This essay analyzes and develops recent views about explanation in biology. Philosophers of biology have parted with the received deductive-nomological model of scientific explanation primarily by attempting to capture actual biological theorizing and practice. This includes an endorsement of different kinds of explanation (e.g., mathematical and causal-mechanistic), a joint study of discovery and explanation, and an abandonment of models of theory reduction in favor of accounts of explanatory reduction. Of particular current interest are philosophical accounts of complex explanations that appeal (...) to different levels of organismal organization and use contributions from different biological disciplines. The essay lays out one model that views explanatory integration across different disciplines as being structured by scientific problems. I emphasize the philosophical need to take the explanatory aims pursued by different groups of scientists into account, as explanatory aims determine whether different explanations are competing or complementary and govern the dynamics of scientific practice, including interdisciplinary research. I distinguish different kinds of pluralism that philosophers have endorsed in the context of explanation in biology, and draw several implications for science education, especially the need to teach science as an interdisciplinary and dynamic practice guided by scientific problems and explanatory aims. (shrink)

This chapter explores the idea that causal inference is warranted if and only if the mechanism underlying the inferred causal association is identified. This mechanistic stance is discernible in the epidemiological literature, and in the strategies adopted by epidemiologists seeking to establish causal hypotheses. But the exact opposite methodology is also discernible, the black box stance, which asserts that epidemiologists can and should make causal inferences on the basis of their evidence, without worrying about the mechanisms that might underlie their (...) hypotheses. I argue that the mechanistic stance is indeed a bad methodology for causal inference. However, I detach and defend a mechanistic interpretation of causal generalisations in epidemiology as existence claims about underlying mechanisms. (shrink)

This paper presents an attempt to integrate theories of causal processes—of the kind developed by Wesley Salmon and Phil Dowe—into a theory of causal models using Bayesian networks. We suggest that arcs in causal models must correspond to possible causal processes. Moreover, we suggest that when processes are rendered physically impossible by what occurs on distinct paths, the original model must be restricted by removing the relevant arc. These two techniques suffice to explain cases of late preëmption and other cases (...) that have proved problematic for causal models. (shrink)

During the past decade, social mechanisms and mechanism-based ex- planations have received considerable attention in the social sciences as well as in the philosophy of science. This article critically reviews the most important philosophical and social science contributions to the mechanism approach. The first part discusses the idea of mechanism- based explanation from the point of view of philosophy of science and relates it to causation and to the covering-law account of explanation. The second part focuses on how the idea (...) of mechanisms has been used in the social sciences. The final part discusses recent developments in analytical sociology, covering the nature of sociological explananda, the role of theory of action in mechanism-based explanations, Merton’s idea of middle-range theory, and the role of agent-based simulations in the development of mechanism-based explanations. (shrink)

For an Aristotelian observer, the halo is a puzzling phenomenon since it is apparently sublunary, and yet perfectly circular. This paper studies Aristotle's explanation of the halo in Meteorology III 2-3 as an optical illusion, as opposed to a substantial thing (like a cloud), as was thought by his predecessors and even many successors. Aristotle's explanation follows the method of explanation of the Posterior Analytics for "subordinate" or "mixed" mathematical-physical sciences. The accompanying diagram described by Aristotle is one of the (...) earliest lettered geometrical diagrams, in particular of a terrestrial phenomenon, and versions of it can still be found in modern textbooks on meteorological optics. (shrink)

Debates about explanation in the social sciences often proceed without any clear idea what an 'account' of explanation should do. In this paper I take a stance - what I will call contextualism - that denies there are purely formal and conceptual constraints on explanation and takes standards of explanation to be substantive empirical claims, paradigmatically claims about causation. I then use this standpoint to argue for position on issues in the philosophy of social science concerning reduction, idealized models, social (...) mechanisms, functional explanations, inference to the best explanation and interpretive understanding. (shrink)

In this essay, I address a novel criticism recently levelled at the Strong Programme by Nick Tosh and Tim Lewens. Tosh and Lewens paint Strong Programme theorists as trading on a contrastive form of explanation. With this, they throw valuable new light on the explanatory methods employed by the Strong Programme. However, as I shall argue, Tosh and Lewens run into trouble when they accuse Strong Programme theorists of unduly restricting the contrast space in which legitimate historical and sociological explanations (...) of scientific knowledge might be given. Their attack founders as a result of their failure to properly understand the overall methodological concerns of Strong Programme theorists. After introducing readers to the technique of contrastive explanation and correcting the errors in Tosh and Lewens’ interpretation of the Strong Programme, I argue that it is, in fact, Tosh and Lewens’ own commitment to scientific realism which places an unacceptable restriction on the explanatory space open to historians and sociologists of science. The happy ending is that the Strong Programme provides more freedom for analysis than does scientific realism, and that careful attention to the methodological benefits of contrastive explanation can help lighten the burden on historians and sociologists of science as they go about their explanatory business. (shrink)

Explanation and understanding Content Type Journal Article Pages 29-38 DOI 10.1007/s13194-010-0002-6 Authors Angela Potochnik, University of Cincinnati, P.O. Box 210374, Cincinnati, OH 45221-0374, USA Journal European Journal for Philosophy of Science Online ISSN 1879-4920 Print ISSN 1879-4912 Journal Volume Volume 1 Journal Issue Volume 1, Number 1.

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

Causal explanation proceeds by citing the causes of the explanandum. Any model of causal explanation requires a specification of the relation between cause and effect in virtue of which citing the cause explains the effect. In particular, it requires a specification of what it is for the explanandum to be causally dependent on the explanans and what types of things (broadly understood) the explanans are. There have been a number of such models. For the benefit of the unfamiliar reader, here (...) is a brief statement of some major views. On David Lewis’s account, c causally explains e if c is connected to e with a network of causal chains. For him, causal explanation consists in presenting portions of explanatory information captured by the causal network. On Wesley Salmon’s reading, c causally explains e if c is connected with e by a suitable continuous causal (i.e., capable of transmitting a mark) process. On the standard deductive-nomological reading of causal explanation, for c to causally explain e, c must be a nomologically sufficient condition for e. And for John Mackie, for c to causally explain e there must be event-types C and E such that C is an inus-condition for E.53 In a series of papers and a book, James Woodward (1997, 2000, 2002, 2003a, 2003b) has put forward a ‘manipulationist’ account of causal explanation. Briefly put, c causally explains e if e causally depends on c, where the notion of causal dependence is understood in terms of relevant (interventionist) counterfactual, that is counterfactuals that describe the outcomes of interventions. A bit more accurately, c causally explains e if, were c to be (actually or counterfactually) manipulated, e would change too. This model ties causal explanation to actual and counterfactual experiments that show how manipulation of factors mentioned in the explanans would alter the explanandum. It also stresses the role of invariant relationships, as opposed to strict laws, in causal explanation. Explanation in this model consists in answering a network of “what-if-things-had-been-different questions”, thereby placing the explanandum within a pattern of counterfactual dependencies (cf. Woodward 2003a, p.. (shrink)

Achieving understanding of nature is one of the aims of science. In this paper we offer an analysis of the nature of scientific understanding that accords with actual scientific practice and accommodates the historical diversity of conceptions of understanding. Its core idea is a general criterion for the intelligibility of scientific theories that is essentially contextual: which theories conform to this criterion depends on contextual factors, and can change in the course of time. Our analysis provides a general account of (...) how understanding is provided by scientific explanations of diverse types. In this way, it reconciles conflicting views of explanatory understanding, such as the causal-mechanical and the unificationist conceptions. (shrink)

Wesley Salmon is renowned for his seminal contributions to the philosophy of science. He has powerfully and permanently shaped discussion of such issues as lawlike and probabilistic explanation and the interrelation of explanatory notions to causal notions. This unique volume brings together twenty-six of his essays on subjects related to causality and explanation, written over the period 1971-1995. Six of the essays have never been published before and many others have only appeared in obscure venues. The volume includes a section (...) of accessible introductory pieces, as well as more advanced and technical pieces, and will make essential work in the philosophy of science readily available to both scholars and students. (shrink)

This paper discusses several distinct process theories of causality offered in recent years by Phil Dowe and me. It addresses problems concerning the explication of causal process, causal interaction, and causal transmission, whether given in terms of transmission of marks, transmission of invariant or conserved quantities, or mere possession of conserved quantities. Renouncing the mark-transmission and invariant quantity criteria, I accept a conserved quantity theory similar to Dowe's--differing basically with respect to causal transmission. This paper also responds to several fundamental (...) constructive criticisms contained in Christopher Hitchcock's discussion of both the mark-transmission and the conserved quantity theories. (shrink)

Approaches to explanation -- Causal and explanatory relevance -- The kairetic account of /D making -- The kairetic account of explanation -- Extending the kairetic account -- Event explanation and causal claims -- Regularity explanation -- Abstraction in regularity explanation -- Approaches to probabilistic explanation -- Kairetic explanation of frequencies -- Kairetic explanation of single outcomes -- Looking outward -- Looking inward.

The two major modern accounts of explanation are the causal and unification accounts. My aim in this paper is to provide a kind of unification of the causal and the unification accounts, by using the central technical apparatus of the unification account to solve a central problem faced by the causal account, namely, the problem of determining which parts of a causal network are explanatorily relevant to the occurrence of an explanandum. The end product of my investigation is a causal (...) account of explanation that has many of the advantages of the unification account. (shrink)

I give two arguments for the claim that all events which occur at the actual world and are such that they could be caused, are also such that they must actually be caused. The first argument is an improvement of a similar argument advanced by Alexander Pruss, which I show to be invalid. It uses Pruss’s Brouwer Analog for counterfactual logic, and, as a consequence, implies inconsistency with Lewis’s semantics for counterfactuals. While (I suggest) this consequence may not be objectionable, (...) the argument founders on the fact that Pruss’s Brouwer Analog has a clear counterexample. I thus turn to a second, “Lewisian” argument, which requires only an affirmation of one element of Lewis’s analysis of causation and one other, fairly weak possibility claim about the nature of wholly contingent events. The final section of the paper explains how both arguments escape objections from supposed indeterminacy in quantum physics. (shrink)

Pluralism with respect to the structure of explanations of facts is not uncommon. Wesley Salmon, for instance, distinguished two types of explanation: causal explanations (which provide insight in the causes of the fact we want to explain) and unification explanations (which fit the explanandum into a unified world view). The pluralism which Salmon and others have defended is compatible with several positions about the exact relation between these two types of explanations. We distinguish four such positions, and argue in favour (...) of one of them. We also compare our results with the views of some authors who have recently written on this subject. (shrink)

I defend an account of explanatory depth according to which explanations in the non-fundamental sciences can be deeper than explanations in fundamental physics.

The concept of causation plays a central role in many philosophical theories, and yet no account of causation has gained widespread acceptance among those who have investigated its foundations. Theories based on laws, counterfactuals, physical processes, and probabilistic dependence and independence relations (the list is by no means exhaustive) have all received detailed treatment in recent years—and, while no account has been entirely successful, it is generally agreed that the concept has been greatly clarified by the attempts. In this magnificent (...) book, Woodward aims to give a unified account of causation and causal explanation in terms of the notion of a manipulation (or intervention, terms which can be read interchangeably). Not only does he produce in my view the most illuminating and comprehensive account of causation on offer, his theory also opens a great many avenues for future work in the area, and has ramifications for many other areas of philosophy. Making Things Happen ought to be of interest not only to philosophers of causation and philosophers of science, but to any philosopher whose concerns involve assumptions about the nature of causation, laws, or explanation. (shrink)

This paper is an attempt to further our understanding of mechanisms conceived of as ontologically separable from laws. What opportunities are there for a mechanistic perspective to be independent of, or even more fundamental than, a law perspective? Advocates of the mechanistic view often play with the possibility of internal and external reliability, or with the paralleling possibilities of enforcing, counteracting, redirecting, etc., the mechanisms’ power to produce To further this discussion I adopt a trope ontology. It is independent of (...) the notion of law, and can easily be adapted to account for such characteristics of mechanisms. The idea of tropes as mechanisms is worked out in some detail. According to the resulting picture, there is still an opportunity to link mechanisms and laws. But while the predominant law view conceives of mechanistic approaches as special kinds of law accounts, this study indicates that the converse may be true. Law accounts are special cases of mechanistic accounts, and they work only in those worlds where the mechanisms are of the right kind. (shrink)

Comparisons of rival explanations or theories often involve vague appeals to explanatory power. In this paper, we dissect this metaphor by distinguishing between different dimensions of the goodness of an explanation: non-sensitivity, cognitive salience, precision, factual accuracy and degree of integration. These dimensions are partially independent and often come into conflict. Our main contribution is to go beyond simple stipulation or description by explicating why these factors are taken to be explanatory virtues. We accomplish this by using the contrastive-counterfactual approach (...) to explanation and the view of understanding as an inferential ability. By combining these perspectives, we show how the explanatory power of an explanation in a given dimension can be assessed by showing the range of answers it provides to what-if-things-had-been-different questions and the theoretical and pragmatic importance of these questions. Our account also explains intuitions linking explanation to unification or to exhibition of a mechanism. (shrink)

This paper discusses the important paper by Paul Thagard on the pathway version of mechanistic explanation that is currently used in chemical explanation. The author claims that this method of explanation has a respectable pedigree and can be traced back to the Chemical Revolution in the arguments used by the Lavoisier School in their theoretical duels with Richard Kirwan, the proponent of a revised phlogistonian theory. Kirwan believed that complex chemical reactions could be explained by recourse to affinity tables that (...) catalogued the attraction that various simple bodies possessed towards each other. To explain was in effect to make a delayed prediction, it is not enough just to show how a phenomenon fits into the discernible patterns of the world. Lavoisier, Fourcroy and their colleagues used pathway reasoning, although disguising this fact by suggesting that affinities varied when subjected to n-body situations. (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)

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)

This essay analyzes and develops recent views about explanation in biology. Philosophers of biology have parted with the received deductive-nomological model of scientific explanation primarily by attempting to capture actual biological theorizing and practice. This includes an endorsement of different kinds of explanation (e.g., mathematical and causal-mechanistic), a joint study of discovery and explanation, and an abandonment of models of theory reduction in favor of accounts of explanatory reduction. Of particular current interest are philosophical accounts of complex explanations that appeal (...) to different levels of organismal organization and use contributions from different biological disciplines. The essay lays out one model that views explanatory integration across different disciplines as being structured by scientific problems. I emphasize the philosophical need to take the explanatory aims pursued by different groups of scientists into account, as explanatory aims determine whether different explanations are competing or complementary and govern the dynamics of scientific practice, including interdisciplinary research. I distinguish different kinds of pluralism that philosophers have endorsed in the context of explanation in biology, and draw several implications for science education, especially the need to teach science as an interdisciplinary and dynamic practice guided by scientific problems and explanatory aims. (shrink)

Introduction: Science and Common Sense Long before the beginnings of modern civilization, men ac- quired vast funds of information about their environment. ...

In this paper an attempt is made at developing the notion of a real and complete empirical explanation as excluding all forms of potential or incomplete explanations. This explanation is, however, no longer conceived as the proper aim of empirical science, for it can certainly be gleaned from recent epistemological publications that no comprehensive notion of a real and complete scientific explanation is likely to be constructed from within empirical science. Contrary to common understanding the empirical explanation, deductive-nomological as well (...) as statistical explanation, is considered here only as motive of scientific activities, i.e., as common aim of a transcending cooperation of scientific and non-scientific social practice. Following from this the proper aim of empirical science now consists in the development of practically relevant explanatory theories.This redetermination of the aim of scientific activities of empirical science also means criticism of the unification of deductive-nomological and statistical explanations, as it has been proposed by Wolfgang Stegmüller in his pragmatisch-epistemische Wende. For both forms of empirical explanation must be referred to fundamentally different kinds of practical relevance, the former playing a more important role in the advancement of social practice. Stegmüller's development of a comprehensive probabilistic notion of empirical explanation, as tied up to pragmatic knowledge-situations, in a way already transcends a scientifically immanent determination of it, but he seems to have stopped halfway on the road to practically relevant empirical explanations. Several insufficiencies with his probabilistic notion of empirical explanation are shown up in this paper as a consequence of his abiding by pragmatic, and not penetrating to practical, knowledge-situations. The final result of it, however, consists in a clarification and a modification of the concept of deductive-nomological explanation, originally developed by Hempel and Oppenheim. (shrink)

It is often argued (as by Hempel and Nagel) that genuine historical explanations — if these are to be had — must exhibit a connection between events to be explained and universal or probabilistic laws (or 'hypotheses'). This connection may take either a 'strong' or 'weak' form. The historian may show that a statement of the event to be explained is a logical consequence of statements of reasonably well-confirmed universal laws and occurrences linked by the laws to the event to (...) be explained. Or the historian may show that a statement of the event to be explained has high inductive probability conferred upon it given statements of reasonably well-confirmed probabilistic laws and occurrences so linked by the laws to the type of event to be explained that one finds the occurrence of the particular event likely. This essay focuses on 'strong' explanations which meet a 'deducibility' requirement (for reasons given in the body of the article). It is argued that explanations in history (at least where it is plausible to construe them as 'non-rational') may meet a 'deducibility' requirement and count as genuine historical explanations although they do not meet a 'covering law' requirement (i. e. none of the premises of these explanations state universal or probabilistic hypotheses). It is required, however, that at least one premise in such explanations assert a reasonably well-confirmed condition (e. g., a co-variation) which can be taken as a sign or indication of the presence of laws. Rather than appealing to laws, the historian may appeal to the well-founded possibility of laws. (shrink)

We revive the idea that a deductive-nomological explanation of a scientific theory by its successor may be defensible, even in those common and troublesome cases where the theories concerned are mutually incompatible; and limiting, approximating and counterfactual assumptions may be required in order to define a logical relation between them. Our solution is based on a general characterization of limiting relations between physical theories using the method of nonstandard analysis.

It has been the dominant view that probabilistic explanations of particular facts must be inductive in character. I argue here that this view is mistaken, and that the aim of probabilistic explanation is not to demonstrate that the explanandum fact was nomically expectable, but to give an account of the chance mechanism(s) responsible for it. To this end, a deductive-nomological model of probabilistic explanation is developed and defended. Such a model has application only when the probabilities occurring in covering laws (...) can be interpreted as measures of objective chance, expressing the strength of physical propensities. Unlike inductive models of probabilistic explanation, this deductive model stands in no need of troublesome requirements of maximal specificity or epistemic relativization. (shrink)

In this paper, I discuss the key role played by Carl G. Hempel's work on theoretical realism and scientific explanation in effecting a crucial philosophical transition between the beginning and the end of the twentieth century. At the beginning of the century, the dominant view was that science is incapable of furnishing explanations of natural phenomena; at the end, explanation is widely viewed as an important, if not the primary, goal of science. In addition to its intellectual benefits, this transition (...) has important practical consequences with respect to dealing with the global problems humans everywhere will face in the twenty-first century. (shrink)

Carl G. Hempel has often stated that inductive-statistical explanations, as he conceives them, are inductive arguments. This discussion note raises the question of whether such arguments are to be understood as (1) arguments of the traditional sort, containing premises and conclusions, governed by some sort of inductive "acceptance rules," or (2) something more closely akin to Carnap's degree of confirmation statements which occur in an inductive logic which entirely eschews inductive "acceptance rules." Hempel's writings do not seem unequivocal on this (...) issue. It is suggested that adoption of construal (2) would remove the need for Hempel's high probability requirement on I-S explanations. (shrink)

Carl G. Hempel's doctrine of essential epistemic relativization of inductive-statistical explanation seems to entail the unintelligibility of the notion of objective homogeneity of reference classes. This discussion note explores the question of whether, as a consequence, essential epistemic relativization also entails the unintelligibility of the doctrine of indeterminism.

Using Coffa's paper as a point of departure, this brief note is designed to show that Hempel's inductive-statistical model of explanation implicitly construes explanations of that type as defective deductive-nomological explanations, with the consequence that there is no such thing as genuine inductive-statistical explanation according to Hempel's account. This result suggests a possible implicit commitment to determinism behind Hempel's theory of scientific explanation.

The present paper first shows that the validity of deductive-nomological (D-N) explanations (systematizations) depends in general on the interpretation context of the predicates involved in the explanation. Therefore, no logical-semantical model can be adequate. This problem is solved by relativisation of the validity criteria on both the confirmation context and the definition context of the premisses. Based upon this, a logical-pragmatical model of D-N explanation is developed. Thereby, especially explanations of laws and global explanations are taken into consideration, since these (...) can be regarded as prototypes of scientific explanation. (shrink)

Nagel’s official model of theory-reduction and the way it is represented in the literature are shown to be incompatible with the careful remarks on the notion of reduction Nagel gave while developing his model. Based on these remarks, an alternative model is outlined which does not face some of the problems the official model faces. Taking the context in which Nagel developed his model into account, it is shown that the way Nagel shaped his model and, thus, its well-known deficiencies, (...) are best conceived of as a mere by-product of his philosophical background. (shrink)

I defend an account of explanatory depth according to which explanations in the non-fundamental sciences can be deeper than explanations in fundamental physics.

This paper is an attempt to further our understanding of mechanisms conceived of as ontologically separable from laws. What opportunities are there for a mechanistic perspective to be independent of, or even more fundamental than, a law perspective? Advocates of the mechanistic view often play with the possibility of internal and external reliability, or with the paralleling possibilities of enforcing, counteracting, redirecting, etc., the mechanisms’ power to produce To further this discussion I adopt a trope ontology. It is independent of (...) the notion of law, and can easily be adapted to account for such characteristics of mechanisms. The idea of tropes as mechanisms is worked out in some detail. According to the resulting picture, there is still an opportunity to link mechanisms and laws. But while the predominant law view conceives of mechanistic approaches as special kinds of law accounts, this study indicates that the converse may be true. Law accounts are special cases of mechanistic accounts, and they work only in those worlds where the mechanisms are of the right kind. (shrink)

Explanations contribute to our understanding of the world byembedding phenomena into general nomic patterns that we recognize in the world. Manyof these patterns are, of course, causal ones, but the declaration as ``causal'' often fails to determinethe explanatory power of the pattern. More important is the systematization capacity and the empiricalcontent of the pattern or theory with respect to explanations. We can specify these parameters moreprecisely within the framework of the structuralist view of theories.

There is more than one explanation for the evolution of sexual reproduction. This paper investigates the possibility that this pluralism exists because these different explanations rely on intuitions provided by different philosophical theories of explanation, namely unifying views and causal mechanical views. I conclude that this is not the case.

Kitcher's unification theory of explanation seems to suggest that only the most reductive accounts can legitimately be termed explanatory. This is not what we find in actual scientific practice. In this paper, I attempt to reconcile these ideas. I claim that Kitcher's theory picks out ideal explanations, but that our term explanation is used to cover other accounts that have a certain relationship with the ideal accounts. At times, versions and portions of ideal explanations can also be considered explanatory.

Most scientists and philosophers of science recognize that, when it comes to accepting and rejecting theories in science, considerations that have to do with simplicity, unity, symmetry, elegance, beauty or explanatory power have an important role to play, in addition to empirical considerations. Until recently, however, no one has been able to give a satisfactory account of what simplicity (etc.) is, or how giving preference to simple theories is to be justified. But in the last few years, two different but (...) related accounts have appeared, both of which address the above issues. On the one hand, James McAllister has argued that aesthetic criteria in science reflect scientists' judgements about what kind of theory is most likely to be empirically successful, based on the relative empirical success and failure of different kinds of theories in the past. Scientists employ what McAllister dubs "the aesthetic induction". On the other hand, I have argued that we need to see science as making a hierarchy of metaphysical assumptions about the comprehensibility and knowability of the universe, these assumptions asserting less and less as one ascends the hierarchy. One of the more substantial of these assumptions is that the universe is physically comprehensible. The key non-empirical feature a body of fundamental theories in physics must possess to be acceptable is unity. The better such a body of theory exemplifies the metaphysical thesis that the universe is physically comprehensible, in the sense that it has a unified dynamic structure, so the more acceptable such a body of theory is, from this standpoint. This affects not just theoretical physics, but the whole of natural science. In this paper I compare and contrast, and try to assess impartially the relative merits of, these two views. (shrink)

A scientific theory, in order to be accepted as a part of theoretical scientific knowledge, must satisfy both empirical and non-empirical requirements, the latter having to do with simplicity, unity, explanatory character, symmetry, beauty. No satisfactory, generally accepted account of such non-empirical requirements has so far been given. Here, a proposal is put forward which, it is claimed, makes a contribution towards solving the problem. This proposal concerns unity of physical theory. In order to satisfy the non-empirical requirement of unity, (...) a physical theory must be such that the same laws govern all possible phenomena to which the theory applies. Eight increasingly demanding versions of this requirement are distinguished. Some implications for other non-empirical requirements, and for our understanding of science are indicated. (shrink)

An important part of the mind-brain problem arises because sentience and consciousness seem inherently resistant to scientific explanation and understanding. The solution to this dilemma is to recognize, first, that scientific explanation can only render comprehensible a selected aspect of what there is, and second, that there is a mode of explanation and understanding, the personalistic, quite different from, but just as viable as, scientific explanation. In order to understand the mental aspect of brain processes - that aspect we know (...) about as a result of having relevant neurological processes occur in our own brain - we need to avail ourselves of personalistic explanation, irreducible to scientific explanation. The problem of explaining and understanding why experiential or mental aspects of brain processes or things should be correlated with certain physical processes, things or states of affairs is a non-problem because there is no kind of explanation possible in terms of which an explanation could be couched. A physical theory, amplified to include the experiential, might be predictive but would, necessarily, cease to be explanatory; and an amplified personalistic explanation could not succeed either. There is, in short, an explanation as to why there cannot be an explanation of correlations between physical and mental aspects of processes going on inside our heads. (shrink)

This paper represents a response to the criticisms made by Eric Barnes in “Explanatory Unification and the Problem of Asymmetry” and “Explanatory Unification and Scientific Understanding” against the thesis of Explanatory Unification. This paper responds to Barnes‟ two main criticisms, that of derivational skepticism and causal asymmetry, and successfully refutes his objections. This paper also defends the plausibility of the unificationist account of scientific explanation because of its ability to render coherent the notion of scientific understanding, focusing in particular on (...) the work by Michael Friedman and Philip Kitcher. (shrink)

Achieving understanding of nature is one of the aims of science. In this paper we offer an analysis of the nature of scientific understanding that accords with actual scientific practice and accommodates the historical diversity of conceptions of understanding. Its core idea is a general criterion for the intelligibility of scientific theories that is essentially contextual: which theories conform to this criterion depends on contextual factors, and can change in the course of time. Our analysis provides a general account of (...) how understanding is provided by scientific explanations of diverse types. In this way, it reconciles conflicting views of explanatory understanding, such as the causal-mechanical and the unificationist conceptions. (shrink)

Philip Kitcher's account of scientific progress incorporates a conception of explanatory unification that invites the so-called 'obsessive unifier' worry, to wit, that in our drive to unify the phenomena we might impose artificial structure on the world and consequently produce an incorrect view of how things, in fact, are. I argue that Kitcher's attempt to address this worry is unsatisfactory because it relies on an ability to choose between rival patterns of explanation which itself rests on the relevant choice having (...) already been made. I also suggest a way of answering the worry that Kitcher is not likely to endorse. (shrink)

The two major modern accounts of explanation are the causal and unification accounts. My aim in this paper is to provide a kind of unification of the causal and the unification accounts, by using the central technical apparatus of the unification account to solve a central problem faced by the causal account, namely, the problem of determining which parts of a causal network are explanatorily relevant to the occurrence of an explanandum. The end product of my investigation is a causal (...) account of explanation that has many of the advantages of the unification account. (shrink)

Pluralism with respect to the structure of explanations of facts is not uncommon. Wesley Salmon, for instance, distinguished two types of explanation: causal explanations (which provide insight in the causes of the fact we want to explain) and unification explanations (which fit the explanandum into a unified world view). The pluralism which Salmon and others have defended is compatible with several positions about the exact relation between these two types of explanations. We distinguish four such positions, and argue in favour (...) of one of them. We also compare our results with the views of some authors who have recently written on this subject. (shrink)

Interpretation in science has gained little attention in the past because philosophers of science believed that interpretation belongs to the context of discovery or must be associated with meaning. But scientists often speak about interpretation when they report their findings. Elsewhere I have argue in favour of a pragmatic-rhetorical theory of explanation, and it is in light of this theory that I suggest we can understand interpretation in the natural sciences.

In this paper I defend the idea that there is a sense in which it is meaningful and useful to talk about objective understanding, and that to characterize that notion it is necessary to formulate an account of explanation that makes reference to the beliefs and epistemic goals of the participants in a cognitive enterprise. Using the framework for belief revision developed by Isaac Levi, I analyze the conditions that information must fulfill to be both potentially explanatory and epistemically (...) valuable to an inquiring agent and to a scientific community. To be potentially explanatory, the information must state the relations of probabilistic relevance that the explanans bares to the explanandum. But a potential explanation con only be a bona fide explanation if it becomes part of inquiry, that is, if an agent or a group of agents can see any value in it for their cognitive purposes. I provide a way to evaluate the epistemic value of a potential explanation as a function of its credibility and its informational content. (shrink)

Both von Neumann and Wiener were outsiders to biology. Both were inspired by biology and both proposed models and generalizations that proved inspirational for biologists. Around the same time in the 1940s von Neumann developed the notion of self reproducing automata and Wiener suggested an explication of teleology using the notion of negative feedback. These efforts were similar in spirit. Both von Neumann and Wiener used mathematical ideas to attack foundational issues in biology, and the concepts they articulated had lasting (...) effect. But there were significant differences as well. Von Neumann presented a how-possibly model, which sparked interest by mathematicians and computer scientists, while Wiener collaborated more directly with biologists, and his proposal influenced the philosophy of biology. The two cases illustrate different strategies by which mathematicians, the “professional outsiders” of science, can choose to guide their engagement with biological questions and with the biological community, and illustrate different kinds of generalizations that mathematization can contribute to biology. The different strategies employed by von Neumann and Wiener and the types of models they constructed may have affected the fate of von Neumann’s and Wiener’s ideas – as well as the reputation, in biology, of von Neumann and Wiener themselves. (shrink)

Review of Peter Mc. Laughlin *What Functions Explain" (2001).

Does mathematics ever play an explanatory role in science? If so then this opens the way for scientific realists to argue for the existence of mathematical entities using inference to the best explanation. Elsewhere I have argued, using a case study involving the prime-numbered life cycles of periodical cicadas, that there are examples of indispensable mathematical explanations of purely physical phenomena. In this paper I respond to objections to this claim that have been made by various philosophers, and I discuss (...) potential future directions of research for each side in the debate over the existence of abstract mathematical objects. Introduction: Mathematical Explanation Indispensability and Explanation Is the Mathematics Indispensable to the Explanation? 3.1 Object-level arbitrariness 3.2 Concept-level arbitrariness 3.3 Theory-level arbitrariness Is the Explanandum ‘Purely Physical’? Is the Mathematics Explanatory in Its Own Right? Does Inference to the Best Explanation Apply to Mathematics? 6.1 Leng's first argument 6.2 Leng's second argument 6.3 Leng's third argument Conclusions CiteULike Connotea Del.icio.us What's this? (shrink)

Robert Batterman examines a form of scientific reasoning called asymptotic reasoning, arguing that it has important consequences for our understanding of the scientific process as a whole. He maintains that asymptotic reasoning is essential for explaining what physicists call universal behavior. With clarity and rigor, he simplifies complex questions about universal behavior, demonstrating a profound understanding of the underlying structures that ground them. This book introduces a valuable new method that is certain to fill explanatory gaps across disciplines.

This essay analyzes and develops recent views about explanation in biology. Philosophers of biology have parted with the received deductive-nomological model of scientific explanation primarily by attempting to capture actual biological theorizing and practice. This includes an endorsement of different kinds of explanation (e.g., mathematical and causal-mechanistic), a joint study of discovery and explanation, and an abandonment of models of theory reduction in favor of accounts of explanatory reduction. Of particular current interest are philosophical accounts of complex explanations that appeal (...) to different levels of organismal organization and use contributions from different biological disciplines. The essay lays out one model that views explanatory integration across different disciplines as being structured by scientific problems. I emphasize the philosophical need to take the explanatory aims pursued by different groups of scientists into account, as explanatory aims determine whether different explanations are competing or complementary and govern the dynamics of scientific practice, including interdisciplinary research. I distinguish different kinds of pluralism that philosophers have endorsed in the context of explanation in biology, and draw several implications for science education, especially the need to teach science as an interdisciplinary and dynamic practice guided by scientific problems and explanatory aims. (shrink)

Batterman ([2010]) raises a number of concerns for the inferential conception of the applicability of mathematics advocated by Bueno and Colyvan ([2011]). Here, we distinguish the various concerns, and indicate how they can be assuaged by paying attention to the nature of the mappings involved and emphasizing the significance of interpretation in this context. We also indicate how this conception can accommodate the examples that Batterman draws upon in his critique. Our conclusion is that ‘asymptotic reasoning’ can be straightforwardly accommodated (...) within the inferential conception. (shrink)

We defend Joseph Melia's thesis that the role of mathematics in scientific theory is to 'index' quantities, and that even if mathematics is indispensable to scientific explanations of concrete phenomena, it does not explain any of those phenomena. This thesis is defended against objections by Mark Colyvan and Alan Baker.

Reasoning under uncertainty, that is, making judgements with only partial knowledge, is a major theme in artificial intelligence. Professor Paris provides here an introduction to the mathematical foundations of the subject. It is suited for readers with some knowledge of undergraduate mathematics but is otherwise self-contained, collecting together the key results on the subject, and formalising within a unified framework the main contemporary approaches and assumptions. The author has concentrated on giving clear mathematical formulations, analyses, justifications and consequences of the (...) main theories about uncertain reasoning, so the book can serve as a textbook for beginners or as a starting point for further basic research into the subject. It will be welcomed by graduate students and research workers in logic, philosophy, and computer science as a textbook for beginners, a starting point for further basic research into the subject, and not least, an account of how mathematics and artificial intelligence can complement and enrich each other. (shrink)

How regular do mechanisms need to be, in order to count as mechanisms? This paper addresses two arguments for dropping the requirement of regularity from the definition of a mechanism, one motivated by examples from the sciences and the other motivated by metaphysical considerations regarding causation. I defend a broadened regularity requirement on mechanisms that takes the form of a taxonomy of kinds of regularity that mechanisms may exhibit. This taxonomy allows precise explication of the degree and location of regular (...) operation within a mechanism, and highlights the role that various kinds of regularity play in scientific explanation. I defend this regularity requirement in terms of regularity’s role in individuating mechanisms against a background of other causal processes, and by prioritizing mechanisms’ ability to serve as a model of scientific explanation, rather than as a metaphysical account of causation. It is because mechanisms are regular, in the expanded sense described here, that they are capable of supporting the kinds of generalizations that figure prominently in scientific explanations. (shrink)

This paper will examine the nature of mechanisms and the distinction between the relevant and irrelevant parts involved in a mechanism’s operation. I first consider Craver’s account of this distinction in his book on the nature of mechanisms, and explain some problems. I then offer a novel account of the distinction that appeals to some resources from Mackie’s theory of causation. I end by explaining how this account enables us to better understand what mechanisms are and their various features.

Not all models are explanatory. Some models are data summaries. Some models sketch explanations but leave crucial details unspecified or hidden behind filler terms. Some models are used to conjecture a how-possibly explanation without regard to whether it is a how-actually explanation. I use the Hodgkin and Huxley model of the action potential to illustrate these ways that models can be useful without explaining. I then use the subsequent development of the explanation of the action potential to show what is (...) required of an adequate mechanistic model. Mechanistic models are explanatory. (shrink)

There is more than one explanation for the evolution of sexual reproduction. This paper investigates the possibility that this pluralism exists because these different explanations rely on intuitions provided by different philosophical theories of explanation, namely unifying views and causal mechanical views. I conclude that this is not the case.

One of the main early forms of “functionalism,” developed by writers like Jerry Fodor and William Lycan, focused on “mechanistic” explanation in the special sciences and argued that “functional properties” in psychology were continuous in nature with the special science properties posited in such mechanistic explanations. I dub the latter position“Continuity Functionalism” and use it to critically examine the “Standard Picture” of the metaphysics of functionalism which takes “functional” properties to be second-order properties and claims there are two metaphysical forms (...) of “functionalism,” in so-called “role” and “realizer” functionalism. Looking at mechanistic explanations, I show that the “functional properties” posited in the special sciences are not second-order properties and that Continuity Functionalism is a distinctive metaphysical version of functionalism not covered by the Standard Picture. My conclusion is that the Standard Picture offers us a false dichotomy of ways to be a “functionalist” and that “functionalists” thus need to look once more to the special sciences to configure their views, thus eschewing the machinery inherited from “analytic” philosophers. (shrink)

During the past decade, social mechanisms and mechanism-based ex- planations have received considerable attention in the social sciences as well as in the philosophy of science. This article critically reviews the most important philosophical and social science contributions to the mechanism approach. The first part discusses the idea of mechanism- based explanation from the point of view of philosophy of science and relates it to causation and to the covering-law account of explanation. The second part focuses on how the idea (...) of mechanisms has been used in the social sciences. The final part discusses recent developments in analytical sociology, covering the nature of sociological explananda, the role of theory of action in mechanism-based explanations, Merton’s idea of middle-range theory, and the role of agent-based simulations in the development of mechanism-based explanations. (shrink)

Historically embryogenesis has been among the most philosophically intriguing phenomena. In this paper I focus on one aspect of biological development that was particularly perplexing to the ancients: self-organisation. For many ancients, the fact that an organism determines the important features of its own development required a special model for understanding how this was possible. This was especially true for Aristotle, Alexander, and Simplicius who all looked to contemporary technology to supply that model. However, they did not all agree on (...) what kind of device should be used. In this paper I explore the way these ancients made use of technology as a model for the developing embryo. However, my purpose here is more than just the historical interest of knowing which devices were used by whom and how each of them worked; I shall largely ignore the details of how the various devices actually worked. Instead I shall look at the use of technology from a philosophical perspective. As we shall see, the different choices of device reveal fundamental differences in the way each thinker understood the nature of biological development itself. Thus, the central aim of this paper is to examine, not who used what devices and how they worked, but why they used those particular devices and what they thought their functioning could tell us about the nature of embryological phenomena. (shrink)

Traditional accounts of explanation fail to illuminate the explanatory relevance of “models that are descriptively false” in the sense that the regularities they entail fail to obtain. In this paper, I propose an account of explanation, which I call ‘explanation by concretization’, that serves to explicate the explanatory relevance of such models. Starting from a highly abstract and idealized model, causal explanations of the absence of regularities are sought by adding complexity to the model or by concretizing it. Whether this (...) process is successful depends on whether the abstractions and idealizations in the basic model succeed in isolating a mechanism, i.e. in representing how it operates when interfering factors are absent. This account is developed in the context of economics and contrasted to those of Daniel Hausman and Nancy Cartwright. I go on to provide an account of how unrealistic models can be used for providing understanding of the way mechanisms work. (shrink)

Many of the arguments for neuroeconomics rely on mistaken assumptions about criteria of explanatory relevance across disciplinary boundaries and fail to distinguish between evidential and explanatory relevance. Building on recent philosophical work on mechanistic research programmes and the contrastive counterfactual theory of explanation, we argue that explaining an explanatory presupposition or providing a lower-level explanation does not necessarily constitute explanatory improvement. Neuroscientific findings have explanatory relevance only when they inform a causal and explanatory account of the psychology of human decision-making.

The concept of mechanism is analyzed in terms of entities and activities, organized such that they are productive of regular changes. Examples show how mechanisms work in neurobiology and molecular biology. Thinking in terms of mechanisms provides a new framework for addressing many traditional philosophical issues: causality, laws, explanation, reduction, and scientific change.

We provide an account of mechanistic representation and explanation that has several advantages over previous proposals. In our view, explaining mechanistically is not simply giving an explanation of a mechanism. Rather, an explanation is mechanistic because of particular relations that hold between a mechanical representation, or model, and the target of explanation. Under this interpretation, mechanistic explanation is possible even when the explanatory target is not a mechanism. We argue that taking this view is not only coherent and plausible, it (...) gives a more sophisticated view of the relationship between mechanical models and their targets. This allows us to address some ambiguities within the mechanist framework, and delivers a more intuitive way to interpret scientists' use of the term "mechanism". (shrink)

We sketch a framework for building a unified science of cognition. This unification is achieved by showing how functional analyses of cognitive capacities can be integrated with the multilevel mechanistic explanations of neural systems. The core idea is that functional analyses are sketches of mechanisms , in which some structural aspects of a mechanistic explanation are omitted. Once the missing aspects are filled in, a functional analysis turns into a full-blown mechanistic explanation. By this process, functional analyses are seamlessly integrated (...) with multilevel mechanistic explanations. (shrink)