What is consciousness and why is it so philosophically and scientifically puzzling? For many years philosophers approached this question assuming a standard physicalist framework on which consciousness can be explained by contemporary physics, biology, neuroscience, and cognitive science. This book is a debate between two philosophers who are united in their rejection of this kind of "standard" physicalism - but who differ sharply in what lesson to draw from this. Amy Kind defends dualism 2.0, a thoroughly modern version of dualism (...) (the theory that there are two fundamentally different kinds of things in the world: those that are physical and those that are mental) decoupled from any religious or non-scientific connotations. Daniel Stoljar defends non-standard physicalism, a kind of physicalism different from both the standard version and dualism 2.0. The book presents a cutting-edge assessment of the philosophy of consciousness and provides a glimpse at what the future study of this area might bring. (shrink)

The aim of this article is to discuss the relation between indigenous and scientific kinds on the basis of contemporary ethnobiological research. I argue that ethnobiological accounts of taxonomic convergence-divergence patters challenge common philosophical models of the relation between folk concepts and natural kinds. Furthermore, I outline a positive model of taxonomic convergence-divergence patterns that is based on Slater's [2014] notion of “stable property clusters” and Franklin-Hall's [2014] discussion of natural kinds as “categorical bottlenecks.” Finally, I (...) argue that this model is not only helpful for understanding the relation between indigenous and scientific kinds but also makes substantial contributions to contemporary debates about natural kinds.to contemporary debates about natural kinds. (shrink)

Some scientific categories seem to correspond to genuine features of the world and are indispensable for successful science in some domain; in short, they are natural kinds. This book gives a general account of what it is to be a natural kind and puts the account to work illuminating numerous specific examples.

In this chapter, I argue that scientific practice in the neurosciences of cognition is not conducive to the discovery of natural kinds of cognitive capacities. The “neurosciences of cognition” include cognitive neuroscience and cognitive neurobiology, two research areas that aim to understand how the brain gives rise to cognition and behavior. Some philosophers of neuroscience have claimed that explanatory progress in these research areas ultimately will result in the discovery of the underlying mechanisms of cognitive capacities. Once such (...) mechanistic understanding is achieved, cognitive capacities purportedly will be relegated into natural kind categories that correspond to real divisions in the causal structure of the world. I provide reasons here, however, in support of the claim that the neurosciences of cognition currently are not on a trajectory for discovering natural kinds. As I explain, this has to do with how mechanistic explanations of cognitive capacities are developed. Mechanistic explanations and the kinds they explain are abstract representational byproducts of the conceptual, experimental and integrative practices of neuroscientists. If these practices are not coordinated towards developing mechanistic explanations that mirror the causal structure of the world, then natural kinds of cognitive capacities will not be discovered. I provide reasons to think that such coordination is currently lacking in the neurosciences of cognition and indicate where changes in these practices appropriate to the natural kinds ideal would be required if achieving this ideal is indeed the goal. However, I suggest that an evaluation of current practices in these research areas is suggestive that discovering natural kinds of cognitive capacities is not the goal. (shrink)

Discussions over whether these natural kinds exist, what is the nature of their existence, and whether natural kinds are themselves natural kinds aim to not only characterize the kinds of things that exist in the world, but also what can knowledge of these categories provide. Although philosophically critical, much of the past discussions of natural kinds have often answered these questions in a way that is unresponsive to, or has actively avoided, discussions of the empirical (...) use of natural kinds and what I dub “activities of natural kinding” and “natural kinding practices”. The natural kinds of a particular discipline are those entities, events, mechanisms, processes, relationships, and concepts that delimit investigation within it—but we might reasonably ask: How are these natural kinds discovered?, How are they made?, Are they revisable?, and Where do they come from? A turn to natural kinding practices reveals a new set of questions open for investigation: How do natural kinds explain through practice?, What are natural kinding practices and classifications and why should we care?, What is the nature of natural kinds viewed as a set of activities?, and How do practice approaches to natural kinds shape and reconfigure scientific disciplines? Natural kinds have traditionally been discussed in terms of how they classify the contents of the world. The metaphysical project has been one which identifies essences, laws, sameness relations, fundamental properties, and clusters of family resemblances and how these map out the ontological space of the world. But actually how this is done has been less important in the discussion than the resultant categories that are produced. I aim to rectify these omissions and suggest a new metaphysical project investigating kinds in practice. (shrink)

I examine the epistemological debate on scientific realism in the context of quantum physics, focusing on the empirical underdetermin- ation of different formulations and interpretations of QM. I will argue that much of the interpretational, metaphysical work on QM tran- scends the kinds of realist commitments that are well-motivated in the light of the history of science. I sketch a way of demarcating empirically well-confirmed aspects of QM from speculative quantum metaphysics in a way that coheres with anti-realist (...) evidence from the history of science. The minimal realist attitude sketched withholds realist com- mitment to what quantum state |Ψ⟩ represents. I argue that such commitment is not required for fulfilling the ultimate realist motiva- tion: accounting for the empirical success of quantum mechanics in a way that is in tune with a broader understanding of how theoretical science progresses and latches onto reality. (shrink)

In this dissertation, I address the question of how to construct scientific theories of emotions that are both conceptually sound and empirically fruitful. To do this, I offer an analysis of the main challenges scientific theories of emotions face, and I propose a meta-theoretical framework to construct scientific concepts of emotions as explications of folk emotion concepts. Part I discusses the main challenges theories of emotions in psychology and neuroscience encounter. The first states that a proper (...) class='Hi'>scientific theory of emotions must explain all and only the phenomena under the vernacular term ‘emotion’ with a common set of conceptual resources and under an overarching generic concept of emotion. The second demands that each emotion category corresponds to well-coordinated sets of neural, physiological, and behavioral patterns of responses. I argue that none of the best contemporary theories of emotions in psychology and neuroscience overcomes these challenges. As a result, a new theory of emotions is required. In Part II, I develop the meta-theoretical framework to construct a theory of emotions that overcomes the challenges above. First, I propose a pluralistic account of scientific kinds based on different patterns of projection that various disciplines may take to justify inductive inferences. These are essentialist, historical, and social patterns. Each of these patterns provides a framework to construct different types of scientific concepts. I argue that among the frameworks for scientific kinds available, the one that is best suited to explicate emotion concepts is a functional framework. Consequently, I conclude by recommending scientists pursue functionalist theories of emotions over essentialist, historical, or social theories. (shrink)

Many debates in philosophy focus on whether folk or scientific psychological notions pick out cognitive natural kinds. Examples include memory, emotions and concepts. A potentially interesting type of kind is: kinds of mental representations (as opposed, for example, to kinds of psychological faculties). In this chapter we outline a proposal for a theory of representational kinds in cognitive science. We argue that the explanatory role of representational kinds in scientific theories, in conjunction with (...) a mainstream approach to explanation in cognitive science, suggest that representational kinds are multi-level. This is to say that representational kinds’ properties cluster at different levels of explanation and allow for intra- and inter-level projections. (shrink)

Computational systems biologists create and manipulate computational models of biological systems, but they do not always have straightforward epistemic access to the content and behavioural profile of such models because of their length, coding idiosyncrasies, and formal complexity. This creates difficulties both for modellers in their research groups and for their bioscience collaborators who rely on these models. In this paper we introduce a new kind of visualization that was developed to address just this sort of epistemic opacity. The visualization (...) is unusual in that it depicts the dynamics and structure of a computer model instead of that model’s target system, and because it is generated algorithmically. Using considerations from epistemology and aesthetics, we explore how this new kind of visualization increases scientific understanding of the content and function of computer models in systems biology to reduce epistemic opacity. (shrink)

Philosophical treatments of natural kinds are embedded in two distinct projects. I call these the philosophy of science approach and the philosophy of language approach. Each is characterized by its own set of philosophical questions, concerns, and assumptions. The kinds studied in the philosophy of science approach are projectible categories that can ground inductive inferences and scientific explanation. The kinds studied in the philosophy of language approach are the referential objects of a special linguistic category—natural kind (...) terms—thought to refer directly. Philosophers may hope for a unified account addresses both sets of concerns. This paper argues that this cannot be done successfully. No single account can satisfy both the semantic objectives of the philosophy of language approach and the explanatory projects of the philosophy of science approach. After analyzing where the tensions arise, I make recommendations about assumptions and projects that are best abandoned, those that should be retained, and those that should go their separate ways. I also recommend adopting the disambiguating terminology of “scientific kinds” and “natural kinds” for the different notions of kinds developed in these different approaches. (shrink)

Scientists use models to understand the natural world, and it is important not to conflate model and nature. As an illustration, we distinguish three different kinds of populations in studies of ecology and evolution: theoretical, laboratory, and natural populations, exemplified by the work of R.A. Fisher, Thomas Park, and David Lack, respectively. Biologists are rightly concerned with all three types of populations. We examine the interplay between these different kinds of populations, and their pertinent models, in three examples: (...) the notion of “effective” population size, the work of Thomas Park on /Tribolium/ populations, and model-based clustering algorithms such as /Structure/. Finally, we discuss ways to move safely between three distinct population types while avoiding confusing models and reality. (shrink)

We ask whether it is reasonable to delay or refuse to take COVID-19 vaccines that have been shown in clinical trials to be safe and effective against infectious diseases. We consider two kinds of vaccine hesitancy. The first is geared to scientifically informed open questions about vaccines. We argue that in cases where the data is not representative of relevant groups, such as pregnant women and ethnic minorities, hesitancy can be reasonable on epistemic grounds. However, we argue that hesitancy (...) is not reasonable if a vaccine has passed well-conducted clinical trials. The second kind of hesitancy is to do with beliefs about the institutions offering a successfully trialled vaccine and the justifiability of cooperating with those institutions. For example, in the UK, distrust of the UK Government or the National Health Service is identified as a factor in the vaccine hesitancy of minority ethnic populations. We ask whether this sort of hesitation is reasonable given normative requirements of fair co-operation, both with those institutions and the wider population. We suggest that the answer is not straightforward. Sometimes the hesitation is unreasonable but understandable. -/- . (shrink)

Scientists cannot devise theories, construct models, propose explanations, make predictions, or even carry out observations, without first classifying their subject matter. The goal of scientific taxonomy is to come up with classification schemes that conform to nature's own. Another way of putting this is that science aims to devise categories that correspond to 'natural kinds.' The interest in ascertaining the real kinds of things in nature is as old as philosophy itself, but it takes on a different (...) guise when one adopts a naturalist stance in philosophy, that is when one looks closely at scientific practice and takes it as a guide for identifying natural kinds and investigating their general features. This Element surveys existing philosophical accounts of natural kinds, defends a naturalist alternative, and applies it to case studies in a diverse set of sciences. This title is also available as Open Access on Cambridge Core. (shrink)

There are many ways of construing the claim that some categories are more “natural" than others. One can ask whether a system of categories is innate or acquired by learning, whether it pertains to a natural phenomenon or to a social institution, whether it is lexicalized in natural language or requires a compound linguistic expression. This renders suspect any univocal answer to this question in any particular case. Yet another question one can ask, which some authors take to have a (...) bearing on the issue of the naturalness of categories, is whether a system of categories constitutes a unique way of organizing a particular set of entities or phenomena, or whether there are other legitimate classification schemes that can coexist with it. Another way of putting this is by asking whether systems of categories can cut across one another, and if so, under what circumstances. Some philosophers have claimed that crosscutting systems of categories cannot exist as genuine natural kinds. This paper examines that claim and puts forward some counterexamples, concluding that this notion of natural kind is not in tune with scientific classification and ought to be rejected in favor of an alternative. (shrink)

Recent work on Natural Kind Essentialism has taken a deflationary turn. The assumptions about the grounds of essentialist truths concerning natural kinds familiar from the Kripke-Putnam framework are now considered questionable. The source of the problem, however, has not been sufficiently explicated. The paper focuses on the Twin Earth scenario, and it will be demonstrated that the essentialist principle at its core (which I call IDENT)—that necessarily, a sample of a chemical substance, A, is of the same kind as (...) another sample, B, if and only if A and B have the same microstructure—must be re-evaluated. The Twin Earth scenario also assumes the falsity of another essentialist principle (which I call INST): necessarily, there is a 1:1 correlation between (all of ) the chemical properties of a chemical substance and the microstructure of that substance. This assumption will be questioned, and it will be argued that, in fact, the best strategy for defending IDENT is to establish INST. The prospects for Natural Kind Essentialism and microstructural essentialism regarding chemical substances will be assessed with reference to recent work in the philosophy of chemistry. Finally, a weakened form of INST will be presented. (shrink)

I argue that Kant’s distinction between the cognitive roles of sensibility and understanding raises a question concerning the conditions necessary for objective representation. I distinguish two opposing interpretive positions—viz. Intellectualism and Sensibilism. According to Intellectualism all objective representation depends, at least in part, on the unifying synthetic activity of the mind. In contrast, Sensibilism argues that at least some forms of objective representation, specifically intuitions, do not require synthesis. I argue that there are deep reasons for thinking that Intellectualism is (...) incompatible with Kant's view as expressed in the Transcendental Aesthetic. We can better see how Kant’s arguments in the first Critique may be integrated, I suggest, by examining his notion of the 'unity' [Einheit] of a representation. I articulate two distinct ways in which a representation may possess unity and claim that we can use these notions to integrate Kant’s arguments in the Aesthetic and the Transcendental Deduction without compromising the core claims of either Sensibilism or Intellectualism—that intuition is a form of objective representation independent of synthesis, and that the kind of objective representations that ground scientific knowledge of the world require synthesis by the categories. (shrink)

Scientific realism driven by inference to the best explanation (IBE) takes empirically confirmed objects to exist, independent, pace empiricism, of whether those objects are observable or not. This kind of realism, it has been claimed, does not need probabilistic reasoning to justify the claim that these objects exist. But I show that there are scientific contexts in which a non-probabilistic IBE-driven realism leads to a puzzle. Since IBE can be applied in scientific contexts in which empirical confirmation (...) has not yet been reached, realists will in these contexts be committed to the existence of empirically unconfirmed objects. As a consequence of such commitments, because they lack probabilistic features, the possible empirical confirmation of those objects is epistemically redundant with respect to realism. (shrink)

Natural kinds, real kinds, or, following J.S Mill simply, Kinds, are thought to be an important asset for scientific realists in the non-fundamental (or “special”) sciences. Essential natures are less in vogue. I show that the realist would do well to couple her Kinds with essential natures in order to strengthen their epistemic and ontological credentials. I argue that these essential natures need not however be intrinsic to the Kind’s members; they may be historical. I (...) concentrate on assessing the merits of historical essential natures in a paradigm case of Kinds in the non-fundamental sciences: species. I specify two basic jobs for essential natures: 1) offering individuation criteria, and 2) providing a causal explanation of the Kind’s multiple projectable properties. I argue that at least in the case of species historical essences are fit for both tasks. The principled resistance to Kinds with historical essences should also be cleared. (shrink)

The new externalist picture of natural kind terms due to Kripke, Putnam, and others has become quite popular in philosophy. Many philosophers of science have remained sceptical. Häggqvist and Wikforss have recently criticised this view severely. They contend it depends essentially on a micro-essentialist view of natural kinds that is widely rejected among philosophers of science, and that a scientifically reasonable metaphysics entails the resurrection of some version of descriptivism. It is argued in this paper that the situation is (...) not quite as dark for the new theory of reference as many critics suggest. There are several distinct questions here which should not be conflated and ought to be dealt with one by one. Descriptivism remains arguably problematic. (shrink)

There is broad agreement among social researchers and social ontologists that the project of dividing humans into social kinds should be guided by at least two methodological commitments. First, a commitment to what best serves moral and political interests, and second, a commitment to describing accurately the causal structures of social reality. However, researchers have not sufficiently analyzed how these two commitments interact and constrain one another. In the absence of that analysis, several confusions have set in, threatening to (...) undermine shared goals for the responsible modeling of social kinds of humans. This essay first explains the source and substance of these confusions. Then, by distinguishing different value-laden investigative questions into the classification of social kinds of humans, it sets out specific relations of dependence and constraint between empirically-driven investigations and value-driven investigations into social kinds of humans. The result is a more detailed and fruitful framework for thinking about the classification of social kinds that respects both normative interests and mind-independent causal regularities. (shrink)

Natural Categories and Human Kinds is a recent and timely contribution to current debate on natural kinds. Because of the growing sophistication of this debate, it is necessary to make careful distinctions in order to appreciate the originality of Khalidi’s position. Khalidi’s view on natural kinds is naturalistic: if we want to know what Nature’s joints really are, we should look at the actual carving job carried out by our best scientific practices. Like LaPorte, Khalidi is (...) a fallibilist: our best scientific theories may be revised or abandoned and so can our current classifications of natural kinds. Unlike LaPorte, however, Khalidi is an anti-essentialist: he argues against the idea that membership in a natural kind is a matter of possessing an essential set of necessary and sufficient properties. Like Dupré, Khalidi is a pluralist and anti-reductionist: he does not believe that there is only one true classification system and that there are natural kinds only at the so-called "fundamental level" of microphysics. Khalidi develops his pluralistic and anti-reductionistic position on the basis of a deep appreciation for the special sciences but, unlike Dupré, he thinks that only the scientific inquiry, which is driven by epistemic purposes, discover natural kinds and that, therefore, there are important differences between scientific and folk classifications. Khalidi’s conception of natural kinds has both an epistemic and a metaphysical component. (shrink)

Scientific essentialism holds that: (1) each scientific kind is associated with the same set of properties in every possible world; and (2) every individual member of a scientific kind belongs to that kind in every possible world in which it exists. Recently, Ellis (Scientific essentialism, 2001 ; The philosophy of nature 2002 ) has provided the most sustained defense of scientific essentialism, though he does not clearly distinguish these two claims. In this paper, I argue (...) that both claims face a number of formidable difficulties. The necessities of scientific essentialism are not adequately distinguished from semantic necessities, they have not been shown to be necessities in the strictest sense, they must be relativized to context, and they must either be confined to a subset of scientific properties without warrant or their connection to causal powers must be revoked. Moreover, upon closer examination (1) turns out to be a trivial thesis that can be satisfied by non-kinds, and (2) is inapplicable to some of the most fundamental kinds in the basic sciences. (shrink)

The functionalist approach to kinds has suffered recently due to its association with law-based approaches to induction and explanation. Philosophers of science increasingly view nomological approaches as inappropriate for the special sciences like psychology and biology, which has led to a surge of interest in approaches to natural kinds that are more obviously compatible with mechanistic and model-based methods, especially homeostatic property cluster theory. But can the functionalist approach to kinds be weaned off its dependency on laws? (...) Dan Weiskopf has recently offered a reboot of the functionalist program by replacing its nomological commitments with a model-based approach more closely derived from practice in psychology. Roughly, Weiskopf holds that the natural kinds of psychology will be the functional properties that feature in many empirically successful cognitive models, and that those properties need not be localized to parts of an underlying mechanism. I here skeptically examine the three modeling practices that Weiskopf thinks introduce such non-localizable properties: fictionalization, reification, and functional abstraction. In each case, I argue that recognizing functional properties introduced by these practices as autonomous kinds comes at clear cost to those explanations’ counterfactual explanatory power. At each step, a tempting functionalist response is parochialism: to hold that the false or omitted counterfactuals fall outside the modeler’s explanatory aims, and so should not be counted against functional kinds. I conclude by noting the dangers this attitude poses to scientific disagreement, inviting functionalists to better articulate how the individuation conditions for functional kinds might outstrip the perspective of a single modeler. (shrink)

A prominent type of scientific realism holds that some important parts of our best current scientific theories are at least approximately true. According to such realists, radically distinct alternatives to these theories or theory-parts are unlikely to be approximately true. Thus one might be tempted to argue, as the prominent anti-realist Kyle Stanford recently did, that realists of this kind have little or no reason to encourage scientists to attempt to identify and develop theoretical alternatives that are radically (...) distinct from currently accepted theories in the relevant respects. In other words, it may seem that realists should recommend that scientists be relatively conservative in their theoretical endeavors. This paper aims to show that this argument is mistaken. While realists should indeed be less optimistic of finding radically distinct alternatives to replace current theories, realists also have greater reasons to value the outcomes of such searches. Interestingly, this holds both for successful and failed attempts to identify and develop such alternatives. (shrink)

This paper examines the phenomenon of ‘interactive kinds’ first identified by Ian Hacking. An interactive kind is one that is created or significantly modified once a concept of it has been formulated and acted upon in certain ways. Interactive kinds may also ‘loop back’ to influence our concepts and classifications. According to Hacking, interactive kinds are found exclusively in the human domain. After providing a general account of interactive kinds and outlining their philosophical significance, I argue (...) that they are not confined to the human realm, but that they can also occur elsewhere. Hence, I conclude by arguing that interactive kinds pose a challenge to scientific realism about kinds by making it difficult to make a distinction between real and non-real kinds. (shrink)

A large part of our exploration of the world consists in categorizing or classifying the objects and processes we encounter, both in scientific and everyday contexts. There are various, perhaps innumerable, ways to sort objects into different kinds or categories, but it is commonly assumed that, among the countless possible types of classifications, one group is privileged. Philosophy refers to such categories as natural kinds. Standard examples of such kinds include fundamental physical particles, chemical elements, and (...) biological species. The term natural does not imply that natural kinds ought to categorize only naturally occurring stuff or objects. Candidates for natural kinds can include man-made substances, such as synthetic elements, that can be created in a laboratory. The naturalness in question is not the naturalness of the entities being classified, but that of the groupings themselves. Groupings that are artificial or arbitrary are not natural; they are invented or imposed on nature. Natural kinds, on the other hand, are not invented, and many assume that scientific investigations should discover them. (shrink)

I distinguish three theses associated with the new mechanistic philosophy – concerning causation, explanation and scientific methodology. Advocates of each thesis are identified and relationships among them are outlined. I then look at some recent work on natural selection and mechanisms. There, attention to different kinds of New Mechanism significantly affects of what is at stake.

Two great problems of learning confront humanity: (1) learning about the universe, and about ourselves as a part of the universe, and (2) learning how to make progress towards as good a world as possible. We solved the first problem when we created modern science in the 17th century, but we have not yet solved the second problem. This puts us in a situation of unprecedented danger. Modern science and technology enormously increase our power to act, but not our power (...) to act wisely. All our current global crises have arisen as a result. What we need to do is learn from our solution to the first great problem of learning how to go about solving the second one. Properly implemented, this idea leads to a new kind of inquiry rationally devoted to helping humanity make progress towards as good a world as possible. (shrink)

This is an introduction to the volume "Explanation Beyond Causation: Philosophical Perspectives on Non-Causal Explanations", edited by A. Reutlinger and J. Saatsi (OUP, forthcoming in 2017). -/- Explanations are very important to us in many contexts: in science, mathematics, philosophy, and also in everyday and juridical contexts. But what is an explanation? In the philosophical study of explanation, there is long-standing, influential tradition that links explanation intimately to causation: we often explain by providing accurate information about the causes of the (...) phenomenon to be explained. Such causal accounts have been the received view of the nature of explanation, particularly in philosophy of science, since the 1980s. However, philosophers have recently begun to break with this causal tradition by shifting their focus to kinds of explanation that do not turn on causal information. The increasing recognition of the importance of such non-causal explanations in the sciences and elsewhere raises pressing questions for philosophers of explanation. What is the nature of non-causal explanations - and which theory best captures it? How do non-causal explanations relate to causal ones? How are non-causal explanations in the sciences related to those in mathematics and metaphysics? This volume of new essays explores answers to these and other questions at the heart of contemporary philosophy of explanation. The essays address these questions from a variety of perspectives, including general accounts of non-causal and causal explanations, as well as a wide range of detailed case studies of non-causal explanations from the sciences, mathematics and metaphysics. (shrink)

Geographic Information Science (GIS) is an interdisciplinary science aiming to detect and visually represent patterns in spatial data. GIS is used by businesses to determine where to open new stores and by conservation biologists to identify field study locations with relatively little anthropogenic influence. Products of GIS include topographic and thematic maps of the Earth’s surface, climate maps, and spatially referenced demographic graphs and charts. In addition to its social, political, and economic importance, GIS is of intrinsic philosophical interest due (...) to its methodological richness and because it is an instructive analogue to other sciences. This chapter works towards a philosophy of GIS and cartography, or PGISC. In particular, it examines practices of classifying geographic space, objects, and relations. By focusing on the use of natural kinds in data modeling and map generalization practices, I show how the making and using of kinds is contextual, fallible, plural, and purposive. (shrink)

According to one large family of views, scientific explanations explain a phenomenon (such as an event or a regularity) by subsuming it under a general representation, model, prototype, or schema (see Bechtel, W., & Abrahamsen, A. (2005). Explanation: A mechanist alternative. Studies in History and Philosophy of Biological and Biomedical Sciences, 36(2), 421–441; Churchland, P. M. (1989). A neurocomputational perspective: The nature of mind and the structure of science. Cambridge: MIT Press; Darden (2006); Hempel, C. G. (1965). Aspects of (...) scientific explanation. In C. G. Hempel (Ed.), Aspects of scientific explanation (pp. 331–496). New York: Free Press; Kitcher (1989); Machamer, P., Darden, L., & Craver, C. F. (2000). Thinking about mechanisms. Philosophy of Science, 67(1), 1–25). My concern is with the minimal suggestion that an adequate philosophical theory of scientific explanation can limit its attention to the format or structure with which theories are represented. The representational subsumption view is a plausible hypothesis about the psychology of understanding. It is also a plausible claim about how scientists present their knowledge to the world. However, one cannot address the central questions for a philosophical theory of scientific explanation without turning one’s attention from the structure of representations to the basic commitments about the worldly structures that plausibly count as explanatory. A philosophical theory of scientific explanation should achieve two goals. The first is explanatory demarcation. It should show how explanation relates with other scientific achievements, such as control, description, measurement, prediction, and taxonomy. The second is explanatory normativity. It should say when putative explanations succeed and fail. One cannot achieve these goals without undertaking commitments about the kinds of ontic structures that plausibly count as explanatory. Representations convey explanatory information about a phenomenon when and only when they describe the ontic explanations for those phenomena. (shrink)

In the course of developing an account of scientific progress, C. D. McCoy (2022) appeals centrally to understanding as well as to problem-solving. On the face of it, McCoy’s account could thus be described as a kind of hybrid of the understanding-based account that I favor (Dellsén 2016, 2021) and the functional (a.k.a. problem-solving) account developed most prominently by Laudan (1977; see also Kuhn 1970; Shan 2019). In this commentary, I offer two possible interpretations of McCoy’s account and explain (...) why I do not find it entirely compelling on either interpretation. (shrink)

Is simulation some new kind of science? We argue that instead simulation fits smoothly into existing scientific practice, but does so in several importantly different ways. Simulations in general, and computer simulations in particular, ought to be understood as techniques which, like many scientific techniques, can be employed in the service of various and diverse epistemic goals. We focus our attentions on the way in which simulations can function as (i) explanatory and (ii) predictive tools. We argue that (...) a wide variety of simulations, both computational and physical, are best conceived in terms of a set of common features: initial or input conditions, a mechanism or set of rules, and a set of results or output conditions. Studying simulations in these terms yields a new understanding of their character as well as a body of normative recommendations for the care and feeding of scientific simulations. (shrink)

Defences of perspectival realism are motivated, in part, by an attempt to find a middle ground between the realist intuition that science seems to tell us a true story about the world, and the Kuhnian intuition that scientific knowledge is historically and culturally situated. The first intuition pulls us towards a traditional, absolutist scientific picture, and the second towards a relativist one. Thus, perspectival realism can be seen as an attempt to secure situated knowledge without entailing epistemic relativism. (...) A very similar motivation is behind feminist standpoint theory, a view which aims to capture the idea that knowledge is socially situated, whilst retaining some kind of absolutism. Elsewhere I argue that the feminist project fails to achieve this balance; its commitment to situated knowledge unavoidably entails epistemic relativism (though of an unproblematic kind), which allows them to achieve all of their feminist goals. In this paper I will explore whether the same arguments apply to perspectival realism. And so I will be asking whether perspectival realism too is committed to an unproblematic kind of relativism, capable of achieving scientific goals; or, whether it succeeds in carving out a third view, between or beyond the relativism/absolutism dichotomy. (shrink)

Naturalism about natural kinds is the view that they are none other than the kinds discoverable by science. This thesis is in tension with what is perhaps the dominant contemporary view of natural kinds: essentialism. According to essentialism, natural kinds constitute a small subset of our scientific categories, namely those definable in terms of intrinsic, microphysical properties, which are possessed necessarily rather than contingently by their bearers. Though essentialism may appear compatible with naturalism, and is (...) indeed sometimes qualified with the epithet “scientific,” it has become increasingly clear in recent years that only a minority of categories posited by science satisfy those conditions. I will not try to argue against essentialism directly in this chapter. Instead, I will attempt to articulate an alternative, naturalist conception of natural kinds, according to which the mark of natural kinds is their discoverability by science, not just basic science but the special sciences and even the social sciences. (shrink)

Moral philosophers are, among other things, in the business of constructing moral theories. And moral theories are, among other things, supposed to explain moral phenomena. Consequently, one’s views about the nature of moral explanation will influence the kinds of moral theories one is willing to countenance. Many moral philosophers are (explicitly or implicitly) committed to a deductive model of explanation. As I see it, this commitment lies at the heart of the current debate between moral particularists and moral generalists. (...) In this paper I argue that we have good reasons to give up this commitment. In fact, I show that an examination of the literature on scientific explanation reveals that we are used to, and comfortable with, non-deductive explanations in almost all areas of inquiry. As a result, I argue that we have reason to believe that moral explanations need not be grounded in exceptionless moral principles. (shrink)

Theories of natural kinds can be seen to face a twofold task: First, they should provide an ontological account of what kinds of (fundamental) things there are, what exists. The second task is an epistemological one, accounting for the inductive reliability of acceptable scientific concepts. In this chapter I examine whether concepts and categories used in the cognitive sciences should be understood as natural kinds. By using examples from human memory research to illustrate my argument, I (...) critically examine some of the main contenders for a theory of natural kinds. I show that when applied to complex target domains – such as human cognition – both essentialist theories and more liberal accounts of natural kindhood (such as HPC theory) fail to simultaneously satisfy the ontological and epistemological desiderata for a theory of natural kinds. I argue, however, that natural kindhood of a category in a metaphysical sense is not necessary for its inductive reliability, and that HPC theory provides an analytically useful account of the grounds of category-based inductive inference. (shrink)

A perennial problem in social epistemology is the problem of expert testimony, specifically expert testimony regarding scientific issues: for example, while it is important for me to know information pertaining to anthropogenic climate change, vaccine safety, Covid-19, etc., I may lack the scientific background required to determine whether the information I come across is, in fact, true. Without being able to evaluate the science itself, then, I need to find trustworthy expert testifiers to listen to. A major project (...) in social epistemology has thus become determining what the markers of trustworthiness are that laypersons can appeal to in order to identify and acquire information from expert testifiers. At the same time, the ways in which we acquire scientific information has changed significantly, with much of it nowadays being acquired in online environments. While much has been said about the potential pitfalls of seeking information online, little has been said about how the nature of seeking information online should make us think about the problem of expert testimony. Indeed, it seems to be an underlying assumption that good markers of trustworthiness apply equally well when seeking information from expert testifiers in online and offline environments alike, and that the new challenges and opportunities presented by online environments merely affects the methods by which we can acquire evidence of said trustworthiness. Here I argue that in making this assumption one risks failing to account for how unique features of the ways in which we acquire information online affect how we evaluate the trustworthiness of experts. Specifically, I argue for two main claims: first, that the nature of information-seeking online is such that the extent to which information is susceptible to manipulation is a dominant marker of trustworthiness; second, as a result, one will be more likely to seek out a particular kind of expert testifier in online environments, what I call a cooperative as opposed to preemptive expert. The result is that criteria for expert trustworthiness may look significantly different when acquiring information online as opposed to offline. (shrink)

Homology is a natural kind concept, but one that has been notoriously elusive to pin down. There has been sustained debate over the nature of correspondence and the units of comparison. But this continued debate over its meaning has focused on defining homology rather than on its use in practice. The aim of this chapter is to concentrate on the practices of homologizing. I define “homologizing” to be a concept-in-use. Practices of homologizing are kinds of rule following, the satisfaction (...) of which demarcates a category—that of being a homologue. Identifying, explaining, discovering, and understanding are exchanges that connect practice to concept through the performance of a rule by practitioners. These practices are constitutive of natural kinding activities. If homologizing is a kind of kinding, consideration of these practices of discovery, tracking, and identification not only clarifies the meaning, use, and progression of the concept of homology, but provides further understanding of the processes and progression of natural kinds and kinding practices in general. (shrink)

The basic task of the essay is to exhibit science as a rational enterprise. I argue that in order to do this we need to change quite fundamentally our whole conception of science. Today it is rather generally taken for granted that a precondition for science to be rational is that in science we do not make substantial assumptions about the world, or about the phenomena we are investigating, which are held permanently immune from empirical appraisal. According to this standard (...) view, science is rational precisely because science does not make a priori metaphysical presuppositions about the world forever preserved from possible empirical refutation. It is of course accepted that an individual scientist, developing a new theory, may well be influenced by his own metaphysical presuppositions. In addition, it is acknowledged that a successful scientific theory, within the context of a particular research program, may be protected for a while from refutation, thus acquiring a kind of temporary metaphysical status, as long as the program continues to be empirically progressive. All such views unite, however, in maintaining that science cannot make permanent metaphysical presuppositions, held permanently immune from objective empirical evaluation. According to this standard view, the rationality of science arises, not from the way in which new theories are discovered, but rather from the way in which already formulated theories are appraised in the light of empirical considerations. And the fundamental problem of the rationality of science—the Humean problem of induction— concerns precisely the crucial issue of the rationality of accepting theories in the light of evidence. In this essay I argue that this widely accepted standard conception of science must be completely rejected if we are to see science as a rational enterprise. In order to assess the rationality of accepting a theory in the light of evidence it is essential to consider the ultimate aims of science. This is because adopting different aims for science will lead us, quite rationally, to accept different theories in the light of evidence. I argue that a basic aim of science is to explain. At the outset science simply presupposes, in a completely a priori fashion, that explanations can be found, that the world is ultimately intelligible or simple. In other words, science simply presupposes in an a priori way the metaphysical thesis that the world is intelligible, and then seeks to convert this presupposed metaphysical theory into a testable scientific theory. Scientific theories are only accepted insofar as they promise to help us realize this fundamental aim. At once a crucial problem arises. If scientific theories are only accepted insofar as they promise to lead us towards articulating a presupposed metaphysical theory, it is clearly essential that we can choose rationally, in an a priori way, between all the very different possible metaphysical theories that can be thought up, all the very different ways in which the universe might ultimately be intelligible. For holding different aims, accepting different metaphysical theories conceived of as blueprints for future scientific theories will, quite rationally, lead us to accept different scientific theories. Thus it is only if we can choose rationally between conflicting metaphysical blueprints for future scientific theories that we will be in a position to appraise rationally the acceptability of our present day scientific theories. We thus face the crucial problem: How can we choose rationally between conflicting possible aims for science, conflicting metaphysical blueprints for future scientific theories ? It is only if we can solve this fundamental problem concerning the aims of science that we can be in a position to appraise rationally the acceptability of existing scientific theories. There is a further point here. If we could choose rationally between rival aims, rival metaphysical blueprints for future scientific theories, then we would in effect have a rational method for the discovery of new scientific theories! Thus we reach the result: there is only a rational method for the appraisal of existing scientific theories if there is a rational method of discovery. I shall argue that the aim-oriented theory of scientific inquiry to be advocated here succeeds in exhibiting science as a rational enterprise in that it succeeds in providing a rational procedure for choosing between rival metaphysical blueprints: it thus provides a rational, if fallible, method of discovery, and a rational method for the appraisal of existing scientific theories—thus resolving the Humean problem. In Part I of the essay I argue that the orthodox conception of science fails to exhibit science as a rational enterprise because it fails to solve the Humean problem of induction. The presuppositional view advocated here does however succeed in resolving the Humean problem. In Part II of the essay I spell out the new aim-oriented theory of scientific method that becomes inevitable once we accept the basic presuppositional viewpoint. I argue that this new aim oriented conception of scientific method is essentially a rational method of scientific discovery, and that the theory has important implications for scientific practice. (shrink)

Abstract Criteria of scientific value are of different kinds. This paper concerns ultimate criteria, i.e. the axiology of science. Most ultimate criteria are multi?dimensional. This gives rise to an aggregation problem, which cannot be adequately solved with reference to attitudes and behaviour within the scientific community. Therefore, in many cases, there is no fact of the matter as to whether one theory is better than another. This, in turn, creates problems for methodology.

In our paper we investigate a difficulty arising when one tries to reconsiliateessentialis t’s thinking with classification practice in the biological sciences. The article outlinessome varieties of essentialism with particular attention to the version defended by Brian Ellis. Weunderline the basic difference: Ellis thinks that essentialism is not a viable position in biology dueto its incompatibility with biological typology and other essentialists think that these two elementscan be reconciled. However, both parties have in common metaphysical starting point and theylack explicit (...) track of methodological procedures. Methodological inquiry involves less demandingassumptions than metaphysical, and therefore it is justified to analyse abovementioned discrepancy between Ellis and other essentialist in this context. We do it by bottom-up investigation whichfocuses on the practice of taxonomists in the particular field of biology. A case study helps us todiscover four characteristics of biological typology practice: impossibility of algorithmization,relativity, subjectivity and conventionality. These features prove non-realistic and therefore anti-essentialistic character of biological classification. We conclude by saying that any essentialismrelated to the notion of biological kind cannot be regarded as justified by scientific enterprise of creating typologies. (shrink)

At the intersection of taxonomy and nomenclature lies the scientific practice of typification. This practice occurs in biology with the use of holotypes (type specimens), in geology with the use of stratotypes, and in metrology with the use of measurement prototypes. In this paper I develop the first general definition of a scientific type and outline a new philosophical theory of types inspired by Pierre Duhem. I use this general framework to resolve the necessity-contingency debate about type specimens (...) in philosophy of biology, to advance the debate over the myth of the absolute accuracy of standards in metrology, and to address the definition-correlation debate in geology. I conclude that just as there has been a productive synergy between philosophical accounts of natural kinds and scientific taxonomic practices, so too there is much to be gained from developing a deeper understanding of the practices and philosophy of scientific types. (shrink)

This paper offers an overview of "the species problem", arguing for a view of species as homeostatic property cluster kinds, positioning the resulting form of realism about species as an alternative to the claim that species are individuals and pluralistic views of species. It draws on taxonomic practice in the neurosciences, especially of neural crest cells and retinal ganglion cells, to motivate both the rejection of the species-as-individuals thesis and species pluralism.

This article aims to develop a new account of scientific explanation for computer simulations. To this end, two questions are answered: what is the explanatory relation for computer simulations? And what kind of epistemic gain should be expected? For several reasons tailored to the benefits and needs of computer simulations, these questions are better answered within the unificationist model of scientific explanation. Unlike previous efforts in the literature, I submit that the explanatory relation is between the simulation model (...) and the results of the simulation. I also argue that our epistemic gain goes beyond the unificationist account, encompassing a practical dimension as well. (shrink)

Theoretical models are widely held as sources of knowledge of reality. Imagination is vital to their development and to the generation of plausible hypotheses about reality. But how can imagination, which is typically held to be completely free, effectively instruct us about reality? In this paper I argue that the key to answering this question is in constrained uses of imagination. More specifically, I identify make-believe as the right notion of imagination at work in modelling. I propose the first overarching (...) taxonomy of types of constraints on scientific imagination that enables knowledge of reality. And I identify two main kinds of knowledge enabled by models, knowledge of the imaginary scenario specified by models and knowledge of reality. (shrink)

In this paper I distinguish between two kinds of meta-hypotheses, or hypotheses about science, at issue in the scientific realism debate. The first are descriptive empirical hypotheses regarding the nature of scientific inquiry. The second are epistemological theories about what individuals should / can justifiably believe about scientific theories. Favoring the realist Type-D meta-hypotheses, I argue that a particular set of realist and non-realist efforts in the debate over Type-E’s have been valuable in the quest to (...) describe and understand the nature of scientific inquiry. For the realism debate itself has inadvertently and indirectly laid the foundations for an important kind of Type-D meta-hypothesis, one regarding creativity in the history of science—which, in turn, is relevant to refining our descriptions of inference. After illustrating this result with regard to the historical argument against realism, I suggest that these empirically attained meta-hypotheses pertaining to scientific creativity can, in turn, be made methodologically prescriptive. (shrink)

Many philosophers have drawn parallels between scientific models and fictions. In this paper I will be concerned with a recent version of the analogy, which compares models to the imagined characters of fictional literature. Though versions of the position differ, the shared idea is that modeling essentially involves imagining concrete systems analogously to the way that we imagine characters and events in response to works of fiction. Advocates of this view argue that imagining concrete systems plays an ineliminable role (...) in the practice of modeling that cannot be captured by other accounts. The approach thus leaves open what we should say about the ontological status of model-systems, and here advocates differ among themselves, defending a variety of realist or anti-realist positions. I argue that this debate over the ontological status of model-systems is misguided. If model-systems are the kinds of objects fictional realists posit, they can play no role in explaining the epistemology of modeling for an advocate of this approach. So they are at best superfluous. Defenders of the approach should focus on developing an account of the epistemological role of imagining model-systems. (shrink)

Hermann von Helmholtz allows for not only physiological facts and psychological inferences, but also perspectival reasoning, to influence perceptual experience and knowledge gained from perception. But Helmholtz also defends a version of the view according to which there can be a kind of “perspectival truth” revealed in scientific research and investigation. Helmholtz argues that the relationships between subjective and objective, real and actual, actual and illusory, must be analyzed scientifically, within experience. There is no standpoint outside experience from which (...) we can reason, no extra-sensory knowledge of the constitution of the “ideal subject” or of the properties of “real objects.” In the tradition of psychophysics inherited by Helmholtz, we can arrive at a kind of perspectival analysis of perceptual experience, which embeds an account of that experience within the context of the history and situation of the perceiving subject. That analysis is relative to the perceiving subject, but the perspectival explanations Helmholtz constructs are not thereby relativist: in fact, for Helmholtz, the more squarely the perceiving subject is placed in a scientific, perspectival context, the more facts we are able to learn about her experience and the objects with which she interacts. (shrink)

This paper evaluates the Natural-Kinds Argument for cognitive extension, which purports to show that the kinds presupposed by our best cognitive science have instances external to human organism. Various interpretations of the argument are articulated and evaluated, using the overarching categories of memory and cognition as test cases. Particular emphasis is placed on criteria for the scientific legitimacy of generic kinds, that is, kinds characterized in very broad terms rather than in terms of their fine-grained (...) causal roles. Given the current state of cognitive science, I conclude that we have no reason to think memory or cognition are generic natural kinds that can ground an argument for cognitive extension. (shrink)