In the recent philosophy of explanation, a growing attention to and discussion of non-causal explanations has emerged, as there seem to be compelling examples of non-causal explanations in the sciences, in pure mathematics, and in metaphysics. I defend the claim that the counterfactual theory of explanation (CTE) captures the explanatory character of both non-causal scientific and metaphysical explanations. According to the CTE, scientific and metaphysical explanations are explanatory by virtue of revealing counterfactual dependencies between the explanandum and the explanans. I (...) support this claim by illustrating that CTE is applicable to Euler’s explanation (an example of a non-causal scientific explanation) and Loewer’s explanation (an example of a non-causal metaphysical explanation). (shrink)

It is argued that a popular way of accounting for the distinctive value of knowledge by appeal to the distinctive value of cognitive achievements fails because it is a mistake to identify knowledge with cognitive achievements. Nevertheless, it is claimed that understanding, properly conceived, is a type of cognitive achievement, and thus that the distinctive value of cognitive achievements can explain why understanding is of special value.

This is, no doubt, an emotional response, but there are, I believe, occasions when an emotional response is the only intellectually honest one. Brian Barry (1975, p. 332)Deliberative democracy is o...

The argument for modal collapse is partly responsible for the widespread rejection of the so-called Principle of Sufficient Reason in recent times. This paper discusses the PSR against the background of the recent debate about grounding and develops principled reasons for rejecting the argument from modal collapse.

Is the nature of explanation a metaphysical issue? Or has it more to do with psychology and pragmatics? To put things in a different way: what are primary relata in an explanation? What sorts of thing explain what other sorts of thing? David Lewis identifies two senses of ‘explanation’ (Lewis 1986, 217–218). In the first sense, an explanation is an act of explaining. I shall call this the subjectivist sense, since its existence depends on some subject doing the explaining. Hence (...) it is people who, in this sense, explain things. In the second of his two senses, Lewis says, quoting Sylvain Bromberger, that one may properly ask of an explanation “Does anyone know it? Who thought of it first? Is it very complicated?” (Lewis 1986, 218; Bromberger 1965). In this second sense, no subject is needed, the explanation can remain unknown, perhaps for ever. So I call this the objectivist sense. (shrink)

The goal of this paper is to develop a counterfactual theory of explanation. The CTE provides a monist framework for causal and non-causal explanations, according to which both causal and non-causal explanations are explanatory by virtue of revealing counterfactual dependencies between the explanandum and the explanans. I argue that the CTE is applicable to two paradigmatic examples of non-causal explanations: Euler’s explanation and renormalization group explanations of universality.

By briefly reviewing three well-known scientific revolutions in fundamental physics (the discovery of inertia, of special relativity and of general relativity), I claim that problems that were supposed to be crying for a dynamical explanation in the old paradigm ended up receiving a structural explanation in the new one. This claim is meant to give more substance to Kuhn’s view that revolutions are accompanied by a shift in what needs to be explained, while suggesting at the same time the existence (...) of a pattern that is common to all of the discussed case-studies. It remains to be seen whether also quantum mechanics, in particular entanglement, conforms to this pattern. (shrink)

What is it that makes someone wise, or one person wiser than another? I argue that wisdom consists in knowledge of how to live well, and that this knowledge of how to live well is constituted by various further kinds of knowledge. One concern for this view is that knowledge is not needed for wisdom but rather some state short of knowledge, such as having rational or justified beliefs about various topics. Another concern is that the emphasis on knowing how (...) to live well fails to do justice to the ancient tradition of ‘theoretical wisdom’. I address both of these concerns in filling out the account. (shrink)

This paper aims to argue for a lawful, intentional approach to human behavior. Donald Davidson’s idea that an event is mental according to the way it is described is here accepted. However, his nonlawful conception of psychology, in its turn, is rejected. Rather, based on Howard Rachlin’s teleological behaviorism, a lawful, externalist approach to explaining human behavior is adopted, according to which a bit of behavior is to be interpreted in connection with other ones, within a certain social context. It (...) is argued here also that Rachlin’s perspective amounts to a sort of externalization of intentionality. (shrink)

In what sense do the sciences explain? Or do they merely describe what is going on without answering why-questions at all. But cannot description at an appropriate ‘level’ provide all that we can reasonably ask of an explanation? Well, what do we mean by explanation anyway? What, if anything, gets left out when we provide a so-called scientific explanation? Are there limits of explanation in general, and scientific explanation, in particular? What are the criteria for a good explanation? Is it (...) possible to satisfy all the desiderata simultaneously? If not, which should we regard as paramount? What is the connection between explanation and prediction? What exactly is it that statistical explanations explain? These are some of the questions that have generated a very extensive literature in the philosophy of science. In attempting to answer them, definite views will have to be taken on related matters, such as physical laws, causality, reduction, and questions of evidence and confirmation, of theory and observation, realism versus antirealism, and the objectivity and rationality of science. I will state my own views on these matters, in the course of this essay. To argue for everything in detail and to do justice to all the alternative views, would fill a book, perhaps several books. I want to lead up fairly quickly to modern physics, and review the explanatory situation there in rather more detail. (shrink)

I provide a brief history of pragmatics as it relates to explanation, highlighting the great neglect of pragmatics and pragmatic considerations in regard to explanation during the mid-twentieth century. In order to understand pragmatic considerations regarding explanation, I utilize the work of Bas C. van Fraassen, Peter Achinstein, and Jan Faye. These thinkers provide crucial tools for understanding pragmatics, especially with regard to concepts such as context and exigence. The work of these thinkers provides the platform from which I compose (...) a definition of pragmatic considerations. (shrink)

This work consists of two parts. Part I will be a contribution to a philo- sophical discussion of the nature of causal explanation. It will present my contrastive counterfactual theory of causal explanation and show how it can be used to deal with a number of problems facing theories of causal explanation. Part II is a contribution to a discussion of the na- ture of interest explanation in social studies of science. The aim is to help to resolve some controversies (...) concerning interest explanation by explicating the concept of interest and its explanatory uses by using the account of explanation developed in Part I. (shrink)

In this paper I assume that we have some intuitive knowledge—i.e. beliefs that amount to knowledge because they are based on intuitions. The question I take up is this: given that some intuition makes a belief based on it amount to knowledge, in virtue of what does it do so? We can ask a similar question about perception. That is: given that some perception makes a belief based on it amount to knowledge, in virtue of what does it do so? (...) A natural idea about perception is that a perception makes a belief amount to knowledge in part by making you sensorily aware of the concrete objects it is about. The analogous idea about intuition is that an intuition makes a belief amount to knowledge in part by making you intellectually aware of the abstract objects it is about. I expand both ideas into fuller accounts of perceptual and intuitive knowledge, explain the main challenge to this sort of account of intuitive knowledge (i.e. the challenge of making sense of intellectual awareness), and develop a response to it. (shrink)

In this paper we will offer a few examples to illustrate the orientation of contemporary research in data analysis and we will investigate the corresponding role of mathematics. We argue that the modus operandi of data analysis is implicitly based on the belief that if we have collected enough and sufficiently diverse data, we will be able to answer most relevant questions concerning the phenomenon itself. This is a methodological paradigm strongly related, but not limited to, biology, and we label (...) it the microarray paradigm. In this new framework, mathematics provides powerful techniques and general ideas which generate new computational tools. But it is missing any explicit isomorphism between a mathematical structure and the phenomenon under consideration. This methodology used in data analysis suggests the possibility of forecasting and analyzing without a structured and general understanding. This is the perspective we propose to call agnostic science, and we argue that, rather than diminishing or flattening the role of mathematics in science, the lack of isomorphisms with phenomena liberates mathematics, paradoxically making more likely the practical use of some of its most sophisticated ideas. (shrink)

Denis Walsh has written a striking new defense in this journal of the statisticalist (i.e., noncausalist) position regarding the forces of evolution. I defend the causalist view against his new objections. I argue that the heart of the issue lies in the nature of nonadditive causation. Detailed consideration of that turns out to defuse Walsh’s ‘description‐dependence’ critique of causalism. Nevertheless, the critique does suggest a basis for reconciliation between the two competing views. *Received December 2009; revised December 2009. †To contact (...) the author, please write to: Department of Philosophy, 599 Lucas Hall, One University Boulevard, University of Missouri, St. Louis, MO 63121; e‐mail: [email protected]. (shrink)

An overview of how mechanisms work in explanations.

This target article presents a new computational theory of explanatory coherence that applies to the acceptance and rejection of scientific hypotheses as well as to reasoning in everyday life, The theory consists of seven principles that establish relations of local coherence between a hypothesis and other propositions. A hypothesis coheres with propositions that it explains, or that explain it, or that participate with it in explaining other propositions, or that offer analogous explanations. Propositions are incoherent with each other if they (...) are contradictory, Propositions that describe the results of observation have a degree of acceptability on their own. An explanatory hypothesis is acccpted if it coheres better overall than its competitors. The power of the seven principles is shown by their implementation in a connectionist program called ECHO, which treats hypothesis evaluation as a constraint satisfaction problem. Inputs about the explanatory relations are used to create a network of units representing propositions, while coherende and incoherence relations are encoded by excitatory and inbihitory links. ECHO provides an algorithm for smoothly integrating theory evaluation based on considerations of explanatory breadth, simplicity, and analogy. It has been applied to such important scientific cases as Lovoisier's argument for oxygen against the phlogiston theory and Darwin's argument for evolution against creationism, and also to cases of legal reasoning. The theory of explanatory coherence has implications for artificial intelligence, psychology, and philosophy. (shrink)

, whereby some causes are deemed more important than others, are ubiquitous in historical studies. Drawing from influential recent work on causation, I develop a definition of causal-explanatory strength. This makes clear exactly which aspects of explanatory weighting are subjective and which objective. It also sheds new light on several traditional issues, showing for instance that: underlying causes need not be more important than proximate ones; several different causes can each be responsible for most of an effect; small causes need (...) not be less important than big ones; and non-additive interactive effects between causes present no particular difficulty. Key Words: causation • explanation • history • interaction • proximate • underlying. (shrink)

Among philosophers of science there seems to be a general consensus that understanding represents a species of knowledge, but virtually every major epistemologist who has thought seriously about understanding has come to deny this claim. Against this prevailing tide in epistemology, I argue that understanding is, in fact, a species of knowledge: just like knowledge, for example, understanding is not transparent and can be Gettiered. I then consider how the psychological act of "grasping" that seems to be characteristic of understanding (...) differs from the sort of psychological act that often characterizes knowledge. Zagzebski's account Kvanvig's account Two problems Comanche cases Unreliable sources of information The upper-right quadrant So is understanding a species of knowledge? A false choice. (shrink)

A wave of recent work in metaphysics seeks to undermine the anti-reductionist, functionalist consensus of the past few decades in cognitive science and philosophy of mind. That consensus apparently legitimated a focus on what systems do, without necessarily and always requiring attention to the details of how systems are constituted. The new metaphysical challenge contends that many states and processes referred to by functionalist cognitive scientists are epiphenomenal. It further contends that the problem lies in functionalism itself, and that, to (...) save the causal significance of mind, it is necessary to re-embrace reductionism. We argue that the prescribed return to reductionism would be disastrous for the cognitive and behavioral sciences, requiring the dismantling of most existing achievements and placing intolerable restrictions on further work. However, this argument fails to answer the metaphysical challenge on its own terms. We meet that challenge by going on to argue that the new metaphysical skepticism about functionalist cognitive science depends on reifying two distinct notions of causality (one primarily scientific, the other metaphysical), then equivocating between them. When the different notions of causality are properly distinguished, it is clear that functionalism is in no serious philosophical trouble, and that we need not choose between reducing minds or finding them causally impotent. The metaphysical challenge to functionalism relies, in particular, on a naïve and inaccurate conception of the practice of physics, and the relationship between physics and metaphysics. Key Words: explanation; functionalism; mental causation; metaphysics; reductionism. (shrink)

Can phenomenal consciousness be given a reductive natural explanation? Exponents of an.

In this paper I argue that the search for explainable models and interpretable decisions in AI must be reformulated in terms of the broader project of offering a pragmatic and naturalistic account of understanding in AI. Intuitively, the purpose of providing an explanation of a model or a decision is to make it understandable to its stakeholders. But without a previous grasp of what it means to say that an agent understands a model or a decision, the explanatory strategies will (...) lack a well-defined goal. Aside from providing a clearer objective for XAI, focusing on understanding also allows us to relax the factivity condition on explanation, which is impossible to fulfill in many machine learning models, and to focus instead on the pragmatic conditions that determine the best fit between a model and the methods and devices deployed to understand it. After an examination of the different types of understanding discussed in the philosophical and psychological literature, I conclude that interpretative or approximation models not only provide the best way to achieve the objectual understanding of a machine learning model, but are also a necessary condition to achieve post hoc interpretability. This conclusion is partly based on the shortcomings of the purely functionalist approach to post hoc interpretability that seems to be predominant in most recent literature. (shrink)

This paper develops an account of metaphysical explanation according to which metaphysical explanations are answers to what-makes-it-the-case-that questions. On this view, metaphysical explanations are not to be considered entirely objective, but are subject to epistemic constraints imposed by the context in which a relevant question is asked. The resultant account of metaphysical explanation is developed independently of any particular views about grounding. Toward the end of the paper an application of the view is proposed that takes metaphysical explanations conceived in (...) this way to characterize reality's structure. According to this proposal, reality's structure is partly constituted by a projection of our explanatory practices onto reality. (shrink)

This paper develops and motivates a unification theory of metaphysical explanation, or as I will call it, Metaphysical Unificationism. The theory’s main inspiration is the unification account of scientific explanation, according to which explanatoriness is a holistic feature of theories that derive a large number of explananda from a meager set of explanantia, using a small number of argument patterns. In developing Metaphysical Unificationism, I will point out that it has a number of interesting consequences. The view offers a novel (...) conception of metaphysical explanation that doesn’t rely on the notion of a “determinative” or “explanatory” relation; it allows us to draw a principled distinction between metaphysical and scientific explanations; it implies that naturalness and fundamentality are distinct but intimately related notions; and perhaps most importantly, it re-establishes the unduly neglected link between explanation and understanding in the metaphysical realm. A number of objections can be raised against the view, but I will argue that none of these is conclusive. The upshot is that Metaphysical Unificationism provides a powerful and hitherto overlooked alternative to extant theories of metaphysical explanation. (shrink)

ABSTRACT: According to a traditional account, understanding why X occurred is equivalent to knowing that X was caused by Y. This paper defends the account against a major objection, viz., knowing-that is not sufficient for understanding-why, for understanding-why requires a kind of grasp while knowledge-that does not. I discuss two accounts of grasp in recent literature and argue that if either is true, then knowing that X was caused by Y entails at least a rudimentary understanding of why X occurred. (...) If my defense is successful, it would cast doubt on an influential account of the epistemic value of understanding. (shrink)

Can mathematics contribute to our understanding of physical phenomena? One way to try to answer this question is by getting involved in the recent philosophical dispute about the existence of mathematical explanations of physical phenomena. If there is such a thing, given the relation between explanation and understanding, we can say that there is an affirmative answer to our question. But what if we do not agree that mathematics can play an explanatory role in science? Can we still consider that (...) the above question can have an affirmative answer? My main aim here is to give an account that takes mathematics, in some of the cases discussed in the literature, as contributing to our understanding of physical phenomena despite not being explanatory. (shrink)

According to manipulationist accounts of causal explanation, to explain an event is to show how it could be changed by intervening on its cause. The relevant change must be a ‘serious possibility’ claims Woodward 2003, distinct from mere logical or physical possibility—approximating something I call ‘scientific possibility’. This idea creates significant difficulties: background knowledge is necessary for judgments of possibility. Yet the primary vehicles of explanation in manipulationism are ‘invariant’ generalisations, and these are not well adapted to encoding such knowledge, (...) especially in the social sciences, as some of it is non-causal. Ceteris paribus (CP) laws or generalisations labour under no such difficulty. A survey of research methods such as case and comparative studies, randomised control trials, ethnography, and structural equation modeling, suggests that it would be more difficult and in some instances impossible to try to represent the output of each method in invariant generalisations; and that this is because in each method causal and non-causal background knowledge mesh in a way that cannot easily be accounted for in manipulationist terms. Ceteris paribus-generalisations being superior in this regard, a theory of explanation based on the latter is a better fit for social science. (shrink)

I present an argument for the view that laws ground their instances. I then outline two important consequences that follow if we accept the conclusion of this argument. First, the claim that laws ground their instances threatens to undermine a prominent recent attempt to make sense of the explanatory power of Humean laws by distinguishing between metaphysical and scientific explanation. And second, the claim that laws ground their instances gives rise to a novel argument against the view that grounding relations (...) are metaphysically necessary. (shrink)

Explaining phenomena is a primary goal of science. Consequently, it is unsurprising that gaining a proper understanding of the nature of explanation is an important goal of science education. In order to properly understand explanation, however, it is not enough to simply consider theories of the nature of explanation. Properly understanding explanation requires grasping the relation between explanation and understanding, as well as how explanations can lead to scientific knowledge. This article examines the nature of explanation, its relation to understanding, (...) and how explanations are used to generate scientific knowledge via inferences to the best explanation. Studying these features and applications of explanation not only provides insight into a concept that is important for science education in its own right, but also sheds light on an aspect of recent debates concerning the so-called consensus view of nature of science (NOS). Once the relation between explanation, understanding, and knowledge is clear, it becomes apparent that science is unified in important ways. Seeing this unification provides some support for thinking that there are general features of NOS of the sort proposed by the consensus view and that teaching about these general features of NOS should be a goal of science education. (shrink)

Complex systems are to be seen as typically having multiple levels of organization. For instance, in the behavioural and cognitive sciences, there has been a long lasting trend, promoted by the seminal work of David Marr, putting focus on three distinct levels of analysis: the computational level, accounting for the What and Why issues, the algorithmic and the implementational levels specifying the How problem. However, the tremendous developments in neuroscience knowledge about processes at different scales of organization together with the (...) complexity of today cognitive theories suggest that there will hardly be only three levels of explanation. Instead, there will be many different degrees of commitments corresponding to the different granularities—from high-level (behavioural) models to low-level (neural and molecular) models of the cognitive research program. For instance, Bayesian approaches, that are usually advocated for formalizing Marr’s computational level and rational behaviour, have even been adopted to model synaptic plasticity and axon guidance by molecular gradients. As a result, we can consider the behavioural scientist as dealing with models at a multiplicity of levels. The purpose of this Research Topic in Frontiers in Theoretical and Philosophical Psychology is to promote an approach to the role of the levels and explanation and models which is of interest for cognitive scientists, neuroscientists, psychologists, behavioural scientists, and philosophers of science. (shrink)

Duncan Pritchard argues that a feature that sets understanding-why apart from knowledge-why is that whereas (I) understanding-why is a kind of cognitive achievement in a strong sense, (II) knowledge-why is not such a kind. I argue that (I) is false and that (II) is true. (I) is false because understanding-why featuring rudimentary explanations and understanding-why concerning very simple causal connections are not cognitive achievements in a strong sense. Knowledge-why is not a kind of cognitive achievement in a strong sense for (...) the same reason knowledge-that is not. The latter thesis requires showing that having (p because q) information is not equivalent to having information about facts or principles that establish the explanatory connections between the phenomena in question. I make a positive case for this claim and defend it against objections. Based on this argument, I identify an alternative feature that sets understanding-why apart from knowledge-why: The minimal condition for understanding-why and knowledge-why with respect to their contents is not identical. Knowing why p merely requires information that some explanatorily relevant dependency obtains. Understanding why p additionally requires information about facts or principles that establish the explanatory connections between the phenomena in question. (shrink)

Traditionally, a scientific model is thought to provide a good scientific explanation to the extent that it satisfies certain scientific goals that are thought to be constitutive of explanation. Problems arise when we realize that individual scientific models cannot simultaneously satisfy all the scientific goals typically associated with explanation. A given model’s ability to satisfy some goals must always come at the expense of satisfying others. This has resulted in philosophical disputes regarding which of these goals are in fact necessary (...) for explanation, and as such which types of models can and cannot provide explanations. Explanatory monists argue that one goal will be explanatory in all contexts, while explanatory pluralists argue that the goal will vary based on pragmatic considerations. In this paper, I argue that such debates are misguided, and that both monists and pluralists are incorrect. Instead of any goal being given explanatory priority over others in a given context, the different goals are all deeply dependent on one another for their explanatory power. Any model that sacrifices some explanatory goals to attain others will always necessarily undermine its own explanatory power in the process. And so when forced to choose between individual scientific models, there can be no explanatory victors. Given that no model can satisfy all the goals typically associated with explanation, no one model in isolation can provide a good scientific explanation. Instead we must appeal to collections of models. Collections of models provide an explanation when they satisfy the web of interconnected goals that justify the explanatory power of one another. (shrink)

Many think that sentences about what metaphysically explains what are true iff there exist grounding relations. This suggests that sceptics about grounding should be error theorists about metaphysical explanation. We think there is a better option: a theory of metaphysical explanation which offers truth conditions for claims about what metaphysically explains what that are not couched in terms of grounding relations, but are instead couched in terms of, inter alia, psychological facts. We do not argue that our account is superior (...) to grounding-based accounts. Rather, we offer it to those already ill-disposed towards grounding. (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)

Explanatory realism is the position that all explanations give information about whatever metaphysically determines the explanandum. This view is popular and plays a central role in metaphysics, but in this paper I argue that explanatory realism is false. In Sect. 1 I introduce explanatory realism in its weak and strong versions, and discuss the argumentative work that explanatory realism is used for in contemporary metaphysics. In Sect. 2 I present a series of problem cases for explanatory realism, including explanation by (...) analogy, explanations involving rules, reduction ad absurdum explanations and certain statistical explanations. In Sect. 3 I consider and reject two modified versions of explanatory realism: the position that explanatory realism is true only of explanation in metaphysics, and the position that determinative explanation is the most complete form of explanation. In conclusion I consider explanatory antirealism and explanatory pluralism as alternatives to explanatory realism. (shrink)

In recent years, metaphysics has undergone what some describe as a revolution: it has become standard to understand a vast array of questions as questions about grounding, a metaphysical notion of determination. Why should we believe in grounding, though? Supporters of the revolution often gesture at what I call the Argument from Explanatoriness: the notion of grounding is somehow indispensable to a metaphysical type of explanation. I challenge this argument and along the way develop a “reactionary” view, according to which (...) there is no interesting sense in which the notion of grounding is explanatorily indispensable. I begin with a distinction between two conceptions of grounding, a distinction which extant critiques of the revolution have usually failed to take into consideration: grounding qua that which underlies metaphysical explanation and grounding qua metaphysical explanation itself. Accordingly, I distinguish between two versions of the Argument from Explanatoriness: the Unexplained Explanations Version for the first conception of grounding, and the Expressive Power Version for the second. The paper’s conclusion is that no version of the Argument from Explanatoriness is successful. (shrink)

In this paper, I aim to provide access to the current debate on non-causal explanations in philosophy of science. I will first present examples of non-causal explanations in the sciences. Then, I will outline three alternative approaches to non-causal explanations – that is, causal reductionism, pluralism, and monism – and, corresponding to these three approaches, different strategies for distinguishing between causal and non-causal explanation. Finally, I will raise questions for future research on non-causal explanations.

Comparing different causes’ importance, and apportioning responsibility between them, requires making good sense of the notion of partial explanation, that is, of degree of explanation. How much is this subjective, how much objective? If the causes in question are probabilistic, how much is the outcome due to them and how much to simple chance? I formulate the notion of degree of causation, or effect size, relating it to influential recent work in the literature on causation. I examine to what extent (...) mainstream social science methods--both quantitative and qualitative--succeed in establishing effect sizes so understood. The answer turns out to be, roughly: only to some extent. Next, the standard understanding of effect size, even though widespread, still has several underappreciated consequences. I detail some of those. Finally, I discuss the separate issue of explanandum-dependence, which is essential to assessing any cause’s explanatory importance and yet which has been comparatively neglected. (shrink)

It is a pleasure for me to give this opening address to the Royal Institute of Philosophy Conference on ‘Explanation’ for two reasons. The first is that it is succeeded by exciting symposia and other papers concerned with various special aspects of the topic of explanation. The second is that the conference is being held in my old alma mater, the University of Glasgow, where I did my first degree. Especially due to C. A. Campbell and George Brown there was (...) in the Logic Department a big emphasis on absolute idealism, especially F. H. Bradley. My inclinations were to oppose this line of thought and to espouse the empiricism and realism of Russell, Broad and the like. Empiricism was represented in the department by D. R. Cousin, a modest man who published relatively little, but who was of quite extraordinary philosophical acumen and lucidity, and by Miss M. J. Levett, whose translation of Plato's Theaetetus formed an important part of the philosophy syllabus. (shrink)

Explanatory contrastivists hold that we often explain phenomena of the form p rather than q. In this paper, I present a new, social‐epistemological model of contrastive explanation—accountabilism. Specifically, my view is inspired by social‐scientific research that treats explanations fundamentally as accounts; that is, communicative actions that restore one's social status when charged with questionable behaviour. After developing this model, I show how accountabilism provides a more comprehensive model of contrastive explanation than the causal models of contrastive explanation that are currently (...) en vogue. (shrink)

The three cardinal aims of science are prediction, control, and explanation; but the greatest of these is explanation. Also the most inscrutable: prediction aims at truth, and control at happiness, and insofar as we have some independent grasp of these notions, we can evaluate science’s strategies of prediction and control from the outside. Explanation, by contrast, aims at scientific understanding, a good intrinsic to science and therefore something that it seems we can only look to science itself to explicate.

The basic theory of scientific understanding presented in Sections 1–2 exploits three main ideas.First, that to understand a phenomenonP (for a given agent) is to be able to fitP into the cognitive background corpusC (of the agent).Second, that to fitP intoC is to connectP with parts ofC (via arguments in a very broad sense) such that the unification ofC increases.Third, that the cognitive changes involved in unification can be treated as sequences of shifts of phenomena inC. How the theory fits (...) typical examples of understanding and how it excludes spurious unifications is explained in detail. Section 3 gives a formal description of the structure of cognitive corpuses which contain descriptive as well as inferential components. The theory of unification is then refined in the light of so called puzzling phenomena, to enable important distinctions, such as that between consonant and dissonant understanding. In Section 4, the refined theory is applied to several examples, among them a case study of the development of the atomic model. The final part contains a classification of kinds of understanding and a discussion of the relation between understanding and explanation. (shrink)

RÉSUMÉ: Prenant comme point de départ un article récent de Neil Campbell, j'examine la question de savoir si la survenance psychophysique peut assurer la dépendance psychophysique. Mes thèses principales sont que contrairement à ce que croit Campbell, il n'est pas clair que Kim ait montré de manière convaincante que les formulations de la survenance psychophysique en termes de propriétés soient inadéquates pour expliquer la dépendance psychophysique; la pertinence des difficultés soulevées par Kim tient surtout à la conception que l'on se (...) fait, d'abord de la notion de dépendance qui est en jeu, puis d'autres notions également, comme celle d'explication; pour quelqu'un qui est convaincu par les problèmes de Kim, il n'est pas clair—contrairement à ce que suggère Campbell—que le passage d'une survenance au niveau des propriétés à une survenance au niveau des prédicats, comme celle de Davidson, puisse être d'une quelconque utilité; donc ce qui importe à notre problème n'est pas de savoir si nous avons affaire à une survenance au niveau des propriétés ou à une survenance au niveau des prédicats, mais c'est plutôt la façon dont on conçoit la notion de dépendance dans ce contexte, et d'autres notions telles que celle d'explication. (shrink)