I propose a deductive-nomological model for mathematical scientific explanation. In this regard, I modify Hempel’s deductive-nomological model and test it against some of the following recent paradigmatic examples of the mathematical explanation of empirical facts: the seven bridges of Königsberg, the North American synchronized cicadas, and Hénon-Heiles Hamiltonian systems. I argue that mathematical scientific explanations that invoke laws of nature are qualitative explanations, and ordinary scientific explanations that employ mathematics are quantitative explanations. I analyse the repercussions of this deductivenomological model (...) on causal explanations. (shrink)

One of the arguments that is put forward both for and against strong moral realism is the argument for the causal effects of moral properties; Whether moral properties have a causal effect on the external and physical world to prove their reality or not. The first who argue this was Gilbert Harman, who considered moral properties to have no causal effects. Shafer-Landau has also obtained an ontological account of it and examined it. In this article, we examine the arguments of (...) Harman and Landau and the drawbacks that have been made to them, and the result is that the arguments of those who consider moral properties to have no causal effects have significant drawbacks and are not defensible. Explanations can also be used to defend the causal effects of moral properties and to use them to the benefit of realism. (shrink)

This chapter shows that the experimental philosophy has much to offer to philosophy of science by reviewing the existing experimental‐philosophy work in the philosophy of science and by defending it against an important criticism. A natural way of extending experimental philosophy methods to the philosophy of science is to survey scientists’ judgments. The chapter presents two projects in the philosophy of science that can benefit from such surveys: analyzing the scientific concepts found in particular scientific communities and studying scientific cognition. (...) It explains how surveying lay people's judgments can bear on issues in the philosophy of science. The chapter examines the possible contributions of bibliometric, ethnographic and cliometric methods to the philosophy of science. Ethnographic methods are particularly useful to study the social structure of science, the nature and role of social norms in the production of scientific knowledge, and the discovery heuristics at work in everyday scientific practice. (shrink)

In the last two decades, philosophy of neuroscience has predominantly focused on explanation. Indeed, it has been argued that mechanistic models are the standards of explanatory success in neuroscience over, among other things, topological models. However, explanatory power is only one virtue of a scientific model. Another is its predictive power. Unfortunately, the notion of prediction has received comparatively little attention in the philosophy of neuroscience, in part because predictions seem disconnected from interventions. In contrast, we argue that topological predictions (...) can and do guide interventions in science, both inside and outside of neuroscience. Topological models allow researchers to predict many phenomena, including diseases, treatment outcomes, aging, and cognition, among others. Moreover, we argue that these predictions also offer strategies for useful interventions. Topology-based predictions play this role regardless of whether they do or can receive a mechanistic interpretation. We conclude by making a case for philosophers to focus on prediction in neuroscience in addition to explanation alone. (shrink)

This thesis explores attempts to characterise the structure of reality. Three notions stand out: Lewisian naturalness, Sider’s ‘structure’, and grounding, where the latter has become the most popular way to characterise the structure of reality in the contemporary literature. I argue that none of these notions, as they are currently understood, are suited for limning the metaphysical structure of reality. In the first part of the thesis I argue that, by the lights of the relevant theories, both naturalness and structure (...) fall short of the theoretical role carved out for those posits. In the second part of the thesis I present two challenges to the ‘orthodox’ conception of grounding. The first contests the standard assumption that grounding is asymmetric, both by citing what I take to be best described as symmetric instances of grounding, and by developing and arguing for a new theory of metaphysical structure – ‘metaphysical interdependence’ – which takes grounding to be nonsymmetric. The second challenge concerns the relationship between grounding and explanation, and leads to a dilemma for the grounding theorist. My proposed resolution to the dilemma is to adopt an antirealist approach to grounding, which I further motivate and develop in the final chapter. (shrink)

Framing systematics as a field consistent with scientific inquiry entails that inferences of phylogenetic hypotheses have the goal of producing accounts of past causal events that explain differentially shared characters among organisms. Linking observations of characters to inferences occurs by way of why-questions implied by data matrices. Because of their form, why-questions require the use of common-cause theories. Such theories in phylogenetic inferences include natural selection and genetic drift. Selection or drift can explain ‘morphological’ characters but selection cannot be causally (...) applied to sequences since fitness differences cannot be directly associated with individual nucleotides or amino acids. The relation of selection to sequence data is by way of downward or top-down causation from those phenotypes upon which selection occurs. The application of phylogenetic inference to explain sequence data is thus restricted to instances where drift is the relevant theory; those nucleotides or amino acids that can be explained via downward causation are precluded from inclusion in the data matrix. The restrictions on the inclusion of sequence data in phylogenetic inferences equally apply to species hypotheses, precluding the more restrictive approach known as DNA barcoding. Not being able to discern drift and selection as relevant causal mechanisms can severely constrain the inclusion and explanations of sequence data. Implications of such exclusion are discussed in relation to the requirement of total evidence. (shrink)

This paper addresses a fundamental line of research in neuroscience: the identification of a putative neural processing core of the cerebral cortex, often claimed to be “canonical”. This “canonical” core would be shared by the entire cortex, and would explain why it is so powerful and diversified in tasks and functions, yet so uniform in architecture. The purpose of this paper is to analyze the search for canonical explanations over the past 40 years, discussing the theoretical frameworks informing this research. (...) It will highlight a bias that, in my opinion, has limited the success of this research project, that of overlooking the dimension of cortical development. The earliest explanation of the cerebral cortex as canonical was attempted by David Marr, deriving putative cortical circuits from general mathematical laws, loosely following a deductive-nomological account. Although Marr’s theory turned out to be incorrect, one of its merits was to have put the issue of cortical circuit development at the top of his agenda. This aspect has been largely neglected in much of the research on canonical models that has followed. Models proposed in the 1980s were conceived as mechanistic. They identified a small number of components that interacted as a basic circuit, with each component defined as a function. More recent models have been presented as idealized canonical computations, distinct from mechanistic explanations, due to the lack of identifiable cortical components. Currently, the entire enterprise of coming up with a single canonical explanation has been criticized as being misguided, and the premise of the uniformity of the cortex has been strongly challenged. This debate is analyzed here. The legacy of the canonical circuit concept is reflected in both positive and negative ways in recent large-scale brain projects, such as the Human Brain Project. One positive aspect is that these projects might achieve the aim of producing detailed simulations of cortical electrical activity, a negative one regards whether they will be able to find ways of simulating how circuits actually develop. (shrink)

Este trabajo consiste en un análisis de la tesis expuesta en el artículo de 1980 “Do the laws of physics state the facts?” de Nancy Cartwright, según la cual las leyes fundamentales de la física no “describen los hechos” porque, respecto de ellas, verdad y explicatividad se excluyen mutuamente. El texto fue luego republicado como tercer ensayo de su libro How the Laws of Physics Lie (1981), del que Mauricio Suárez afirma que el “trade-off” entre verdad y explicación es su (...) “tesis central”. El problema abordado es propio de la filosofía de la ciencia: cómo deben interpretarse o entenderse las leyes teóricas. Específicamente, si deben considerarse descripciones de hechos (es decir, literalmente, en el sentido de que existe una realidad con independencia de las leyes mismas y que las características de la realidad pueden ser representadas mediante el lenguaje: que tienen valor de verdad) o cumplen otra función dentro del conocimiento científico. El artículo de Cartwright estudia el caso del papel que cumplen las leyes fundamentales de la física cuando forman parte de las explicaciones por cobertura legal del tipo denominado por John Stuart Mill “por composición de causas”. Analiza la explicación de la atracción gravitatoria que hay entre dos objetos en un sistema físico en el que están presentes, además de las fuerzas gravitatorias, fuerzas eléctricas. Afirma que en ella la ley de la teoría de Newton tomada individualmente no describe lo que ocurre, no es verdadera. Pero no porque sea falsa sino porque su función o “rol” no consiste en “describir hechos” sino en ser parte de explicaciones científicas. Pero este argumento de la filósofa de la escuela de Stanford presenta dificultades semánticas, como el uso con dos sentidos diferentes del término teórico “fuerza”. Asimismo, es problemático que asuma que los hechos físicos son observables. Y no es correcta la afirmación de que una ley científica “se hace verdadera”, ni que “explica” hechos singulares, ni que “describe” en una explicación. (shrink)

The pragmatic theory of explanation is an attempt to see explanation as a linguistic response to a cognitive problem where the content of the response depends on the context of the scientific inquiry. The present paper draws on the rhetorical situation, as it is defined by Loyld Bitzer, in order to understand how the context may influence the content as well as the acceptability of the response.

The main purpose of this dissertation is to examine critically and discuss the role of imagination in science and religion, with particular emphasis on its possible epistemic, creative, and meaning-making functions. In order to answer my research questions, I apply theories and concepts from contemporary philosophy of mind on scientific and religious practices. This framework allows me to explore the mental state of imagination, not as an isolated phenomenon but, rather, as one of many mental states that co-exist and interplay (...) in our cogntive architecture. Based on the philosophical discourse of philosophy of mind, four types of imagination are indentified and conceptualized: sensory, propositional, experiential, and creative imagination. These categories are then employed on five phenomena that can be found in scientific and religious environments: metaphors, models, thought experiments, aspect perception, and - in the religious case - rituals. In relation to the concept of religious "seeing" I consider how imaginings may influence visionary experiences and visualization, and compare these phenomena with cases of scientific visualization and eureka experiences. In regard to scientific and religious models, a distinction is made between, on the one hand, two notions of truth and, on the other hand, truth-independent meaning-making. In light of these categories, I differentiate between, and critically discuss, the use of imagination in doxastic, non-doxastic and fictionalist accounts. In light of this investigation, I formulate and defend the position of interactivism, which acknowledges a constant interplay between different attitudes and mental states. In my examination of rituals and scientific and religious thought experiments, special attention is given to the mental capacity to recreate the experiences that are entailed in an imagined scenario. At the end of the investigation, I consider the possible impact that my study might have on how we view science and religion as well as the dialogue bewteen these two fields. (shrink)

Today, mechanisms and mechanistic explanation are very popular in philosophy of science and are deemed a welcome alternative to laws of nature and deductive‐nomological explanation. Starting from Mitchell's pragmatic notion of laws, I cast doubt on their status as a genuine alternative. I argue that (1) all complex‐systems mechanisms ontologically must rely on stable regularities, while (2) the reverse need not hold. Analogously, (3) models of mechanisms must incorporate pragmatic laws, while (4) such laws themselves need not always refer to (...) underlying mechanisms. Finally, I show that Mitchell's account is more encompassing than the mechanistic account *Received August 2008; revised January 2010. †To contact the author, please write to: Centre for Logic and Philosophy of Science, Ghent University, Blandijnberg 2, B‐9000 Belgium; e‐mail: [email protected]. (shrink)

Different why-questions emerge under different contexts and require different information in order to be addressed. Hence a relevance relation can hardly be invariant across contexts. However, what is indeed common under any possible context is that all explananda require scientific information in order to be explained. So no scientific information is in principle explanatorily irrelevant, it only becomes so under certain contexts. In view of this, scientific thought experiments can offer explanations, should we analyze their representational strategies. Their representations involve (...) empirical as well as hypothetical statements. I call this the “representational mingling” which bears scientific information that can explain events. Buchanan’s thought experiment from constitutional economics is examined to show how mingled representations explain. (shrink)

This essay develops an inferential account of model explanation, based on Mauricio Suárez’s inferential conception of scientific representation and Alisa Bokulich’s counterfactual account of model explanation. It is suggested that the fact that a scientific model can explain is essentially linked to how a modeler uses an established model to make various inferences about the target system on the basis of results derived from the model. The inference practice is understood as a two-step activity, with the first step involving making (...) counterfactual statements about the model itself and the second step involving making hypothetical statements transferring over claims derived from the model onto the target. To illustrate how this two-step activity proceeds, an agent-based simulation model is discussed. (shrink)

The literature on the nature of understanding can be divided into two broad camps. Explanationists believe that it is knowledge of explanations that is key to understanding. In contrast, their manipulationist rivals maintain that understanding essentially involves an ability to manipulate certain representations. The aim of this paper is to provide a novel knowledge based account of understanding. More specifically, it proposes an account of maximal understanding of a given phenomenon in terms of fully comprehensive and maximally well-connected knowledge of (...) it and of degrees of understanding in terms of approximations to such knowledge. It is completed by a contextualist semantics for outright attributions of understanding according to which an attribution of understanding is true of one just in case one knows enough about it to perform some contextually determined task. It is argued that this account has an edge over both its explanationist and manipulationist competitors. (shrink)

It is not necessarily the case that we ever have experiences of self, but human beings do regularly report instances for which self is experienced as absent. That is there are times when body parts, mental states, or actions are felt to be alien. Here I sketch an explanatory framework for explaining these alienation experiences, a framework that also attempts to explain the “mental glue” whereby self is bound to body, mind, or action. The framework is a multi-dimensional model that (...) integrates personal and sub-personal components, psychological and neural processes. I then proceed to show how this model can be applied to explain the action-related passivity experiences of persons suffering from schizophrenia. I argue that a distinctive phenomenological mark of these experiences is that they are vividly felt, unlike ordinary actions (those taken to belong to self), and I seek to explain these heightened sensory experiences from within the proposed framework. I also propose hypotheses concerning such phenomena as thought insertion and anarchic hand syndrome that are motivated by this framework. Finally, I argue that the proposed model and view of self-experiences is consistent with several aspects of and theories of consciousness, especially theories which indicate that consciousness is more likely to be engaged when we are dealing with novelty or error—e.g. when self seems to have gone missing. I conclude by recommending that if we wish to learn about self, we would be well advised to attend closely to those times when it seems absent. (shrink)

For millennia self has been conjectured to be necessary for consciousness. But scant empirical evidence has been adduced to support this hypothesis. Inconsistent explications of “self” and failure to design apt experiments have impeded progress. Advocates of phenomenological psychiatry, however, have helped explicate “self,” and employed it to explain some psychopathological symptoms. In those studies, “self” is understood in a minimalist sense, sheer “for-me-ness.” Unfortunately, explication of the “minimal self” (MS) has relied on conceptual analysis, and applications to psychopathology have (...) been hermeneutic, allowing for many degrees of interpretive latitude. The result is that MS’s current scientific status is analogous to that of the “atom,” at the time when “atom” was just beginning to undergo transformation from a philosophical to a scientific concept. Fortunately, there is now an opportunity to promote a similar transformation for “MS.” Discovery of the brain’s Default Mode Network (DMN) opened the door to neuroimaging investigations of self. Taking the DMN and other forms of intrinsic activity as a starting point, an empirical foothold can be established, one that spurs experimental research and that enables extension of research into multiple phenomena. New experimental protocols that posit “MS” can help explain phenomena hitherto not thought to be related to self, thereby hastening development of a mature science of self. In particular, targeting phenomena wherein consciousness is lost and recovered, as in some cases of Unresponsive Wakefulness Syndrome (UWS), allow for design of neuroimaging probes that enable detection of MS during non-conscious states. These probes, as well as other experimental protocols applied to NREM Sleep, General Anesthesia (GA), and the waking state, provide some evidence to suggest that not only can self and consciousness dissociate, MS might be a necessary precondition for conscious experience. Finally, these findings have implications for the science of consciousness: it has been suggested that “levels of consciousness” (LoC) is not a legitimate concept for the science of consciousness. But because we have the conceptual and methodological tools with which to refine investigations of MS, we have the means to identify a possible foundation—a bifurcation point—for consciousness, as well as the means by which to measure degrees of distance from that foundation. These neuroimaging investigations of MS position us to better assess whether LoC has a role to play in a mature science of consciousness. (shrink)

"Rationality: Contexts and Constraints" is an interdisciplinary reappraisal of the nature of rationality. In method, it is pluralistic, drawing upon the analytic approaches of philosophy, linguistics, neuroscience, and more. These methods guide exploration of the intersection between traditional scholarship and cutting-edge philosophical or scientific research. In this way, the book contributes to development of a suitably revised, comprehensive understanding of rationality, one that befits the 21st century, one that is adequately informed by recent investigations of science, pathology, non-human thought, emotion, (...) and even enigmatic Chinese texts that might previously have seemed to be expressions of irrationalism. Addresses recent challenges and Identifies a direction for future research on rationalityInvestigates the relationship between rationality and mental disorders, such as delusion and depressionAssesses reasoning in artificial intelligence and nonhuman animalsReflects on ancient Chinese Philosophy and possible cultural differences in human psychology Employs philosophical reflection, along with linguistic, probabilistic, and logical techniques. (shrink)

A cursory glance at the list of Nobel Laureates for Economics is sufficient to confirm Stanovich’s description of the project to evaluate human rationality as seminal. Herbert Simon, Reinhard Selten, John Nash, Daniel Kahneman, and others, were awarded their prizes less for their work in economics, per se, than for their work on rationality, as such. Although philosophical works have for millennia attempted to describe, explicate and evaluate individual and collective aspects of rationality, new impetus was brought to this endeavor (...) over the last century as mathematical logic along with the social and behavioral sciences emerged. Yet more recently, over the last several decades, propelled by the emergence of artificial intelligence, cognitive science, evolutionary psychology, neuropsychology, and related fields, even more sophisticated approaches to the study of rationality have emerged. (shrink)

__In this paper I investigate unification as a virtue of explanation. I the first part of the paper I give a brief exposition of the unification account of Schurz and Lambert and Schurz. I illustrate the advantages of this account in comparison to the older unification accounts of Friedman and Kitcher. In the second part I discuss several comments and objections to the Schurz-Lambert account that were raised by Weber and van Dyck, Gijsberg and de Regt. In the third and (...) final part, I argue that explanation should be understood as a prototype concept which contains nomic expectability, causality and unification as prototypical virtues of explanations, although none of these virtues provides a sufficient and necessary "defining condition" of explanation. (shrink)

Within collective epistemology, there is a class of theories that understand the epistemic status of collective attitude ascriptions, such as ‘the college union knows that the industrial action is going to plan’, or ‘the jury justifiedly believes that the suspect is guilty’, as saying that a sufficient subset of group member attitudes have the relevant epistemic status. In this paper, I will demonstrate that these summativist approaches to collective epistemology are incompatible with epistemic permissivism, the doctrine that a single body (...) of evidence may rationalize multiple doxastic attitudes. In particular, I will make use of epistemic permissivism to provide a general recipe for generating so-called divergence cases, which demonstrate situations in which rationality requires group-level and member-level attitudes to diverge. I will call this class of cases permissive divergence cases. While other divergence cases have been discussed in the literature, permissive divergence cases prove themselves to be less susceptible to many of the worries raised against their competitors, while being directly built on an often-defended epistemological thesis. (shrink)

Science is a product of society: in its funding, its participation, and its application. This Element explores the relationship between science and the public with resources from philosophy of science. Chapter 1 defines the questions about science's relationship to the public and outlines science's obligation to the public. Chapter 2 considers the Vienna Circle as a case study in how science, philosophy, and the public can relate very differently than they do at present. Chapter 3 examines how public understanding of (...) science can have a variety of different goals and introduces philosophical discussions of scientific understanding as a resource. Chapter 4 addresses public trust in science, including responding to science denial. Chapter 5 considers how expanded participation in science can contribute to public trust of science. Finally, Chapter 6 casts light on how science might discharge its obligations to the public. (shrink)

We might think that thought experiments are at their most powerful or most interesting when they produce new knowledge. This would be a mistake; thought experiments that seek understanding are just as powerful and interesting, and perhaps even more so. A growing number of epistemologists are emphasizing the importance of understanding for epistemology, arguing that it should supplant knowledge as the central notion. In this chapter, I bring the literature on understanding in epistemology to bear on explicating the different ways (...) that thought experiments increase three important kinds of understanding: explanatory, objectual and practical. (shrink)

I argue against the claim, advanced by David Albert and Barry Loewer, that all non-fundamental laws can be derived from those required to underwrite the second law of thermodynamics.

This paper analyzes the historical context and systematic importance of Kant's hypothetical use of reason. It does so by investigating the role of hypotheses in Kant's philosophy of science. We first situate Kant’s account of hypotheses in the context of eighteenth-century German philosophy of science, focusing on the works of Wolff, Meier, and Crusius. We contrast different conceptions of hypotheses of these authors and elucidate the different theories of probability informing them. We then adopt a more systematic perspective to discuss (...) Kant's idea that scientific hypotheses must articulate real possibilities. We argue that Kant's views on the intelligibility of scientific hypotheses constitute a valuable perspective on scientific understanding and the constraints it imposes on scientific rationality. (shrink)

There are three main approaches to scientific explanation in the philosophical literature. The unification approach claims that science explains by fitting the particular facts and events within a general theoretical framework. The mechanistic approach claims that science explains by identifying mechanisms. According to the manipulationist approach an explanation ought to be such that it can be used to answer a “what-if-things-had-been-different question.” The article examines whether these three approaches are compatible or not in the case of the social sciences, and (...) it concludes by defending explanatory pluralism. (shrink)

The central aim of this paper is to shed light on the nature of explanation in computational neuroscience. I argue that computational models in this domain possess explanatory force to the extent that they describe the mechanisms responsible for producing a given phenomenon—paralleling how other mechanistic models explain. Conceiving computational explanation as a species of mechanistic explanation affords an important distinction between computational models that play genuine explanatory roles and those that merely provide accurate descriptions or predictions of phenomena. It (...) also serves to clarify the pattern of model refinement and elaboration undertaken by computational neuroscientists. (shrink)

An account of distinctively mathematical explanation (DME) should satisfy three desiderata: it should account for the modal import of some DMEs; it should distinguish uses of mathematics in explanation that are distinctively mathematical from those that are not (Baron [2016]); and it should also account for the directionality of DMEs (Craver and Povich [2017]). Baron’s (forthcoming) deductive-mathematical account, because it is modelled on the deductive-nomological account, is unlikely to satisfy these desiderata. I provide a counterfactual account of DME, the Narrow (...) Ontic Counterfactual Account (NOCA), that can satisfy all three desiderata. NOCA appeals to ontic considerations to account for explanatory asymmetry and ground the relevant counterfactuals. NOCA provides a unification of the causal and the non-causal, the ontic and the modal, by identifying a common core that all explanations share and in virtue of which they are explanatory. (shrink)

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

Este artigo é uma breve introdução à filosofia da linguagem. Ele se concentra nos problemas que surgem a partir de dois conceitos centrais: referência e significado. Em particular, o foco central é no problema fundacional da referência e no problema descritivo do significado, assim como a relação entre eles. Embora esta de modo algum seja uma introdução exaustiva ao tema, muitos conceitos centrais são clarificados, como por exemplo teoria da referência, termo singular, termo geral, teoria do significado, composicionalidade, conteúdo, significado (...) linguístico, implicatura conversacional, vagueza, etc. Espera-se que sirva como um primeiro contato com a disciplina, principalmente voltado a estudantes de filosofia, filosofia da linguagem e áreas afins. (shrink)

Seungbae Park argues that Bas van Fraassen’s rejection of inference to the best explanation (IBE) is problematic for his contextual theory of explanation because van Fraassen uses IBE to support the contextual theory. This paper provides a defense of van Fraassen’s views from Park’s objections. I point out three weaknesses of Park’s objection against van Fraassen. First, van Fraassen may be perfectly content to accept the implications that Park claims to follow from his views. Second, even if van Fraassen rejects (...) IBE he may still endorse particular arguments that instantiate IBE. Third, van Fraassen does not, in fact, use IBE to support his contextual theory. (shrink)

The paper provides a systematic overview of recent debates in epistemology and philosophy of science on the nature of understanding. We explain why philosophers have turned their attention to understanding and discuss conditions for “explanatory” understanding of why something is the case and for “objectual” understanding of a whole subject matter. The most debated conditions for these types of understanding roughly resemble the three traditional conditions for knowledge: truth, justification and belief. We discuss prominent views about how to construe these (...) conditions for understanding, whether understanding indeed requires conditions of all three types and whether additional conditions are needed. (shrink)

Bernard Williams argues that philosophy is in some deep way akin to history. This article is a novel exploration and defense of the Williams thesis —though in a way anathema to Williams himself. The key idea is to apply a central moral from what is sometimes called the analytic philosophy of history of the 1960s to the philosophy of philosophy of today, namely, the separation of explanation and laws. I suggest that an account of causal explanation offered by David Lewis (...) may be modified to bring out the way in which this moral applies to philosophy, and so to defend the Williams thesis. I discuss in detail the consequences of the thesis for the issue of philosophical progress and note also several further implications: for the larger context of contemporary metaphilosophy, for the relation of philosophy to other subjects, and for explaining, or explaining away, the belief that success in philosophy requires a field-specific ability or brilliance. (shrink)

Selection explanations explain some non-accidental generalizations in virtue of a selection process. Such explanations are not particulaizable - they do not transfer as explanations of the instances of such generalizations. This is unlike many explanations in the physical sciences, where the explanation of the general fact also provides an explanation of its instances (i.e. standard D-N explanations). Are selection explanations (e.g. in biology) therefore a different kind of explanation? I argue that to understand this issue, we need to see that (...) a standard D-N explanation of some non-accidental generalization (al Fs are Gs) may also ipso facto explain its contrapositive (all non-Gs are non-Fs), but the explanation is particularizable with respect to the former but not to the latter. This can be seen by noting that the Raven Paradox counterexample to the H-D model of confirmation also generates a counterexample to the D-N model of explanation (all ravens are black does not explain why the non-black shoe is a non-raven). In such cases it is natural to take the generalization with the positive predicates to have a particularizable explanation. However, this need not be the case, and in selection explanations it is the generalization with the positive predicates whose explanation is no particularizable. Thus there is no need to suppose that selection explanations are fundamentally different. (shrink)

Arguably no concept is more fundamental to science than that of causality, for investigations into cases of existence, persistence, and change in the natural world are largely investigations into the causes of these phenomena. Yet the metaphysics and epistemology of causality remain unclear. For example, the ontological categories of the causal relata have been taken to be objects (Hume 1739), events (Davidson 1967), properties (Armstrong 1978), processes (Salmon 1984), variables (Hitchcock 1993), and facts (Mellor 1995). (For convenience, causes and effects (...) will usually be understood as events in what follows.) Complicating matters, causal relations may be singular (Socrates’s drinking hemlock caused Socrates’s death) or general (Drinking hemlock causes death); hence the relata might be tokens (e.g., instances of properties) or types (e.g., types of events) of the category in question. Other questions up for grabs are: Are singular causes metaphysically and/or epistemologically prior to general causes or vice versa (or neither)? What grounds the intuitive asymmetry of the causal relation? Are macro-causal relations reducible to micro-causal relations? And perhaps most importantly: Are causal facts (e.g., the holding of causal relations) reducible to non-causal facts (e.g., the holding of certain spatiotemporal relations)? (shrink)

After Wesley Salmon’s causal-mechanical stance on explanation in the 1980s, the ontic-epistemic debate of scientific explanations appeared to be resolved in the philosophy of science. However, since the twenty-first century, this debate has been rekindled among philosophers who focus on mechanistic explanations. Nevertheless, its issues have evolved, necessitating scrutiny of the new trends in this debate and a comparison with the original controversy between Carl Hempel and Salmon. The primary objective of this paper is to elucidate three categorical dimensions in (...) the ontic-epistemic debates, spanning from the original to the recent controversies. Subsequently, it will explore why the conception of explanation is linked to representations, what conditions are necessary for linguistic expressions to be explanatory, and what roles norms play in explanation. Consequently, contrary to the common stereotype, it will be argued that mechanistic explanations are more likely to be epistemic rather than ontic. (shrink)

The paper introduces a special issue of the journal Philosophical Problems in Science (ZFN) on the topic of the nature and norms of scientific explanation.

The act of understanding is at the heart of all scientific activity; without it any ostensibly scientific activity is as sterile as that of a high school student substituting numbers into a formula. Ordinary language often uses visual metaphors in connection with understanding. When we finally understand what someone is trying to point out to us, we exclaim: “I see!” When someone really understands a subject matter, we say that she has “insight”. There appears to be a link between visualization (...) and understanding, and between visualizability and intelligibility. This applies in science no less than in daily life: visualization is regarded as a useful means of achieving scientific understanding, even in the .. (shrink)

It is often claimed—especially by scientific realists—that science provides understanding of the world only if its theories are (at least approximately) true descriptions of reality, in its observable as well as unobservable aspects. This paper critically examines this ‘realist thesis’ concerning understanding. A crucial problem for the realist thesis is that (as study of the history and practice of science reveals) understanding is frequently obtained via theories and models that appear to be highly unrealistic or even completely fictional. So we (...) face the dilemma of either giving up the realist thesis that understanding requires truth, or allowing for the possibility that in many if not all practical cases we do not have scientific understanding. I will argue that the first horn is preferable: the link between understanding and truth can be severed. This becomes a live option if we abandon the traditional view that scientific understanding is a special type of knowledge. While this view implies that understanding must be factive, I avoid this implication by identifying understanding with a skill rather than with knowledge. I will develop the idea that understanding phenomena consists in the ability to use a theory to generate predictions of the target system’s behavior. This implies that the crucial condition for understanding is not truth but intelligibility of the theory, where intelligibility is defined as the value that scientists attribute to the theoretical virtues that facilitate the construction of models of the phenomena. I will show, first, that my account accords with the way practicing scientists conceive of understanding, and second, that it allows for the use of idealized or fictional models and theories in achieving understanding. (shrink)

In recent years, scientific understanding has become a focus of attention in philosophy of science. Since understanding is typically associated with the pragmatic and psychological dimensions of explanation, shifting the focus from explanation to understanding may induce a shift from accounts that embody normative ideals to accounts that provide accurate descriptions of scientific practice. Not surprisingly, many ‘friends of understanding’ sympathize with a naturalistic approach to the philosophy of science. However, this raises the question of whether the proposed theories of (...) understanding can still have normative power. In this paper I address this question by examining two theories of scientific understanding: Jan Faye’s pragmatic-rhetorical theory and my own contextual theory of scientific understanding. I argue that both theories leave room for normativity, despite their naturalistic tendencies. The normative power of my contextual theory is illustrated with a case study of the chemical revolution. (shrink)

In recent years, a revisionist process focused on logical positivism can be observed, particularly regarding Carnap’s work. In this paper, I argue against the interpretation that Kuhn’s The Structure of Scientific Revolutions having been published in the International Encyclopedia of Unified Science, co-edited by Carnap, is evidence of the revisionist idea that Carnap “would have found Structure philosophically congenial”. I claim that Kuhn’s book, from Carnap’s point of view, is not in philosophy of science but rather in history of science (...) (in the context of a sharp discovery–justification distinction). It could also explain the fact that, despite his sympathetic letters to Kuhn as editor, Carnap never refers to Kuhn’s book in his work in philosophy of science. (shrink)

Understanding is a valued trait in any epistemic practice, scientific or not. Yet, when it comes to characterizing its nature, the notion has not received the philosophical attention it deserves. We have set ourselves three tasks in this paper. First, we defend the importance of this endeavor. Second, we consider and criticize a number of proposals to this effect. Third, we defend an alternative account, focusing on abilities as the proper mark of understanding.

There are many putative counterexamples to the view that all scientific explanations are causal explanations. Using a new theory of what it is to be a causal explanation, Bradford Skow has recently argued that several of the putative counterexamples fail to be non-causal. This paper defends some of the counterexamples by showing how Skow’s argument relies on an overly permissive theory of causal explanations.

PurposeIn this article, we aim to present and defend a contextual approach to mathematical explanation.MethodTo do this, we introduce an epistemic reading of mathematical explanation.ResultsThe epistemic reading not only clarifies the link between mathematical explanation and mathematical understanding, but also allows us to explicate some contextual factors governing explanation. We then show how several accounts of mathematical explanation can be read in this approach.ConclusionThe contextual approach defended here clears up the notion of explanation and pushes us towards a pluralist vision (...) on mathematical explanation. (shrink)

In The Explanatory Dispensability of Idealizations, Sam Baron suggests a possible strategy enabling the indispensability argument to break the symmetry between mathematical claims and idealization assumptions in scientific models. Baron’s distinction between mathematical and non-mathematical idealization, I claim, is in need of a more compelling criterion, because in scientific models idealization assumptions are expressed through mathematical claims. In this paper I argue that this mutual dependence of idealization and mathematics cannot be read in terms of symmetry and that Baron’s non-causal (...) notion of mathematical difference-making is not effective in justifying any symmetry-breaking between mathematics and idealization. The function of making a difference that Baron attributes to mathematics cannot be referred to physical facts, but to the features of quantities, such as step lengths or time intervals taken into account in the models. It appears, indeed, that it does not follow from Baron’s argument that idealizations do not help to carry the explanatory load at least for two reasons: mathematics is not independent of idealizations in modelling and idealizations help mathematics to carry the explanatory load of a model in different degrees. (shrink)

There appears to be a widespread belief that the social sciences during the 1950s and 1960s can be characterized by an almost unquestioned faith in a positivist philosophy of science. In contrast, the article shows that even within the narrower segment of Cold War social science, positivism was not an unquestioned doctrine blindly followed by everybody, but that quite divergent views coexisted. The article analyses two ‘techniques of prospection’, the Delphi technique and political gaming, from the perspective of a comprehensive (...) set of ideas attributed to ‘positivism’. Both techniques were developed in the early 1950s by researchers at the RAND Corporation, a Californian think tank with tight relations to the US Air Force. Despite the closeness of origin, the two techniques show considerable differences in their basic epistemologies. The article thus concludes that more important than positivism in uniting US Cold War social science was the shared sense of urgency and of the potential of social science to put decision-making in foreign policy on a rational basis. In this sense, as far as the Cold War social sciences were of a piece, they were made so by the sense of danger and urgency of action evoked by the image of the Iron Curtain. (shrink)