Why does performing certain tasks cause the aversive experience of mental effort and concomitant deterioration in task performance? One explanation posits a physical resource that is depleted over time. We propose an alternative explanation that centers on mental representations of the costs and benefits associated with task performance. Specifically, certain computational mechanisms, especially those associated with executive function, can be deployed for only a limited number of simultaneous tasks at any given moment. Consequently, the deployment of these computational mechanisms carries (...) an opportunity cost – that is, the next-best use to which these systems might be put. We argue that the phenomenology of effort can be understood as the felt output of these cost/benefit computations. In turn, the subjective experience of effort motivates reduced deployment of these computational mechanisms in the service of the present task. These opportunity cost representations, then, together with other cost/benefit calculations, determine effort expended and, everything else equal, result in performance reductions. In making our case for this position, we review alternative explanations for both the phenomenology of effort associated with these tasks and for performance reductions over time. Likewise, we review the broad range of relevant empirical results from across sub-disciplines, especially psychology and neuroscience. We hope that our proposal will help to build links among the diverse fields that have been addressing similar questions from different perspectives, and we emphasize ways in which alternative models might be empirically distinguished. (shrink)

Why does performing certain tasks cause the aversive experience of mental effort and concomitant deterioration in task performance? One explanation posits a physical resource that is depleted over time. We propose an alternative explanation that centers on mental representations of the costs and benefits associated with task performance. Specifically, certain computational mechanisms, especially those associated with executive function, can be deployed for only a limited number of simultaneous tasks at any given moment. Consequently, the deployment of these computational mechanisms carries (...) an opportunity cost – that is, the next-best use to which these systems might be put. We argue that the phenomenology of effort can be understood as the felt output of these cost/benefit computations. In turn, the subjective experience of effort motivates reduced deployment of these computational mechanisms in the service of the present task. These opportunity cost representations, then, together with other cost/benefit calculations, determine effort expended and, everything else equal, result in performance reductions. In making our case for this position, we review alternative explanations for both the phenomenology of effort associated with these tasks and for performance reductions over time. Likewise, we review the broad range of relevant empirical results from across sub-disciplines, especially psychology and neuroscience. We hope that our proposal will help to build links among the diverse fields that have been addressing similar questions from different perspectives, and we emphasize ways in which alternative models might be empirically distinguished. (shrink)

For all its popularity as a psychological construct, willpower is irremediably polysemous. A more helpful construct is self-control, defined as the self-regulation of conflicting impulses. We show how the process model of self-control provides a principled framework for examining how undesirable impulses may be weakened and desirable impulses may be strengthened.

Science is the study of our world, as it is in its messy reality. Nonetheless, science requires idealization to function—if we are to attempt to understand the world, we have to find ways to reduce its complexity. Idealization and the Aims of Science shows just how crucial idealization is to science and why it matters. Beginning with the acknowledgment of our status as limited human agents trying to make sense of an exceedingly complex world, Angela Potochnik moves on to (...) explain how science aims to depict and make use of causal patterns—a project that makes essential use of idealization. She offers case studies from a number of branches of science to demonstrate the ubiquity of idealization, shows how causal patterns are used to develop scientific explanations, and describes how the necessarily imperfect connection between science and truth leads to researchers’ values influencing their findings. The resulting book is a tour de force, a synthesis of the study of idealization that also offers countless new insights and avenues for future exploration. (shrink)

Als Charles Darwin im Jahr 1859 seine Theorie einer Evolution der Arten durch natürliche Auslese veröffentlichte, sah er bereits eine grosse Debatte voraus, jedoch nicht deren Ausstrahlungskraft und Langlebigkeit. Zu Beginn standen die Folgen für die Wissenschaften, den Glauben an Gott und die Moralvorstellungen im Vordergrund. Bald kamen Überlegungen über Gesellschaft, Politik, internationale Beziehungen und über Eingriffe bis hinunter auf die Ebene des Individuums und seines Erbmaterials, seiner Gene hinzu. Sozialdarwinismus, Eugenik, Rassismus galten zeitweise als wissenschaftlich legitime Diskussions- und Politikfelder. (...) Befürchtungen vor einem vermeintlichen Niedergang lassen sich bis heute angesichts der Biologisierung des Denkens scheinbar wissenschaftlich-objektiv untermauern. Gegenwärtig sind die Kontroversen noch vielfältiger, beziehen weit mehr Menschen ein als im späten 19. Jahrhundert, haben weit gravierendere Auswirkungen. Die aus elf Ländern stammenden Autorinnen und Autoren zeichnen aus unterschiedlichen disziplinären Perspektiven die Facetten einer spannenden und bis in die Gegenwart hochaktuellen Debatte nach und fragen nach der Zukunft des "Streitfalls Evolution". (shrink)

Using data collected at two phases, this study examines why and how ethical leadership behavior influences employees’ evaluations of organization-focused justice, i.e., procedural justice and distributive justice. By proposing ethical leaders as moral agents of the organization, we build up the linkage between ethical leadership behavior and the above two types of organization-focused justice. We further suggest trust in organization as a key mediating mechanism in the linkage. Our findings indicate that ethical leadership behavior engenders employees’ trust in their employing (...) organization, which in turn promotes their justice perceptions toward the organization. The theoretical and practical implications of these findings are discussed, and some directions for future research are suggested. (shrink)

A number of philosophers have recently argued that we should interpret the debate over moral responsibility as a debate over the conditions under which it would be “fair” to blame a person for her attitudes or conduct. What is distinctive about these accounts is that they begin with the stance of the moral judge, rather than that of the agent who is judged, and make attributions of responsibility dependent upon whether it would be fair or appropriate for a moral judge (...) to react to the agent in various (negative) ways. This is problematic, I argue, because our intuitions about whether and when it would be fair to react negatively to another are sensitive to a host of considerations that appear to have little or nothing to do with an agent’s responsibility or culpability for her attitudes or behavior. If this is correct, then theories which make attributions of responsibility dependent upon the appropriateness of our reactions as moral judges will turn out to be fundamentally misguided. (shrink)

ABSTRACTIt has recently become fashionable among those who write on questions of moral responsibility to distinguish two different concepts, or senses, of moral responsibility via the labels ‘responsibility as attributability’ and ‘responsibility as accountability’. Gary Watson was perhaps the first to introduce this distinction in his influential 1996 article ‘Two Faces of Responsibility’ , but it has since been taken up by many other philosophers. My aim in this study is to raise some questions and doubts about this distinction and (...) to argue that it has led to confusion rather than clarification in debates over moral responsibility. In place of the attributability/accountability distinction, I propose that there is a single concept of moral responsibility underlying our actual moral practices. This core notion of moral responsibility, which I call ‘responsibility as answerability’, is well positioned to explain thos.. (shrink)

Recently, a number of philosophers have begun to question the commonly held view that choice or voluntary control is a precondition of moral responsibility. According to these philosophers, what really matters in determining a person’s responsibility for some thing is whether that thing can be seen as indicative or expressive of her judgments, values, or normative commitments. Such accounts might therefore be understood as updated versions of what Susan Wolf has called “real self views,” insofar as they attempt to ground (...) an agent’s responsibility for her actions and attitudes in the fact (when it is a fact) that they express who she is as a moral agent. As such, they seem to be open to some of the same objections Wolf originally raised to such accounts, and in particular to the objection that they cannot license the sorts of robust moral assessments involved in our current practices of moral responsibility. My aim in this paper is to try to respond to this challenge, by clarifying the kind of robust moral assessments I take to be licensed by (at least some) non-volitional accounts of responsibility and by explaining why these assessments do not in general require the agent to have voluntary control over everything for which she is held responsible. I also argue that the limited applicability of the distinction between “bad agents” and “blameworthy agents” on these accounts is in fact a mark in their favor. (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)

The concept of hierarchical organization is commonplace in science. Subatomic particles compose atoms, which compose molecules; cells compose tissues, which compose organs, which compose organisms; etc. Hierarchical organization is particularly prominent in ecology, a field of research explicitly arranged around levels of ecological organization. The concept of levels of organization is also central to a variety of debates in philosophy of science. Yet many difficulties plague the concept of discrete hierarchical levels. In this paper, we show how these difficulties undermine (...) various implications ascribed to hierarchical organization, and we suggest the concept of scale as a promising alternative to levels. Investigating causal processes at different scales offers a way to retain a notion of quasi-levels that avoids the difficulties inherent in the classic concept of hierarchical levels of organization. Throughout, our focus is on ecology, but the results generalize to other invocations of hierarchy in science and philosophy of science. (shrink)

The predominant view is that a study using health data is observational research and should require individual consent unless it can be shown that gaining consent is impractical. But recent arguments have been made that citizens have an ethical obligation to share their health information for research purposes. In our view, this obligation is sufficient ground to expand the circumstances where secondary use research with identifiable health information is permitted without explicit subject consent. As such, for some studies the Institutional (...) Review Board/Research Ethics Committee review process should not assess the practicality of gaining consent for data use. Instead the review process should focus on assessing the public good of the research, public engagement and transparency. (shrink)

The purpose of this article is to show that animal rights are not necessarily at odds with the use of animals for research. If animals hold basic moral rights similar to those of humans, then we should consequently extend the ethical requirements guiding research with humans to research with animals. The article spells out how this can be done in practice by applying the seven requirements for ethical research with humans proposed by Ezekiel Emanuel, David Wendler and Christine Grady to (...) animal research. These requirements are i) social value, ii) scientific validity, iii) independent review, iv) fair subject selection, v) favorable risk-benefit ratio, vi) informed consent, and vii) respect for research subjects. In practice, this means that we must reform the practice of animal research to make it more similar to research with humans, rather than completely abolish the former. Indeed, if we banned animal research altogether, then we would also deprive animals of its potential benefits – which would be ethically problematic. (shrink)

In this paper, I first outline the view developed in my recent book on the role of idealization in scientific understanding. I discuss how this view leads to the recognition of a number of kinds of variability among scientific representations, including variability introduced by the many different aims of scientific projects. I then argue that the role of idealization in securing understanding distances understanding from truth, but that this understanding nonetheless gives rise to scientific knowledge. This discussion will clarify how (...) my view relates to three other recent books on understanding by Henk de Regt, Catherine Elgin, and Kareem Khalifa. (shrink)

Despite the recent proliferation of scientific, clinical, and narrative accounts of auditory verbal hallucinations, the phenomenology of voice hearing remains opaque and undertheorized. In this article, we outline an interdisciplinary approach to understanding hallucinatory experiences which seeks to demonstrate the value of the humanities and social sciences to advancing knowledge in clinical research and practice. We argue that an interdisciplinary approach to the phenomenology of AVH utilizes rigorous and context-appropriate methodologies to analyze a wider range of first-person accounts of AVH (...) at 3 contextual levels: cultural, social, and historical; experiential; and biographical. We go on to show that there are significant potential benefits for voice hearers, clinicians, and researchers. These include informing the development and refinement of subtypes of hallucinations within and across diagnostic categories; “front-loading” research in cognitive neuroscience; and suggesting new possibilities for therapeutic intervention. In conclusion, we argue that an interdisciplinary approach to the phenomenology of AVH can nourish the ethical core of scientific enquiry by challenging its interpretive paradigms, and offer voice hearers richer, potentially more empowering ways to make sense of their experiences. (shrink)

Causal accounts of scientific explanation are currently broadly accepted (though not universally so). My first task in this paper is to show that, even for a causal approach to explanation, significant features of explanatory practice are not determined by settling how causal facts bear on the phenomenon to be explained. I then develop a broadly causal approach to explanation that accounts for the additional features that I argue an explanation should have. This approach to explanation makes sense of several aspects (...) of actual explanatory practice, including the widespread use of equilibrium explanations, the formulation of distinct explanations for a single event, and the tight relationship between explanations of events and explanations of causal regularities. (shrink)

A common argument against explanatory reductionism is that higher‐level explanations are sometimes or always preferable because they are more general than reductive explanations. Here I challenge two basic assumptions that are needed for that argument to succeed. It cannot be assumed that higher‐level explanations are more general than their lower‐level alternatives or that higher‐level explanations are general in the right way to be explanatory. I suggest a novel form of pluralism regarding levels of explanation, according to which explanations at different (...) levels are preferable in different circumstances because they offer different types of generality, which are appropriate in different circumstances of explanation. (shrink)

Debate about cognitive science explanations has been formulated in terms of identifying the proper level(s) of explanation. Views range from reductionist, favoring only neuroscience explanations, to mechanist, favoring the integration of multiple levels, to pluralist, favoring the preservation of even the most general, high-level explanations, such as those provided by embodied or dynamical approaches. In this paper, we challenge this framing. We suggest that these are not different levels of explanation at all but, rather, different styles of explanation that capture (...) different, cross-cutting patterns in cognitive phenomena. Which pattern is explanatory depends on both the cognitive phenomenon under investigation and the research interests occasioning the explanation. This reframing changes how we should answer the basic questions of which cognitive science approaches explain and how these explanations relate to one another. On this view, we should expect different approaches to offer independent explanations in terms of their different focal patterns and the value of those explanations to partly derive from the broad patterns they feature. (shrink)

The value of optimality modeling has long been a source of contention amongst population biologists. Here I present a view of the optimality approach as at once playing a crucial explanatory role and yet also depending on external sources of confirmation. Optimality models are not alone in facing this tension between their explanatory value and their dependence on other approaches; I suspect that the scenario is quite common in science. This investigation of the optimality approach thus serves as a case (...) study, on the basis of which I suggest that there is a widely felt tension in science between explanatory independence and broad epistemic interdependence, and that this tension influences scientific methodology. (shrink)

Scientific explanations must bear the proper relationship to the world: they must depict what, out in the world, is responsible for the explanandum. But explanations must also bear the proper relationship to their audience: they must be able to create human understanding. With few exceptions, philosophical accounts of explanation either ignore entirely the relationship between explanations and their audience or else demote this consideration to an ancillary role. In contrast, I argue that considering an explanation’s communicative role is crucial to (...) any satisfactory account of explanation. (shrink)

There is an apparent tension in our everyday moral responsibility practices. On the one hand, it is commonly assumed that moral responsibility requires voluntary control: an agent can be morally responsible only for those things that fall within the scope of her voluntary control. On the other hand, we regularly praise and blame individuals for mental states and conditions that appear to fall outside the scope of their voluntary control, such as desires, emotions, beliefs, and other attitudes. In order to (...) resolve this apparent tension, many philosophers appeal to a tracing principle to argue that agents are morally responsible for those attitudes whose existence can be traced back, causally, to a voluntary action or omission in the past. My aim in this article is to critically evaluate this tracing strategy and to argue that it gives us a misguided picture of when and why we are morally responsible for our attitudes. I argue that we should accept a ‘judgment sensitivity’ condition of moral responsibility rather than a ‘voluntary control’ condition, and defend this account against various objections. (shrink)

The optimality approach to modeling natural selection has been criticized by many biologists and philosophers of biology. For instance, Lewontin (1979) argues that the optimality approach is a shortcut that will be replaced by models incorporating genetic information, if and when such models become available. In contrast, I think that optimality models have a permanent role in evolutionary study. I base my argument for this claim on what I think it takes to best explain an event. In certain contexts, optimality (...) and game-theoretic models best explain some central types of evolutionary phenomena. ‡Thanks to Michael Friedman, Helen Longino, Michael Weisberg, and especially Elliott Sober for comments on earlier drafts of this paper. †To contact the author, please write to: Department of Philosophy, Stanford University, Stanford, CA 94305-2155; e-mail: [email protected]. (shrink)

Philosophers traditionally recognize two main features of mental states: intentionality and phenomenal consciousness. To a first approximation, intentionality is the aboutness of mental states, and phenomenal consciousness is the felt, experiential, qualitative, or "what it's like" aspect of mental states. In the past few decades, these features have been widely assumed to be distinct and independent. But several philosophers have recently challenged this assumption, arguing that intentionality and consciousness are importantly related. This article overviews the key views on the relationship (...) between consciousness and intentionality and describes our favored view, which is a version of the phenomenal intentionality theory, roughly the view that the most fundamental kind of intentionality arises from phenomenal consciousness. (shrink)

Levels of organization and their use in science have received increased philosophical attention of late, including challenges to the well-foundedness or widespread usefulness of levels concepts. One kind of response to these challenges has been to advocate a more precise and specific levels concept that is coherent and useful. Another kind of response has been to argue that the levels concept should be taken as a heuristic, to embrace its ambiguity and the possibility of exceptions as acceptable consequences of its (...) usefulness. In this chapter, I suggest that each of these strategies faces its own attendant downsides, and that pursuit of both strategies (by different thinkers) compounds the difficulties. That both kinds of approaches are advocated is, I think, illustrative of the problems plaguing the concept of levels of organization. I end by suggesting that the invocation of levels may mislead scientific and philosophical investigations more than it informs them, so our use of the levels concept should be updated accordingly. (shrink)

The fate of optimality modeling is typically linked to that of adaptationism: the two are thought to stand or fall together (Gould and Lewontin, Proc Relig Soc Lond 205:581–598, 1979; Orzack and Sober, Am Nat 143(3):361–380, 1994). I argue here that this is mistaken. The debate over adaptationism has tended to focus on one particular use of optimality models, which I refer to here as their strong use. The strong use of an optimality model involves the claim that selection is (...) the only important influence on the evolutionary outcome in question and is thus linked to adaptationism. However, biologists seldom intend this strong use of optimality models. One common alternative that I term the weak use simply involves the claim that an optimality model accurately represents the role of selection in bringing about the outcome. This and other weaker uses of optimality models insulate the optimality approach from criticisms of adaptationism, and they account for the prominence of optimality modeling (broadly construed) in population biology. The centrality of these uses of optimality models ensures a continuing role for the optimality approach, regardless of the fate of adaptationism. (shrink)

Given the sensitive nature of trauma-focused research, it is important that researchers understand the impact of research participation on study participants. The current study examined the relationship between type of child abuse, psychological adjustment, and self-reported participatory distress in 105 female adult survivors of childhood abuse. Several key findings emerged: (a) overall, participants reported low levels of participatory distress; (b) greater levels of participatory distress were reported by sexual abuse survivors and were associated with higher scores on depressed mood and (...) posttraumatic stress; and (c) posttraumatic stress symptomatology served as a mediator in the relationship between abuse type and participatory distress. The findings inform researchers and members of Institutional Review Boards on variables related to participatory distress in studies of child abuse. (shrink)

In recent years, philosophy of science has witnessed a significant increase in attention directed toward the field’s social relevance. This is demonstrated by the formation of societies with related agendas, the organization of research symposia, and an uptick in work on topics of immediate public interest. The collection of papers that follows results from one such event: a 3-day colloquium on the subject of socially engaged philosophy of science (SEPOS) held at the University of Cincinnati in October 2012. In this (...) introduction, we first survey the recent history of philosophy of science’s social involvement (or lack thereof) and contrast this with the much greater social involvement of the sciences themselves. Next, we argue that the field of philosophy of science bears a special responsibility to contribute to public welfare. We then introduce as a term of art “SEPOS” and articulate what we take to be distinctive about social engagement, with reference to the articles in this collection as exemplars. Finally, we survey the current state of social engagement in philosophy of science and suggest some practical steps for individuals and institutions to support this trajectory. (shrink)

One of biology's fundamental aims is to generate understanding of the living world around—and within—us. In this chapter, I aim to provide a relatively nonpartisan discussion of the nature of explanation in biology, grounded in widely shared philosophical views about scientific explanation. But this discussion also reflects what I think is important for philosophers and biologists alike to appreciate about successful scientific explanations, so some points will be controversial, at least among philosophers. I make three main points: (1) causal relationships (...) and broad patterns have often been granted importance to scientific explanations, and they are in fact both important; (2) some explanations in biology cite the components of or processes in systems that account for the systems’ features, whereas other explanations feature large-scale or structural causes that influence a system; and (3) there can be multiple different explanations of a given biological phenomenon, explanations that respond to different research aims and can thus be compatible with one another even when they may seem to disagree. (shrink)

International research, sponsored by for-profit companies, is regularly criticised as unethical on the grounds that it exploits research subjects in developing countries. Many commentators agree that exploitation occurs when the benefits of cooperative activity are unfairly distributed between the parties. To determine whether international research is exploitative we therefore need an account of fair distribution. Procedural accounts of fair bargaining have been popular solutions to this problem, but I argue that they are insufficient to protect against exploitation. I argue instead (...) that a maximin principle of fair distribution provides a more compelling normative account of fairness in relationships characterised by extreme vulnerability and inequality of bargaining potential between the parties. A global tax on international research would provide a mechanism for implementing the maximin account of fair benefits. This model has the capacity to ensure fair benefits and thereby prevent exploitation in international research. (shrink)

An historically important conception of the unity of science is explanatory reductionism, according to which the unity of science is achieved by explaining all laws of science in terms of their connection to microphysical law. There is, however, a separate tradition that advocates the unity of science. According to that tradition, the unity of science consists of the coordination of diverse fields of science, none of which is taken to have privileged epistemic status. This alternate conception has roots in Otto (...) Neurath’s notion of unified science. In this paper, I develop a version of the coordination approach to unity that is inspired by Neurath’s views. The resulting conception of the unity of science achieves aims similar to those of explanatory reductionism, but does so in a radically different way. As a result, it is immune to the criticisms facing explanatory reductionism. This conception of unity is also importantly different from the view that science is disunified, and I conclude by demonstrating how it accords better with scientific practice than do conceptions of the disunity of science. (shrink)

Public-private partnerships are established to specifically harness the potential of Big Data in healthcare and can include partners working across the data chain—producing health data, analysing data, using research results or creating value from data. This domain paper will illustrate the challenges that arise when partners from the public and private sector collaborate to share, analyse and use biomedical Big Data. We discuss three specific challenges for PPPs: working within the social licence, public antipathy to the commercialisation of public sector (...) health data, and questions of ownership, both of the data and any resulting intellectual property or products. As a specific example we consider the case of the UK National Health Service providing patient data to Google’s DeepMind AI program to develop a diagnostic app for kidney disease. This article is an application of the framework presented in this issue of ABR. Please refer to that article for more information on how this framework is to be used, including a full explanation of the key values involved and the balancing approach used in the case study at the end. We use four specific values to help analysis these issues: public benefit, stewardship, transparency and engagement. We demonstrate how the Deliberative Framework can support ethical governance of PPPs involving biomedical big data. (shrink)

Making data broadly accessible is essential to creating a medical information commons. Transparency about data-sharing practices can cultivate trust among prospective and existing MIC participants. We present an analysis of 34 initiatives sharing DNA-derived data based on public information. We describe data-sharing practices captured, including practices related to consent, privacy and security, data access, oversight, and participant engagement. Our results reveal that data-sharing initiatives have some distance to go in achieving transparency.

In pursuit of the dream that patients' exercise of autonomy could extend beyond their span of competence, living wills have passed from controversy to conventional wisdom, to widely promoted policy. But the policy has not produced results, and should be abandoned.

This paper contends that a research ethics approach to the regulation of health data research is unhelpful in the era of population‐level research and big data because it results in a primary focus on consent (meta‐, broad, dynamic and/or specific consent). Two recent guidelines – the 2016 WMA Declaration of Taipei on ethical considerations regarding health databases and biobanks and the revised CIOMS International ethical guidelines for health‐related research involving humans – both focus on the growing reliance on health data (...) for research. But as research ethics documents, they remain (to varying degrees) focused on consent and individual control of data use. Many current and future uses of health data make individual consent impractical, if not impossible. Many of the risks of secondary data use apply to communities and stakeholders rather than individual data subjects. Shifting from a research ethics perspective to a public health lens brings a different set of issues into view: how are the benefits and burdens of data use distributed, how can data research empower communities, who has legitimate decision‐making capacity? I propose that a public health ethics framework – based on public benefit, proportionality, equity, trust and accountability – provides more appropriate tools for assessing the ethical uses of health data. The main advantage of a public health approach for data research is that it is more likely to foster debate about power, justice and equity and to highlight the complexity of deciding when data use is in the public interest. (shrink)

The concept of ‘ownership’ is increasingly central to debates, in the media, health policy and bioethics, about the appropriate management of clinical data. I argue that the language of ownership acts as a metaphor and reflects multiple concerns about current data use and the disenfranchisement of citizens and collectives in the existing data ecosystem. But exactly which core interests and concerns ownership claims allude to remains opaque. Too often, we jump straight from ‘ownership’ to ‘private property’ and conclude ‘the data (...) belongs to the patient’. I will argue here that private property is only one type of relevant relationship between people, communities and data. There are several reasons to doubt that conceptualising data as private property presents a compelling response to concerns about clinical data ownership. In particular I argue that clinical data are co-constructed, so a property account would fail to confer exclusive rights to the patient. A non-property account of ownership acknowledges that the data are ‘about the patient’, and therefore the patient has relevant interests, without jumping to the conclusion that the data ‘belongs to the patient’. On this broader account of ownership, the relevant harm is the severing of the connection between the patient and their data, and the solution is to re-engage and re-connect patients to the data research enterprise. (shrink)

The tremendous philosophical focus on how to characterize explanatory metaphysical dependence has eclipsed a number of other unresolved issued about scientific explanation. The purpose of this paper is taxonomical. I will outline a number of other questions about the nature of explanation and its role in science—eight, to be precise—and argue that each is independent. All of these topics have received some philosophical attention, but none nearly so much as it deserves. Furthermore, existing views on these topics have been obscured (...) by not distinguishing among these independent questions and, especially, by not separating them from the question of what metaphysical dependence relation is explanatory. Philosophical analysis of scientific explanation would be much improved by attending more carefully to these, and probably still other, elements of an account of explanation. (shrink)