This paper aims to map the different theoretical options related to the Precautionary Principle (PP). Great part of the literature on it can be systematized by answering to three different questions: is there a basic structure in the PP? If so, in which interpretation of the PP does this structure express itself? Finally, are its damage or knowledge conditions fixed or adjustable? The first question separates realist from non-realist approaches. The second question allows us to discriminate monist, dualist, or pluralist (...) positions in relation to the three interpretations of the PP: decision rule, procedural requirement, or epistemic rule. Finally, the third question distinguishes rigid from non-rigid formulations of the principle. Based on this mapping, one can not only navigate through the different formulations of the PP present both in official documents and in specialized literature, but also deflect some of its common objections, and understand Hans Jonas’ eventual connection with PP. Notwithstanding, this mapping does not capture other important themes attached to PP, which motivates a final distinction between narrow and broader forms of PP. (shrink)

Misconduct in science is often viewed and analyzed through the lenses of normative ethics and moral philosophy. However, notions and methods in the philosophy of science could also provide rather penetrative explanatory insights into the nature and causes of scientific misconduct. A brief illustration in this regard, using as examples the widely popular Popperian falsification and the Kuhnian scientific paradigm, is provided. In multiple areas of scientific research, failure to seek falsification in a Popperian manner constitutes a questionable research practice (...) and could lead to “falsification” in the context of research misconduct. On the other hand, scientific misconduct is often facilitated by its perpetrators using the familiarity, expectations and confines of a Kuhnian paradigm to blend in fabricated data/results. A rudimentary application of these philosophical notions could be useful in our understanding of the nature and cause of research misconduct, and facilitate mitigation of the latter through educational means. (shrink)

Two goals - improving replicability and accountability of Machine Learning research respectively, have accrued much attention from the AI ethics and the Machine Learning community. Despite sharing the measures of improving transparency, the two goals are discussed in different registers - replicability registers with scientific reasoning whereas accountability registers with ethical reasoning. Given the existing challenge of the Responsibility Gap - holding Machine Learning scientists accountable for Machine Learning harms due to them being far from sites of application, this paper (...) posits that reconceptualizing replicability can help bridge the gap. Through a shift from model performance replicability to claim replicability, Machine Learning scientists can be held accountable for producing non-replicable claims that are prone to eliciting harm due to misuse and misinterpretation. In this paper, I make the following contributions. First, I define and distinguish two forms of replicability for ML research that can aid constructive conversations around replicability. Second, I formulate an argument for claim-replicability's advantage over model performance replicability in justifying assigning accountability to Machine Learning scientists for producing non-replicable claims and show how it enacts a sense of responsibility that is actionable. In addition, I characterize the implementation of claim replicability as more of a social project than a technical one by discussing its competing epistemological principles, practical implications on Circulating Reference, Interpretative Labor, and research communication. (shrink)

This study takes off from the ethical problem that racism grounded in population genetics raises. It is an analysis of four standard scientific responses to the problem of genetically motivated racism, seen in connection with the Human Genome Diversity Project (HGDP): (1) Discriminatory uses of scientific facts and arguments are in principle ‘misuses’ of scientific data that the researcher cannot be further responsible for. (2) In a strict scientific sense, genomic facts ‘disclaim racism’, which means that an epistemically correct grasp (...) of genomics should be ethically justified. (3) Ethical difficulties are issues to be ‘resolved’ by an ethics institution or committee, which will guarantee the ethical quality of the research scrutinized. (4) Although population genetics occasionally may lead to racism, its overall ‘value’ for humankind justifies its cause as a desirable pursuit. I argue that these typical responses to genetically motivated racism supervene on a principle called the ‘ethic of knowledge’, which implies that an epistemically correct account has intrinsic ethical value. This principle, and its logically related ideas concerning the ethic of science, effectively avoids a deeper ethical question of responsibility in science from being raised. (shrink)

These preprints were automatically compiled into a PDF from the collection of papers deposited in PhilSci-Archive in conjunction with the PSA 2018.

This paper reviews current debates in social epistemology about the relations ‎between ‎knowledge ‎and consensus. These relations are philosophically interesting on their ‎own, but ‎also have ‎practical consequences, as consensus takes an increasingly significant ‎role in ‎informing public ‎decision making. The paper addresses the following questions. ‎When is a ‎consensus attributable to an epistemic community? Under what conditions may ‎we ‎legitimately infer that a consensual view is knowledge-based or otherwise ‎epistemically ‎justified? Should consensus be the aim of scientific inquiry, and (...) if so, what ‎kind of ‎consensus? How should dissent be handled? It is argued that a legitimate inference ‎that a ‎theory is correct from the fact that there is a scientific consensus on it requires taking ‎into ‎consideration both cognitive properties of the theory as well as social properties of ‎the ‎consensus. The last section of the paper reviews computational models of ‎consensus ‎formation.‎. (shrink)

Policymakers who seek to make scientifically informed decisions are constantly confronted by scientific uncertainty and expert disagreement. This thesis asks: how can policymakers rationally respond to expert disagreement and scientific uncertainty? This is a work of non-ideal theory, which applies formal philosophical tools developed by ideal theorists to more realistic cases of policymaking under scientific uncertainty. I start with Bayesian approaches to expert testimony and the problem of expert disagreement, arguing that two popular approaches— supra-Bayesianism and the standard model of (...) expert deference—are insufficient. I develop a novel model of expert deference and show how it can deal with many of these problems raised for them. I then turn to opinion pooling, a popular method for dealing with disagreement. I show that various theoretical motivations for pooling functions are irrelevant to realistic policymaking cases. This leads to a cautious recommendation of linear pooling. However, I then show that any pooling method relies on value judgements, that are hidden in the selection of the scoring rule. My focus then narrows to a more specific case of scientific uncertainty: multiple models of the same system. I introduce a particular case study involving hurricane models developed to support insurance decision-making. I recapitulate my analysis of opinion pooling in the context of model ensembles, confirming that my hesitations apply. This motivates a shift of perspective, to viewing the problem as a decision theoretic one. I rework a recently developed ambiguity theory, called the confidence approach, to take input from model ensembles. I show how it facilitates the resolution of the policymaker’s problem in a way that avoids the issues encountered in previous chapters. This concludes my main study of the problem of expert disagreement. In the final chapter, I turn to methodological reflection. I argue that philosophers who employ the mathematical methods of the prior chapters are modelling. Employing results from the philosophy of scientific models, I develop the theory of normative modelling. I argue that it has important methodological conclusions for the practice of formal epistemology, ruling out popular moves such as searching for counterexamples. (shrink)

Scientists often diverge widely when choosing between research programs. This can seem to be rooted in disagreements about which of several theories, competing to address shared questions or phenomena, is currently the most epistemically or explanatorily valuable—i.e. most successful. But many such cases are actually more directly rooted in differing judgments of pursuit-worthiness, concerning which theory will be best down the line, or which addresses the most significant data or questions. Using case studies from 16th-century astronomy and 20th-century geology and (...) biology, I argue that divergent theory choice is thus often driven by considerations of scientific process, even where direct epistemic or explanatory evaluation of its final products appears more relevant. Broadly following Kuhn’s analysis of theoretical virtues, I suggest that widely shared criteria for pursuit-worthiness function as imprecise, mutually-conflicting values. However, even Kuhn and others sensitive to pragmatic dimensions of theory ‘acceptance’, including the virtue of fruitfulness, still commonly understate the role of pursuit-worthiness—especially by exaggerating the impact of more present-oriented virtues, or failing to stress how ‘competing’ theories excel at addressing different questions or data. This framework clarifies the nature of the choice and competition involved in theory choice, and the role of alternative theoretical virtues. (shrink)

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

Algorithms wield increasing control over our lives—over which jobs we get, whether we're granted loans, what information we're exposed to online, and so on. Algorithms can, and often do, wield their power in a biased way, and much work has been devoted to algorithmic bias. In contrast, algorithmic neutrality has gone largely neglected. I investigate three questions about algorithmic neutrality: What is it? Is it possible? And when we have it in mind, what can we learn about algorithmic bias?

Examining previous discussions on how to construe the concepts of gender and race, we advocate what we call strategic conceptual engineering. This is the employment of a (possibly novel) concept for specific epistemic or social aims, concomitant with the openness to use a different concept (e.g., of race) for other purposes. We illustrate this approach by sketching three distinct concepts of gender and arguing that all of them are needed, as they answer to different social aims. The first concept serves (...) the aim of identifying and explaining gender-based discrimination. It is similar to Haslanger’s well-known account, except that rather than offering a definition of ‘woman’ we focus on ‘gender’ as one among several axes of discrimination. The second concept of gender is to assign legal rights and social recognitions, and thus is to be trans-inclusive. We argue that this cannot be achieved by previously suggested concepts that include substantial gender-related psychological features, such as awareness of social expectations. Instead, our concept counts someone as being of a certain gender solely based on the person’s self-identification with this gender. The third concept of gender serves the aim of personal empowerment by means of one’s gender identity. In this context, substantial psychological features and awareness of one’s social situation are involved. While previous accounts of concepts have focused on their role in determining extensions, we point to contexts where a concept’s role in explanation and moral reasoning can be more important. (shrink)

Animal welfare has a long history of disregard. While in recent decades the study of animal welfare has become a scientific discipline of its own, the difficulty of measuring animal welfare can still be vastly underestimated. There are three primary theories, or perspectives, on animal welfare - biological functioning, natural living and affective state. These come with their own diverse methods of measurement, each providing a limited perspective on an aspect of welfare. This paper describes a perspectival pluralist account of (...) animal welfare, in which all three theoretical perspectives and their multiple measures are necessary to understand this complex phenomenon and provide a full picture of animal welfare. This in turn will offer us a better understanding of perspectivism and pluralism itself. (shrink)

"Analyzes the value of using case-based methodologies to address contemporary social justice issues in philosophy"--.

In the US and UK Births in obstetric units vastly outnumber births that take place outside of an obstetric unit. Still non-obstetric births are increasing in both countries. Is it professionally responsible to support a non-obstetric birth? It is morally responsible to choose to give birth at home? This debate has become heated with those on both sides finding empirical support for their positions. Indeed this moral debate is often carried out in terms of empirical evidence. While to some this (...) debate over the evidence is a distraction from what is genuinely at stake, namely different non-epistemic values, I will argue in this paper that the way forward is to take a closer and more fine grained look at the evidence. This closer look will first require that we distinguish between evidence of risk acceptability and evidence of safety and then focus carefully on evidence of the safety of non-obstetric births compared to obstetric births. (shrink)

This chapter offers a critique of intelligent design arguments against evolution and a philosophical discussion of the nature of science, drawing several lessons for the teaching of evolution and for science education in general. I discuss why Behe’s irreducible complexity argument fails, and why his portrayal of organismal systems as machines is detrimental to biology education and any under-standing of how organismal evolution is possible. The idea that the evolution of complex organismal features is too unlikely to have occurred by (...) random mutation and selection (as recently promoted by Dembski) is very widespread, but it is easy to show students why such small probability arguments are fallacious. While intelligent design proponents have claimed that the exclusion of supernatural causes mandated by scientific methods is dogmatically presupposed by science, scientists have an empirical justification for using such methods. This justification is instructive for my discussion of how to demarcate science from pseudoscience. I argue that there is no universal account of the nature of science, but that the criteria used to judge an intellectual approach vary across historical periods and have to be specific to the scientific domain. Moreover, intellectual approaches have to be construed as practices based on institutional factors and values, and to be evaluated in terms of the activities of their practitioners. Science educators should not just teach scientific facts, but present science as a practice and make students reflect on the nature of science, as this gives them a better appreciation of the ways in which intelligent design falls short of actual science. (shrink)

"Why should we care about having true beliefs? And why do demonstrably false beliefs persist and spread despite consequences for the people who hold them? Philosophers of science Cailin O’Connor and James Weatherall argue that social factors, rather than individual psychology, are what’s essential to understanding the spread and persistence of false belief. It might seem that there’s an obvious reason that true beliefs matter: false beliefs will hurt you. But if that’s right, then why is it irrelevant to many (...) people whether they believe true things or not? In an age riven by "fake news," "alternative facts," and disputes over the validity of everything from climate change to the size of inauguration crowds, the authors argue that social factors, not individual psychology, are what’s essential to understanding the persistence of false belief and that we must know how those social forces work in order to fight misinformation effectively."–Publisher’s description. (shrink)

I argue that scientific and poetic modes of objectivity are perspectival duals: 'views' from and onto basic natural forces, respectively. I ground this analysis in a general account of objectivity, not in terms of either 'universal' or 'inter-subjective' validity, but as receptivity to basic features of reality. Contra traditionalists, bare truth, factual knowledge, and universally valid representation are not inherently valuable. But modern critics who focus primarily on the self-expressive aspect of science are also wrong to claim that our knowledge (...) is or should be ultimately mediated by ourselves. In objective science, we represent nature as a field of phenomena determined by and within explanatorily-basic physical structures that encode the causal impact of elemental physical forces. These causally-basic forces hence ground the possibility of objective scientific theory, even though (I argue) they are systematically excluded from its representational contents. I show how my notions of force and field emerge partly through my effort to naturalize concepts of 'God' and 'Laws' in 17th-century natural philosophy. In science, we use the structure of basic forces' impact to see corresponding objects. We do not see these forces themselves—and this relates to the 'transcendence' of 'God'. I supplement this historical analysis by critiquing standard accounts of objectivity, and by synthesizing elements from neo-Kantian epistemology and current 'structural' realism into a view that I call 'dynamic structuralism'. Finally, I argue that physics systematically relies on passive characterizations of phenomena like inertia and impressed force. Dynamic alternatives that are just as empirically adequate are possible, but they are non-scientific. Poetic objectivity involves a direct presentation of nature as an order of interacting forces. I elaborate first by developing a novel theory of the relation between beauty and sublimity, mediated by a basic category of 'sensory force' (e.g. a 'singing' tone in a beautiful melody). I then describe the interaction between sensory and affective dimensions of aesthetic experience, in relation to an original historical analysis of passion and 'disinterestedness' in Kant, Schiller and Nietzsche. I synthesize these lines of analysis into a critique of the role of 'expression' in art. I also resist 'spectator'-centric aesthetics, in this connection, by developing an account of artistic objectivity in dialogue with Ruskin's critique of the 'pathetic fallacy'. I contrast artistic objectivity with Romantic ideals of self-expression, while elaborating its positive relation to certain currents within Victorian and Modernist aesthetics, including Imagists' stress on 'exteriority'. My project creatively extends Nietzsche's view that philosophical and scientific theories are 'perspectival' expressions of theorists' drives. It is a virtue of Nietzsche's account that he takes the outlet of strong human drives in creative acts of theorizing to be just one among many higher modes of 'will to power' in nature—many of which are totally impersonal. But Nietzsche is still too focused on self-expression or willing one's own power. Objective science involves external forces' 'expression' in and through us, not just 'expressing' our own powers. And Nietzsche's vitalistic 'will to power' must be replaced by a basic ontology that better accommodates inorganic phenomena, like the 'lawful' order of celestial motions. Thus I aim to de-anthropomorphize and 'de-organicize' post-Kantian notions of willful striving and organic development, while preserving for force the primary ontological and evaluative status that theorists from Schiller and Goethe to Schelling and Schlegel to Emerson and Nietzsche attributed to will or to life. (shrink)

This paper presents scientists’ understanding of their roles in society and corresponding responsibilities. It discusses the researchers’ perspective against the background of the contemporary literature on scientific responsibility in the social sciences and philosophy and proposes a heuristic that improves the understanding of the complexity of scientific responsibility. The study is based on qualitative interviews with senior scientists. The presented results show what researchers themselves see as their responsibilities, how they assume them, and what challenges they perceive with respect to (...) their responsibilities. Regarding the latter, the interviewed researchers highlight those aspects of responsibility that go beyond the expertise of their professional role, and thus cannot be carried by scientists alone. For example, scientists alone cannot determine the general direction science takes, or the useful application of their research. The interviewed researchers describe those challenges as responsibilities that must be shared across different societal groups. In the theoretical literature, responsibility has been described as a relation between an actor (who), the action for which someone is responsible (what), and the normative framework against which someone is responsible (why). We will draw on this concept of “relational responsibility” to identify the various actors, normative frameworks, and actions relevant to scientific responsibility. This will serve as a heuristic tool to help identify the entanglement of responsibilities spread across several societal groups. (shrink)

As inductive decision-making procedures, the inferences made by machine learning programs are subject to underdetermination by evidence and bear inductive risk. One strategy for overcoming these challenges is guided by a presumption in philosophy of science that inductive inferences can and should be value-free. Applied to machine learning programs, the strategy assumes that the influence of values is restricted to data and decision outcomes, thereby omitting internal value-laden design choice points. In this paper, I apply arguments from feminist philosophy of (...) science to machine learning programs to make the case that the resources required to respond to these inductive challenges render critical aspects of their design constitutively value-laden. I demonstrate these points specifically in the case of recidivism algorithms, arguing that contemporary debates concerning fairness in criminal justice risk-assessment programs are best understood as iterations of traditional arguments from inductive risk and demarcation, and thereby establish the value-laden nature of automated decision-making programs. Finally, in light of these points, I address opportunities for relocating the value-free ideal in machine learning and the limitations that accompany them. (shrink)

In this chapter, the focus is on robotics development and its ethical implications, especially on some particular applications or interaction principles. In recent years, such developments have happened very quickly, based on the advances achieved in the last few decades in industrial robotics. The technological developments in manufacturing, with the implementation of Industry 4.0 strategies in most industrialized countries, and the dissemination of production strategies into services and health sectors, enabled robotics to develop in a variety of new directions. Policy (...) making and ethical awareness addressed these issues using socio-economic knowledge and also in an effort to solve some of the application problems raised in a range of different circumstances and sectoral environments. (shrink)

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

Innovative modes of collaboration between archaeologists and Indigenous communities are taking shape in a great many contexts, in the process transforming conventional research practice. While critics object that these partnerships cannot but compromise the objectivity of archaeological science, many of the archaeologists involved argue that their research is substantially enriched by them. I counter objections raised by internal critics and crystalized in philosophical terms by Boghossian, disentangling several different kinds of pluralism evident in these projects and offering an analysis of (...) why they are epistemically productive when they succeed. My central thesis is that they illustrate the virtues of epistemic inclusion central to proceduralist accounts of objectivity, but I draw on the resources of feminist standpoint theory to motivate the extension of these social -cognitive norms beyond the confines of the scientific community. (shrink)

Recently, some philosophers of science (e.g., Gürol Irzik, Michael Friedman) have challenged the ‘received view’ on the relationship between Rudolf Carnap and Thomas Kuhn, suggesting that there is a close affinity (rather than opposition) between their philosophical views. In support of this argument, these authors cite Carnap and Kuhn’s similar views on incommensurability, theory-choice, and scientific revolutions. Against this revisionist view, I argue that the philosophical relationship between Carnap and Kuhn should be regarded as opposed rather than complementary. In particular, (...) I argue that a consideration of the fundamentally disparate nature of the broader philosophical projects of Carnap (logic of science) and Kuhn (providing a theory of scientific revolutions)renders the alleged similarities between their views superficial in comparison to their fundamental differences. In defense of the received view, I suggest that Carnap and Kuhn are model representatives of two contrasting styles of doing philosophy of science, viz., logical analysis and historical analysis respectively. This analysis clarifies the role played by Kuhn’s Structure of Scientific Revolutions in the demise of logical empiricism in the second half of the twentieth-century. (shrink)

Drug regulation is fraught with inductive risk. Regulators must make a prediction about whether or not an experimental pharmaceutical will be effective and relatively safe when used by typical patients, and such predictions are based on a complex, indeterminate, and incomplete evidential basis. Such inductive risk has important practical consequences. If regulators reject an experimental drug when it in fact has a favourable benefit/harm profile, then a valuable intervention is denied to the public and a company’s material interests are needlessly (...) thwarted. Conversely, if regulators approve an experimental drug when it in fact has an unfavourable benefit/harm profile, then resources are wasted, people are needlessly harmed, and other potentially more effective treatments are underutilized. Given that such regulatory decisions have these practical consequences, non-epistemic values about the relative importance of these consequences impact the way such regulatory decisions are made (similar to the analysis of laboratory studies on the toxic effects of dioxins presented in Douglas [2000]). To balance the competing demands of the pertinent non-epistemic values, regulators must perform what I call an “inductive risk calculus.” At least in the American context this inductive risk calculus is not well-managed. (shrink)

‘Sentience’ sometimes refers to the capacity for any type of subjective experience, and sometimes to the capacity to have subjective experiences with a positive or negative valence, such as pain or pleasure. We review recent controversies regarding sentience in fish and invertebrates and consider the deep methodological challenge posed by these cases. We then present two ways of responding to the challenge. In a policy-making context, precautionary thinking can help us treat animals appropriately despite continuing uncertainty about their sentience. In (...) a scientific context, we can draw inspiration from the science of human consciousness to disentangle conscious and unconscious perception (especially vision) in animals. Developing better ways to disentangle conscious and unconscious affect is a key priority for future research. (shrink)

The democratization of science entails the public having greater influence over science and that influence being shared more equally among members of the public. This chapter will present a thumbnail sketch of the arguments for the democratization of science based on the importance of collectively shaping science’s impact on society, the instrumental benefits of public participation in science, and the need to ensure that the use of science in politics does not undermine collective self-government. It will then outline worries about (...) citizen competence, the abuse of democratic ideals and the limits posed by the nation-state. (shrink)

In evaluating science, philosophers tends to focus on general laws and on their truth. I urge a shift in focus to the reliability of the panoply of outputs science produces and in tandem, from the general to the particular. Here I give five arguments to support this, including many, many scientific outputs, which must be supposed reliable if we are to warrant our general principles, aren’t truth-apt; and reliability invites the crucial question, ‘Reliable for what?’ Getting clear the particular purpose (...) is essential for effective action and just evaluation. (shrink)

Claims that science may become 'self-fulfilling' through its impact on objects of study have recently risen to prominence. Despite radical statements about the supposed consequences of such accounts, however, the central notion of scientific self-fulfillment has remained obscure, leading to skewed views of its actual prevalence and significance. -/- Self-Fulfilling Science illuminates this underexplored phenomenon, drawing on insights from philosophy of science to address questions of its conceptualization, prevalence, and significance. The book critically engages with the popular notion that economic (...) theories of homo economicus exhibit self-fulfillment, and explores its relevance to various metaphysical, ethical, and epistemic issues. Extreme claims of fundamental incompatibility with our usual notions of scientific success are ill-founded. Instead, self-fulfillment’s true epistemic significance lies in more local, nuanced philosophical issues such as theory evaluation and the thesis of underdetermination. -/- In presenting a novel framework, this book facilitates deeper engagement with the developing field of self-fulfilling science and is of interest to philosophers of science, social scientists, and social constructionists. (shrink)

Jonathan Y. Tsou examines and defends positions on central issues in philosophy of psychiatry. The positions defended assume a naturalistic and realist perspective and are framed against skeptical perspectives on biological psychiatry. Issues addressed include the reality of mental disorders; mechanistic and disease explanations of abnormal behavior; definitions of mental disorder; natural and artificial kinds in psychiatry; biological essentialism and the projectability of psychiatric categories; looping effects and the stability of mental disorders; psychiatric classification; and the validity of the DSM's (...) diagnostic categories. The main argument defended by Tsou is that genuine mental disorders are biological kinds with harmful effects. This argument opposes the dogma that mental disorders are necessarily diseases that result from biological dysfunction. Tsou contends that the broader ideal of biological kinds offers a more promising and empirically ascertainable naturalistic standard for assessing the reality of mental disorders and the validity of psychiatric categories. (shrink)

This book addresses key conceptual issues relating to the modern scientific and engineering use of computer simulations. It analyses a broad set of questions, from the nature of computer simulations to their epistemological power, including the many scientific, social and ethics implications of using computer simulations. The book is written in an easily accessible narrative, one that weaves together philosophical questions and scientific technicalities. It will thus appeal equally to all academic scientists, engineers, and researchers in industry interested in questions (...) related to the general practice of computer simulations. (shrink)

In this paper, I distinguish three general approaches to public trust in science, which I call the individual approach, the semi-social approach, and the social approach, and critically examine their proposed solutions to what I call the problem of harmful distrust. I argue that, despite their differences, the individual and the semi-social approaches see the solution to the problem of harmful distrust as consisting primarily in trying to persuade individual citizens to trust science and that both approaches face two general (...) problems, which I call the problem of overidealizing science and the problem of overburdening citizens. I then argue that in order to avoid these problems we need to embrace a (thoroughly) social approach to public trust in science, which emphasizes the social dimensions of the reception, transmission, and uptake of scientific knowledge in society and the ways in which social forces influence both positively and negatively the trustworthiness of science. (shrink)

Quantitative researchers often discuss research ethics as if specific ethical problems can be reduced to abstract normative logics (e.g., virtue ethics, utilitarianism, deontology). Such approaches overlook how values are embedded in every aspect of quantitative methods, including ‘observations,’ ‘facts,’ and notions of ‘objectivity.’ We describe how quantitative research practices, concepts, discourses, and their objects/subjects of study have always been value-laden, from the invention of statistics and probability in the 1600s to their subsequent adoption as a logic made to appear as (...) if it exists prior to, and separate from, ethics and values. This logic, which was embraced in the Academy of Management from the 1960s, casts management researchers as ethical agents who ought to know about a reality conceptualized as naturally existing in the image of statistics and probability (replete with ‘constructs’), while overlooking that S&P logic and practices, which researchers made for themselves, have an appreciable role in making the world appear this way. We introduce a different way to conceptualize reality and ethics, wherein the process of scientific inquiry itself requires an examination of its own practices and commitments. Instead of resorting to decontextualized notions of ‘rigor’ and its ‘best practices,’ quantitative researchers can adopt more purposeful ways to reason about the ethics and relevance of their methods and their science. We end by considering implications for addressing ‘post truth’ and ‘alternative facts’ problems as collective concerns, wherein it is actually the pluralistic nature of description that makes defending a collectively valuable version of reality so important and urgent. (shrink)

Theories of scientific rationality typically pertain to belief. In this paper, the author argues that we should expand our focus to include motivations as well as belief. An economic model is used to evaluate whether science is best served by scientists motivated only by truth, only by credit, or by both truth and credit. In many, but not all, situations, scientists motivated by both truth and credit should be judged as the most rational scientists.

In recent years, the EU legislation on genetically modified crops has come under severe criticism. Among the arguments are that the present legislation is inconsistent, disproportionate, obsolete from a scientific point of view, and vague in terms of its scope. In this paper, the EU GM legislation is analysed based on five proposed criteria: legal certainty, non-discrimination, proportionality, scientific adaptability, and inclusion of non-safety considerations. It is argued that the European regulatory framework does not at present satisfy the criteria of (...) legal certainty, non-discrimination, and scientific adaptability. Two ways of reforming the present legislation toward greater accommodation of the values expressed through the proposed criteria are briefly introduced and discussed. (shrink)

Qualitative researchers sometimes talk about objectivity in relation to qualitative data sets. In this paper, I defend a reconstructed notion of objective qualitative data sets that may serve as a useful and reachable guiding ideal in qualitative data generation. In the first part of the paper, I develop the ideal. According to it, a qualitative data set is objective to the extent that it, in conjunction with true assumptions, possesses a combination of good-making features in virtue of which the data (...) set is suited to serve as evidence base for a satisfying answer to the research question under study. In the second part of the paper, I examine and reject two possible lines of objection to this ideal: One is that it picks out the wrong good-making features. The other is that the very focus on good-making features is misguided: the objectivity of a qualitative data set should instead be seen as a matter of how it was generated or evaluated. (shrink)

Case Study research is characterized by the employment of multiple data gathering methods. In this paper, I examine the concurrent use of participant observation and qualitative interviews. The question I examine is: what is the rationale behind their combination in case study research? In the literature on case study research, the two most common reasons for using multiple methods appeal to comprehensiveness and convergent confirmation respectively. I argue that there is a third significant, yet overlooked, way to motivate the joint (...) use of participant observation and qualitative interviews: the methods may generate complementary evidence and this puts the researcher in a better position to confirm that her data manifest central epistemic values and so are suitable as basis for providing an adequate answer to her research question. I refer to this as the rationale of blended epistemic value validation. (shrink)

Philosophy of science has traditionally focused on the epistemological dimensions of scientific practice at the expense of the ethical and political questions scientists encounter when addressing questions of policy in advisory contexts. In this article, I will explore how an exclusive focus on epistemology and theoretical reason can function to reinforce common, yet flawed assumptions concerning the role of scientific knowledge in policy decision making when reproduced in philosophy courses for science students. In order to address this concern, I will (...) argue that such courses should supplement the traditional focus on theoretical reason with an analysis of the practical reasoning employed by scientists in advisory contexts. Later sections of this paper outline a teaching strategy by which this can be achieved that consists of two steps: the first examines idealized examples of scientific advising in order to highlight the irreducible role played by moral reasoning in justifying policy recommendations. The second employs argument analysis to reveal implicit moral assumptions in actual advisory reports that form the basis for class discussion. This paper concludes by examining some of the wider benefits that can be expected from adopting such an approach. (shrink)

AbsractIn this paper, we contribute to a growing literature in the philosophy of social science cautioning social scientists against context-independent claims to objectivity, by analyzing the recent proposal of a new Basic Index of Gender Inequality by Gijsbert Stoet and David Geary. Despite the many internal problems with BIGI, Stoet and Geary have had some success in positioning the index as an important corrective to the way in which gender inequality is measured in mainstream metrics like the Global Gender Gap (...) Index. We argue that this success is facilitated at least in part by the failure of GGGI’s proponents to adequately justify the methodological choices underpinning the index in relation to the context in which the index’s findings are intended to be used. In so doing, the authors of GGGI oversell the objectivity of the metric’s assessment of the state of global gender inequality—and it is this overselling that allows Stoet and Geary to present BIGI as a metric that corrects what they claim are systematic biases within GGGI. The case of BIGI and GGGI, we argue, suggests that the kind of epistemic modesty exhibited by recent operational approaches to objectivity is particularly important for social research on highly politically contested topics. (shrink)

This paper discusses how to deal with research that threatens to cause harm to society—in particular, whether and in what cases bans and moratoria are appropriate. First, it asks what normative resources philosophy of science may draw on to answer such questions. In an effort to presuppose only resources acknowledgeable across different comprehensive worldviews, it is claimed that the aim of credibility provides a good basis for normative reflection. A close analysis reveals an inner tension inherent in the pursuit of (...) credibility, referred to as the paradox of credibility: Although the aim of credibility involves the goal of being trusted, the immediate pursuit of the goal of being trusted as much as possible can run counter to and undermine the pursuit of credibility. From this inner tension, considerations are derived on what it means to uncompromisingly strive for trustworthiness. When applied to the problem of harmful research, it becomes apparent that it is important to distinguish between different types of cases. Some cases allow science to prevent harm while relinquishing credibility in the associated research area. In contrast, other cases demand preserving subject-specific scientific credibility in order to manage potential harm. (shrink)

This paper advocates for making epistemic interests a central object of philosophical analysis in epistemology and philosophy of science. It is argued that the importance of epistemic interests derives from their fundamental importance for the notion of objectivity. Epistemic interests are defined as individuated by a set of objectives, each of which represents a dimension of the search for truth. Among these dimensions, specificity, sensitivity, and productivity are discussed in detail. It is argued that the relevance of productivity is often (...) overlooked in debates about the ends and means of science. A definition of the objectivity of inquiry is proposed that takes the notion of epistemic interest as its starting point. (shrink)

In light of the growth in the conduct of international clinical research in developing populations, this paper seeks to explore what is owed to developing world communities who host international clinical research. Although existing paradigms for assigning and assessing benefits to host communities offer valuable insight, I criticize their failure to distinguish between those benefits which can justify the conduct of research in a developing world setting and those which cannot. I argue that the justification for human subjects research is (...) fundamentally grounded in the social value of knowledge, and that this value is context-dependent in a manner which should inform our ethical evaluation of the conduct of research in specific settings. I propose a new framework for the assessment of research benefits assigned to developing world host communities, a natural implication of which is to limit the types of research projects which may permissibly be conducted in developing world settings. (shrink)

In this paper I argue that philosophers of science have an obligation to recognize and engage with the social nature of the sciences they assess if those sciences are morally relevant. Morally-relevant science is science that has the potential to risk harm to humans, non-humans, or the environment. My argument and the approach I develop are informed by an analysis of the philosophy of biology literature on the criticism of evolutionary psychology, the study of the evolution of human psychology and (...) behaviour. From this literature, I tease out two different methods of scientific critique. The first I call the “truth-detectional” approach. Those who take this approach are first and foremost concerned about the truth of EP claims as that truth can be determined by evidence. The second I call the “social-dimensional” approach. Those who take this approach talk about the production and truth of EP claims but within a social framework. On this account, the legitimacy and perceived legitimacy of EP claims are not separate from the institutional and social processes and values that lend to their production. I show that the truth-detectional approach risks harms to society and to the philosophy of science, but that the social-dimensional approach avoids these harms. Philosophers of science, therefore, should take a social-dimensional approach to the assessment of morally-relevant science. (shrink)

In their recent book, Oreskes and Conway describe the ‘tobacco strategy’, which was used by the tobacco industry to influence policymakers regarding the health risks of tobacco products. The strategy involved two parts, consisting of promoting and sharing independent research supporting the industry’s preferred position and funding additional research, but selectively publishing the results. We introduce a model of the tobacco strategy, and use it to argue that both prongs of the strategy can be extremely effective—even when policymakers rationally update (...) on all evidence available to them. As we elaborate, this model helps illustrate the conditions under which the tobacco strategy is particularly successful. In addition, we show how journalists engaged in ‘fair’ reporting can inadvertently mimic the effects of industry on public belief. 1Introduction2Epistemic Network Models3Selective Sharing4Biased Production5Journalists as Unwitting Propagandists6ConclusionAppendix. (shrink)

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

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