, which answer why something happens in (...) virtue of what it is made of. I apply the three forms of understanding to two case studies: first, to the historical development of thermodynamics and, second, to the differences between the Clausius and the Boltzmann entropy in explaining thermodynamic processes. (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)

We critically engage two traditional views of scientific data and outline a novel philosophical view that we call the pragmatic-representational view of data. On the PR view, data are representations that are the product of a process of inquiry, and they should be evaluated in terms of their adequacy or fitness for particular purposes. Some important implications of the PR view for data assessment, related to misrepresentation, context-sensitivity, and complementary use, are highlighted. The PR view provides insight into the common (...) but little-discussed practices of iteratively reusing and repurposing data, which result in many datasets’ having a phylogeny—an origin and complex evolutionary history—that is relevant to their evaluation and future use. We relate these insights to the open-data and data-rescue movements, and highlight several future avenues of research that build on the PR view of data. (shrink)

Scientific progress has many facets and can be conceptualized in different ways, for example in terms of problem-solving, of truthlikeness or of growth of knowledge. The main claim of the paper is that the most important prerequisite of scientific progress is the institutionalization of competition and criticism. An institutional framework appropriately channeling competition and criticism is the crucial factor determining the direction and rate of scientific progress, independently on how one might wish to conceptualize scientific progress itself. The main intention (...) is to narrow the divide between traditional philosophy of science and the sociological, economic and political outlook at science that emphasizes the private interests motivating scientists and the subsequent contingent nature of the enterprise. The aim is to show that although science is a social enterprise taking place in historical time and thus is of a contingent nature, it can and in fact does lead to genuine scientific progress - contrary to the claims of certain sociologists of science and other relativists who standardly stress its social nature, but deny its progressive character. I will first deal with the factual issue by way of introducing the main concepts and mechanisms of modern institutional theory and by applying them to the analysis of the cultural phenomenon that we call modern science. I will then turn to the normative issue: what is the appropriate content of the institutional framework, for scientific progress to emerge and be sustained at which level should it be set and by whom? Addressing this problematic is equivalent to conducting a constitutional debate leading to a Constitution of Science. (shrink)

This paper articulates and defends three interconnected claims: first, that the debate on the role of values for science misses a crucial dimension, the institutional one; second, that institutions occupy the intermediate level between scientific activities and values and that they are to be systematically integrated into the analysis; third, that the appraisal of the institutions of science with respect to values should be undertaken within the premises of a comparative approach rather than an ideal approach. Hence, I defend the (...) view that the issue be framed in reference to the following question: "What kind of institutional rules should be in place in order for the scientific process to unfold in such a way that the values that we deem more important come to the fore?" Addressing this concern is equivalent to conducting a debate on institutions and their role for science. (shrink)

What does Cyberpunk and AI Ethics have to do with each other? Cyberpunk is a sub-genre of science fiction that explores the post-human relationships between human experience and technology. One similarity between AI Ethics and Cyberpunk literature is that both seek a dialogue in which the reader may inquire about the future and the ethical and social problems that our technological advance may bring upon society. In recent years, an increasing number of ethical matters involving AI have been pointed and (...) debated, and several ethical principles and guides have been suggested as governance policies for the tech industry. However, would this be the role of AI Ethics? To serve as a soft and ambiguous version of the law? I would like to promote in this article a more Cyberpunk way of doing AI Ethics, whit a more anarchic way of governance. In this study, I will seek to expose some of the deficits of the underlying power structures of our society, and suggest that AI governance be subject to public opinion, so that ‘good AI’ can become ‘good AI for all’. (shrink)

This paper explores the important role of critical science, and in particular of post-colonial and decolonial theories, in understanding and shaping the ongoing advances in artificial intelligence. Artificial intelligence is viewed as amongst the technological advances that will reshape modern societies and their relations. While the design and deployment of systems that continually adapt holds the promise of far-reaching positive change, they simultaneously pose significant risks, especially to already vulnerable peoples. Values and power are central to this discussion. Decolonial theories (...) use historical hindsight to explain patterns of power that shape our intellectual, political, economic, and social world. By embedding a decolonial critical approach within its technical practice, AI communities can develop foresight and tactics that can better align research and technology development with established ethical principles, centring vulnerable peoples who continue to bear the brunt of negative impacts of innovation and scientific progress. We highlight problematic applications that are instances of coloniality, and using a decolonial lens, submit three tactics that can form a decolonial field of artificial intelligence: creating a critical technical practice of AI, seeking reverse tutelage and reverse pedagogies, and the renewal of affective and political communities. The years ahead will usher in a wave of new scientific breakthroughs and technologies driven by AI research, making it incumbent upon AI communities to strengthen the social contract through ethical foresight and the multiplicity of intellectual perspectives available to us, ultimately supporting future technologies that enable greater well-being, with the goal of beneficence and justice for all. (shrink)

According to an adequacy-for-purpose view, models should be assessed with respect to their adequacy or fitness for particular purposes. Such a view has been advocated by scientists and philosophers...

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)

Sustainability science seeks to extend scientific investigation into domains characterized by a distinct problem-solving agenda, physical and social complexity, and complex moral and ethical landscapes. In this endeavor it arguably pushes scientific investigation beyond its usual comfort zones, raising fundamental issues about how best to structure such investigation. Philosophers of science have long scrutinized the structure of science and scientific practices, and the conditions under which they operate effectively. We propose a critical engagement between sustainability scientists and philosophers of science (...) with respect to how to engage in scientific activity in these complex domains. We identify specific issues philosophers of science raise concerning current sustainability science and the contributions philosophers can make to resolving them. In conclusion we reflect on the steps philosophers of science could take to advance sustainability science. (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...

Experimental design is one aspect of a scientific method. A well-designed, properly conducted experiment aims to control variables in order to isolate and manipulate causal effects and thereby maximize internal validity, support causal inferences, and guarantee reliable results. Traditionally employed in the natural sciences, experimental design has become an important part of research in the social and behavioral sciences. Experimental methods are also endorsed as the most reliable guides to policy effectiveness. Through a discussion of some of the central concepts (...) associated with experimental design, including controlled variation and randomization, this chapter will provide a summary of key ethical issues that tend to arise in experimental contexts. In addition, by exploring assumptions about the nature of causation and by analyzing features of causal relationships, systems, and inferences in social contexts, this chapter will summarize the ways in which experimental design can undermine the integrity of not only social and behavioral research but policies implemented on the basis of such research. (shrink)

After raising some minor philosophical points about Kevin Elliott’s A Tapestry of Values (2017), I argue that we should expand on the themes raised in the book and that philosophers of science need to pay as much attention to the loom of science (i.e., the institutional structures which guide the pursuit of science) as the tapestry of science. The loom of science includes such institutional aspects as patents, funding sources, and evaluation regimes that shape how science gets pursued, and that (...) attending to these aspects will enable us to provide more robust guidance on the values that infuse the tapestry of science. (shrink)

This response addresses the excellent responses to my book provided by Heather Douglas, Janet Kourany, and Matt Brown. First, I provide some comments and clarifications concerning a few of the highlights from their essays. Second, in response to the worries of my critics, I provide more detail than I was able to provide in my book regarding my three conditions for incorporating values in science. Third, I identify some of the most promising avenues for further research that flow out of (...) this interchange. (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)

Proponents of evidence-based policy (EBP) call for public policy to be informed by high-quality evidence from randomized controlled trials. This methodological preference aims to promote several epistemic values, e.g. rigor, unbiasedness, precision, and the ability to obtain causal conclusions. I argue that there is a trade-off between these epistemic values and several non-epistemic, moral and political values. This is because the evidence afforded by preferred EBP methods is differentially useful for pursuing different moral and political values. I expand on how (...) this challenges ideals of value-freedom and -neutrality in EBP, and offer suggestions for how EBP methodology might be revised. (shrink)

Once lively debates concerning the philosophical significance of self-fulfilling science, or the causal contribution of science to bringing about the states of affairs it depicts, lapsed in the 1970s. Recent claims concerning the influence of economic theory on the behavior it predicts or explains seem poised to revitalize discussion, yet lack of clarity abounds concerning the key features of such cases and the philosophical issues to which they might be relevant. In this paper, I examine a paradigmatic case of self-fulfilling (...) science, clarify its key features, and critically discuss two existing approaches to understanding such phenomena. Ultimately, I suggest a novel approach more well-suited to analyzing such cases and exploring their philosophical significance. (shrink)

The aim of this article is to critically build on Justin Biddle and Anna Leuschner’s characterization of epistemologically detrimental dissent in the context of science. We argue that the presence of nonepistemic agendas and severe nonepistemic consequences offers neither necessary nor sufficient conditions for EDD to obtain. We clarify their role by arguing that they are contingent enabling factors, not stable difference-makers, in the production of EDD. We maintain that two stable difference-makers are core to the production of EDD: production (...) of skewed science and effective public dissemination. (shrink)

Empirical adequacy matters directly - as it does for antirealists - if we aim to get all or most of the observable facts right, or indirectly - as it does for realists - as a symptom that the claims we make about the theoretical facts are right. But why should getting the facts - either theoretical or empirical - right be required of an acceptable theory? Here we endorse two other jobs that good theories are expected to do: helping us (...) with a) understanding and b) managing the world. Both are of equal, often greater, importance than getting a swathe of facts right, and empirical adequacy fares badly in both. It is not needed for doing these jobs and in many cases it gets in the way of doing them efficiently. (shrink)

It's not uncommon for scientists to give different explanations of the same phenomenon, but we currently lack clear guidelines for deciding whether to treat such accounts as competitors. This article discusses how science studies can help create tools and guidelines for thinking about whether explanations compete. It also specifies how one family of discourse rules enables there to be differing accounts that appear to compete but don't. One hopes that being more aware of the linguistic mechanisms making compatible accounts appear (...) to compete will prevent people from wasting resources trying to show which account is right. (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)

In this paper, I consider the relationship between Inference to the Best Explanation and Bayesianism, both of which are well-known accounts of the nature of scientific inference. In Sect. 2, I give a brief overview of Bayesianism and IBE. In Sect. 3, I argue that IBE in its most prominently defended forms is difficult to reconcile with Bayesianism because not all of the items that feature on popular lists of “explanatory virtues”—by means of which IBE ranks competing explanations—have confirmational import. (...) Rather, some of the items that feature on these lists are “informational virtues”—properties that do not make a hypothesis \ more probable than some competitor \ given evidence E, but that, roughly-speaking, give that hypothesis greater informative content. In Sect. 4, I consider as a response to my argument a recent version of compatibilism which argues that IBE can provide further normative constraints on the objectively correct probability function. I argue that this response does not succeed, owing to the difficulty of defending with any generality such further normative constraints. Lastly, in Sect. 5, I propose that IBE should be regarded, not as a theory of scientific inference, but rather as a theory of when we ought to “accept” H, where the acceptability of H is fixed by the goals of science and concerns whether H is worthy of commitment as research program. In this way, IBE and Bayesianism, as I will show, can be made compatible, and thus the Bayesian and the proponent of IBE can be friends. (shrink)

Complex environmental problems require well-researched policies that integrate knowledge from both the natural and social sciences. Epistemic differences can impede interdisciplinary collaboration, as shown by debates between conservation biologists and anthropologists who are working to preserve biological diversity and support economic development in central Africa. Disciplinary differences with regard to 1) facts, 2) rigor, 3) causal explanation, and 4) research goals reinforce each other, such that early decisions about how to define concepts or which methods to adopt may tilt research (...) design and data interpretation toward one discipline’s epistemological framework. If one of the contributing fields imposes a solution to an epistemic problem, this sets the stage for what I call disciplinary capture. Avoiding disciplinary capture requires clear communication between collaborators, but beyond this it also requires that collaborators craft research questions and innovate research designs which are different from the inherited epistemological frameworks of contributing disciplines. (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)

In robustness analysis, hypotheses are supported to the extent that a result proves robust, and a result is robust to the extent that we detect it in diverse ways. But what precise sense of diversity is at work here? In this paper, I show that the formal explications of evidential diversity most often appealed to in work on robustness – which all draw in one way or another on probabilistic independence – fail to shed light on the notion of diversity (...) relevant to robustness analysis. I close by briefly outlining a promising alternative approach inspired by Horwich’s (1982) eliminative account of evidential diversity. (shrink)

If we find life on another world, it will be an extremely important discovery and we will have to take great care not to do anything that might endanger that life. If the life we find is sentient we will have moral obligations to that life. Whether it is sentient or not, we have a duty to ourselves to preserve it as a study object, and also because it would be commonly seen as valuable in its own right. In addition (...) to this we would also have a duty to our fellow humans and other earthly life forms not to expose them to danger by advertently or inadvertently exposing them to potentially harmful space organisms. When space exploration turns into exploitation it will therefore be important to be able to show that a world that is up for exploitation is uninhabited before the exploitation starts. Showing that a world is uninhabited is, however, a different kind of task than showing that it is inhabited. The latter task can be accomplished through one positive finding but it is not clear how to go about the former task. In this paper I suggest that it is a gradual process asymptotically approaching certainty rather than a discovery in the traditional sense of the word. It has to be handled in two steps. The first is to connect degree of certainty with research setup. The second is to decide how certain we need to be. The first step is about the number, diversity and quality of observations. The second step is a decision we have to make based on the purpose of the investigation. The purpose and therefore the degree of certainty needed to establish that a world is uninhabited will be different for a world that is up for exploitation than for a world that is not. In the latter case it is only a matter of epistemic values. In the former case also ethical values have to be considered. (shrink)

There is increasing attention to the centrality of idealization in science. One common view is that models and other idealized representations are important to science, but that they fall short in one or more ways. On this view, there must be an intermediary step between idealized representation and the traditional aims of science, including truth, explanation, and prediction. Here I develop an alternative interpretation of the relationship between idealized representation and the aims of science. In my view, continuing, widespread idealization (...) calls into question the idea that science aims for truth. I argue that understanding must replace truth as the ultimate epistemic aim of science. Additionally, science has a wide variety aims, epistemic and non-epistemic, and these aims motivate different kinds of scientific products. Finally, I show how these diverse aims---all rather distant from truth---result in the expanded influence of social values on science. (shrink)

This study addresses the question of normative analysis of the value‐based aspects of nursing. In our perspective, values in science may be distinguished into (i) epistemic when related to the goals of truth and objectivity and (ii) non‐epistemic when related to social, cultural or political aspects. Furthermore, values can be called constitutive when necessary for a scientific enterprise, or contextual when contingently associated with science. Analysis of the roles of the various forms of values and models of knowledge translation provides (...) the ground to understand the specific role of values in nursing. A conceptual framework has been built to classify some of the classical perspectives on nursing knowledge and to examine the relationships between values and different forms of knowledge in nursing. It follows that adopting a normative perspective in the analysis of nursing knowledge provides key elements to identify its proper dimension. (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)

Engineering accident investigations are systematic inquiries into the facts and causes of engineering accidents. The aims of an engineering accident investigation include identifying significant truths about an accident, learning lessons to prevent similar future accidents, and authoritatively communicating the investigative results to the stakeholders. An important normative dimension along which an engineering accident investigation can be evaluated is its degree of success in fulfilling these aims. In this paper, I propose criteria for evaluating the degree of success of an engineering (...) accident investigation using a question-centered framework, and then argue for the relevance of this proposal to the actual engineering practice. The basic idea of my proposal is that an engineering accident investigation is successful to the extent that (1) questions that should arise in the investigation do arise, and (2) questions that arise—especially the more significant ones—are resolved satisfactorily by the end of the investigation. The first part of this paper unpacks my proposal by analyzing the following three concepts and illustrating them using examples from the TWA Flight 800 accident investigation: The (satisfactory) resolution of questions, the significance of questions, and the arising of questions. The second part of this paper argues for the relevance of my proposal to the practitioners and stakeholders of engineering accident investigations. First, I argue that my proposal is sensitive to the aims of the investigators and stakeholders regarding engineering accident investigations, and that it helps them navigate competing and conflicting aims. Second, I go beyond the TWA 800 case study and argue that my proposal explains the strengths and limitations of different types of accident causation models used in investigations. (shrink)

A century ago historian of science George Sarton argued that “science is our greatest treasure, but it needs to be humanized or it will do more harm than good”. The systematic cultivation of an “historical spirit,” a philosophical appreciation of the dynamic nature of scientific inquiry, and a recognition that science is irreducibly a “collective enterprise” was, on Sarton’s account, crucial to the humanizing mission he advocated. These elements of Sarton’s program are more relevant than ever as philosophers of science (...) articulate research programs that take seriously the contextual factors, situated interests, and historical contingencies that shape the sciences we study. I trace the trajectory of a long-term philosophical engagement with archaeology that illustrates a succession of ways in which social, cultural, and political values configure inquiry, culminating in a program of collaborative research that raises the question of what role philosophers can usefully play when the challenges of humanizing scientific practice have centrally to do with navigating entrenched asymmetries of power. (shrink)

ABSTRACT The emerging consensus in the secondary literature on Duhem is that his notion of ‘good sense’ is a virtue of individual scientists that guides them choosie between empirically equal rival theories : 149–159; Ivanova 2010. “Pierre Duhem’s Good Sense as a Guide to Theory Choice.” Studies in History and Philosophy of Science Part A 41 : 58–64; Fairweather 2011. “The Epistemic Value of Good Sense.” Studies in History and Philosophy of Science Part A 43 : 139–146; Bhakthavatsalam. “Duhemian Good (...) Sense and Agent Reliabilism.” Studies in History and Philosophy of Science Part A 64: 22–29). In this paper, I argue that good sense is irrelevant for theory choice within Duhem’s conception of scientific methodology. Theory choice, for Duhem, is either a pseudo-problem or addressed purely by empirical and formal desiderata depending on how it is understood. I go on to provide a positive interpretation of good sense as a feature of scientific communities that undergo particular forms of education that allow scientists to abandon theory pursuit. I conclude by suggesting that this interpretation entails that virtue epistemological readings of Duhem are insufficient for understanding good sense; we must employ a social epistemological perspective. (shrink)