Offering a new approach to scientific explanation, this book focuses initially on the explaining act itself.

Studdert-Kennedy, Gerald, Evidence and Explanation in Social Science. ... Kauffman, Stuart, "Articulation of Parts Explanation in Biology and the Rational ...

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)

Can religious premises ever be cited legitimately in explanations of matters of fact? Scientific practice is generally regarded as the source of our explanatory paradigms and the final arbiter of matters of fact, and is so constituted that it could never endorse such explanations. Neither would they be sanctioned by the non-cognitive reconstructions of religious discourse currently fashionable. I argue: Some scientific constraints on explanations, such as consistency, testability, and corrigibility, are generally legitimate in non-scientific contexts. Other cognitive values, such (...) as clarity and simplicity, though not constraints, still have adequate credentials to serve globally in the evaluation of theories and explanations. In addition to these, science employs overtly ideological constraints on explanation, plus a number of parochial values, including control, replicability, and skepticism. These serve to circumscribe the range of acceptable explanations more narrowly than reasonable standards of rationality would necessitate. In particular, they are responsible for precluding religious explanations unnecessarily. ;Finally, one can reconstruct from religious contexts a system of cognitive values with broad application that takes exception to scientific norms pertaining to the status of teleological explanations, the ranking of outstanding problem areas in importance, the usefulness of anecdotal material, and the appropriateness of pragmatic conceptions of truth. The additional explanations this value structure sanctions will be less secure than scientific explanations generally, and somewhat idiosyncratic. They may be appropriate when no scientific explanations are possible or available, or if the religious explanation is teleological and the scientific explanation is not. Near-death experiences represent a major potential source of religious explanations, although one in great need of development. More generally, our ability to give religious explanations is hampered by inadequate theoretical articulations of the concept of God. (shrink)

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)

The first part of this essay is basically historical. It introduces the explanation–understanding divide, focusing in particular on the general–unique distinction. The second part is more philosophical and it presents two different claims on action. In the first place, I will try to say what it means to understand an action. Secondly, we will focus on the explanation of action as it is seen in some explanatory sciences. I will try to argue that in some cases these sciences (...) commit what I call an “external contradiction”. (shrink)

Hill and Levine offer alternative explanations of these conceivabilities, concluding that these conceivabilities are thereby defeated as evidence. However, this strategy fails because their explanations generalize to all conceivability judgments concerning phenomenal states. Consequently, one could defend absolutely any theory of phenomenal states against conceivability arguments in just this way. This result conflicts with too many of our common sense beliefs about the evidential value of conceivability with respect to phenomenal states. The general moral is that the application of such (...) principles of explanatory defeat is neither simple nor straightforward. (shrink)

Recently, many philosophers have been inclined to ascribe mentality to animals on the main grounds that they possess certain complex computational abilities. In this paper I contend that this view is misleading, since it wrongly assumes that those computational abilities demand a psychological explanation. On the contrary, they can be just characterised from a computational level of explanation, which picks up a domain of computation and information processing that is common to many computing systems but is autonomous from (...) the domain of psychology. Thus, I propose that it is possible to conceive insects and other animals as mere computing agents, without having any commitment to ascribe mentality to them. I conclude by sketching a proposal about how to draw the line between mere computing and genuine mentality. (shrink)

Reduction has long been a favourite method of analysis in all areas of philosophy, but in recent years there has been a reaction against it. The contributors to this volume examine the motivations for such anti-reductionist views and assess their coherence and success in a number of fields.

From antiquity to the end of the twentieth century, philosophical discussions of understanding remained undeveloped, guided by a 'received view' that takes understanding to be nothing more than knowledge of an explanation. More recently, however, this received view has been criticized, and bold new philosophical proposals about understanding have emerged in its place. In this book, Kareem Khalifa argues that the received view should be revised but not abandoned. In doing so, he clarifies and answers the most central questions (...) in this burgeoning field of philosophical research: what kinds of cognitive abilities are involved in understanding? What is the relationship between the understanding that explanations provide and the understanding that experts have of broader subject matters? Can there be understanding without explanation? How can one understand something on the basis of falsehoods? Is understanding a species of knowledge? What is the value of understanding? (shrink)

A compelling idea holds that reality has a layered structure. We often disagree about what inhabits the bottom layer, but we agree that higher up we find chemical, biological, geological, psychological, sociological, economic, /etc./, entities: molecules, human beings, diamonds, mental states, cities, interest rates, and so on. How is this intuitive talk of a layered structure of entities to be understood? Traditionally, philosophers have proposed to understand layered structure in terms of either reduction or supervenience. But these traditional views face (...) well-known problems. A plausible alternative is that layered structure is to be explicated by appeal to explanations of a certain sort, termed / grounding explanations/. Grounding explanations tell us what obtains in virtue of what. Unfortunately, the use of grounding explanations to articulate the layered conception faces a problem, which I call /the collapse/. The collapse turns on the question of how to ground the facts stated by the explanations themselves. In this paper I make a suggestion about how to ground explanations that avoids the collapse. Briefly, the suggestion is that the fact stated by a grounding explanation is grounded in its /explanans/. (shrink)

Issues concerning scientific explanation have been a focus of philosophical attention from Pre- Socratic times through the modern period. However, recent discussion really begins with the development of the Deductive-Nomological (DN) model. This model has had many advocates (including Popper 1935, 1959, Braithwaite 1953, Gardiner, 1959, Nagel 1961) but unquestionably the most detailed and influential statement is due to Carl Hempel (Hempel 1942, 1965, and Hempel & Oppenheim 1948). These papers and the reaction to them have structured subsequent discussion (...) concerning scientific explanation to an extraordinary degree. After some general remarks by way of background and orientation (Section 1), this entry describes the DN model and its extensions, and then turns to some well-known objections (Section 2). It next describes a variety of subsequent attempts to develop alternative models of explanation, including Wesley Salmon's Statistical Relevance (Section 3) and Causal Mechanical (Section 4) models and the Unificationist models due to Michael Friedman and Philip Kitcher (Section 5). Section 6 provides a summary and discusses directions for future work. (shrink)

In this paper I present an internal difficulty for the hypothesis that mentalistic explanation is causal explanation. My thesis is that intuitively acceptable mentalistic explanations appear to violate constraints imposed by the mental causation hypothesis.

The ultimate source of explanation in biology is the principle of natural selection. Natural selection means differential reproduction of genes and gene combinations. It is a mechanistic process which accounts for the existence in living organisms of end-directed structures and processes. It is argued that teleological explanations in biology are not only acceptable but indeed indispensable. There are at least three categories of biological phenomena where teleological explanations are appropriate.

Emile Meyerson's writings on the philosophy of science are a rich source of ideas and information concerning many philosophical and historical aspects of the development of modem science. Meyerson's works are not widely read or cited today by philosophers or even philosophers of science, in part because they have long been out of print and are often not available even in research libraries. There are additional chevaux de!rise for all but the hardiest scholars: Meyerson's books are written in French (and (...) do not all exist in English versions) and deal with the subject matter of science - ideas or concepts, laws or principles, theories - and epis temological questions rather than today's more fashionable topics of the social matrix and external influences on science with the concomitant neglect of the intellectual content of science. Born in Lublin, Poland, in 1859, Meyerson received most of his education in Germany, where he studied from the age of 12 to 23, preparing himself for a career in chemistry.! He moved to Paris in 1882, where he began a career as an industrial chemist. Changing his profession, he then worked for a time as the foreign news editor of the HAVAS News Agency in Paris. In 1898 he joined the agency established by Edmond Rothschild that had as its purpose the settling of Jews in Palestine and became the Director of the Jewish Colonization Association for Europe and Asia Minor. These activities represent Meyerson's formal career. (shrink)

The theories of pre-existence and epigenesis are typically taken to be opposing theories of generation in the seventeenth and eighteenth centuries. One can be a pre-existence theorist only if one does not espouse epigenesis and vice versa. It has also been recognized, however, that the line between pre-existence and epigenesis in the nineteenth century, at least, is considerably less sharp and clear than it was in earlier centuries. The debate (1759-1777) between Albrecht von Haller and Caspar Friedrich Wolff on their (...) theories of generation is usually taken to be a debate between a pre-existence theorist and an epigeneticist, and the supposed fact that these two theories of generation are mutually exclusive explains (so the story goes) the divide between Haller and Wolff. However, it’s not clear that Haller endorsed an especially robust form of pre-existence, and nor is it clear that Wolff’s theory of generation -- once he considered it carefully -- is clear epigenetic. Rather, Haller’s theory of generation is marked by traces of epigensis and Wolff’s theory has elements of pre-existence theory. This is not to say that their theories of generation are basically the same, but the debate between the two ought not to be framed in terms of pre-existence versus epigenesis. Their points of difference must be explained in some other way. In this way, their controversy bears characteristics of similar disputes over generation in the nineteenth century more than it resembles those in the seventeenth century. In this paper, I argue that (a) Haller’s and Wolff’s theories both blend elements from pre-existence and epigenesis; (b) but there are still deeply-rooted differences between the two generation theories; (c) one source of these differences is that Haller and Wolff have divergent conceptions of what an adequate explanation is; (d) we can see that they have different conceptions of what constitutes an adequate explanation by paying heed to their evaluations of Descartes’ epistemology and methodology in his theory of generation (such as it is); and (e) this shows that one of the main differences between Haller’s generation theory and that of Wolff is the degree to which each thinks we need to (and indeed can) explain the nature of the causes -- both efficient and final -- at play during the formation of organic beings. (shrink)

Teleological explanations (TEs) account for the existence or properties of an entity in terms of a function: we have hearts because they pump blood, and telephones for communication. While many teleological explanations seem appropriate, others are clearly not warranted-for example, that rain exists for plants to grow. Five experiments explore the theoretical commitments that underlie teleological explanations. With the analysis of [Wright, L. (1976). Teleological Explanations. Berkeley, CA: University of California Press] from philosophy as a point of departure, we examine (...) in Experiment 1 whether teleological explanations are interpreted causally, and confirm that TEs are only accepted when the function invoked in the explanation played a causal role in bringing about what is being explained. However, we also find that playing a causal role is not sufficient for all participants to accept TEs. Experiment 2 shows that this is not because participants fail to appreciate the causal structure of the scenarios used as stimuli. In Experiments 3-5 we show that the additional requirement for TE acceptance is that the process by which the function played a causal role must be general in the sense of conforming to a predictable pattern. These findings motivate a proposal, Explanation for Export, which suggests that a psychological function of explanation is to highlight information likely to subserve future prediction and intervention. We relate our proposal to normative accounts of explanation from philosophy of science, as well as to claims from psychology and artificial intelligence. (shrink)

Normative explanations of why things are wrong, good, or unfair are ubiquitous in ordinary practice and normative theory. This paper argues that normative explanation is subject to a justification condition: a correct complete explanation of why a normative fact holds must identify features that would go at least some way towards justifying certain actions or attitudes. I first explain and motivate the condition I propose. I then support it by arguing that it fits well with various theories of (...) normative reasons, makes good sense of certain legitimate moves in ordinary normative explanatory discourse, and helps to make sense of our judgments about explanatory priority in certain cases of normative explanation. This last argument also helps to highlight respects in which normative explanation won’t be worryingly discontinuous with explanations in other domains even though these other explanations aren’t subject to the justification condition. Thus the paper aims not only to do some constructive theorizing about the relatively neglected topic of normative explanation but also to cast light on the broader question of how normative explanation may be similar to and different from explanations in other domains. (shrink)

Some properties are causally relevant for a certain effect, others are not. In this paper we describe a problem for our understanding of this notion and then offer a solution in terms of the notion of a program explanation.

Explanation in biology has long been characterized as being very different from explanation in other scientific disciplines, very much so from explanation in physics. One of the reasons was the existence in biology of explanation types that were unheard of in the physical sciences: teleological explanations (e.g. Hull 1974), evolutionary explanations (e.g. Mayr 1988), or even functional explanations (e.g. Neander 1991). More recently, and owing much to the rise of molecular biology, biological explanations have been depicted (...) as mechanisms (e.g; Machamer, Darden and Craver 2000). The aim of this volume is to shed some new light on the diversity of explanation types in biology. What are the different types of explanation that occur in biology? Are these types of explanation specific to particular sub-disciplines of biology, or to particular types of problems across biology? How do they relate to each another? Do they compete with one another for answering the same questions? Or do they complement each other, providing insights to different questions? What are the reasons for such diversity? Can this diversity be overcome by a broader unifying model of explanation or is it more profound and irreducible? Why? This volume aims at making sense of this diversity of types of explanations that are found in biology, of their relationship with one another. After all, explanation in biology may prove not only different from explanation in the physical sciences, but also much more diverse than originally anticipated. (shrink)

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

The essays in this volume address three fundamental questions in the philosophy of science: What is required for some fact to be evidence for a scientific ...

Recent work on interpretability in machine learning and AI has focused on the building of simplified models that approximate the true criteria used to make decisions. These models are a useful pedagogical device for teaching trained professionals how to predict what decisions will be made by the complex system, and most importantly how the system might break. However, when considering any such model it’s important to remember Box’s maxim that "All models are wrong but some are useful." We focus on (...) the distinction between these models and explanations in philosophy and sociology. These models can be understood as a "do it yourself kit" for explanations, allowing a practitioner to directly answer "what if questions" or generate contrastive explanations without external assistance. Although a valuable ability, giving these models as explanations appears more difficult than necessary, and other forms of explanation may not have the same trade-offs. We contrast the different schools of thought on what makes an explanation, and suggest that machine learning might benefit from viewing the problem more broadly. (shrink)

INTRODUCTION The appeal to teleological principles of explanation within the body of natural science has had an unfortunate history. ...

The received view of dynamical explanation is that dynamical cognitive science seeks to provide covering law explanations of cognitive phenomena. By analyzing three prominent examples of dynamicist research, I show that the received view is misleading: some dynamical explanations are mechanistic explanations, and in this way resemble computational and connectionist explanations. Interestingly, these dynamical explanations invoke the mathematical framework of dynamical systems theory to describe mechanisms far more complex and distributed than the ones typically considered by philosophers. Therefore, contemporary (...) dynamicist research reveals the need for a more sophisticated account of mechanistic explanation. (shrink)

Call an explanation in which a non-mathematical fact is explained—in part or in whole—by mathematical facts: an extra-mathematical explanation. Such explanations have attracted a great deal of interest recently in arguments over mathematical realism. In this article, a theory of extra-mathematical explanation is developed. The theory is modelled on a deductive-nomological theory of scientific explanation. A basic DN account of extra-mathematical explanation is proposed and then redeveloped in the light of two difficulties that the basic (...) theory faces. The final view appeals to relevance logic and uses resources in information theory to understand the explanatory relationship between mathematical and physical facts. 1Introduction2Anchoring3The Basic Deductive-Mathematical Account4The Genuineness Problem5Irrelevance6Relevance and Information7Objections and Replies 7.1Against relevance logic7.2Too epistemic7.3Informational containment8Conclusion. (shrink)

The claim that scientific explanation is deductive has been attacked on both systematic and historical grounds. This paper briefly defends the claim against the systematic attack. Essential to this defence is a distinction between perfect and imperfect explanation. This distinction is then used to illuminate the differences and similarities between Aristotelian (anthropomorphic) explanations of certain facts and those of classical mechanics. In particular, it is argued that when one attempts to fit classical mechanics into the Aristotelian framework the (...) latter becomes structurally incoherent. It is suggested that this, together with the fact that classical mechanics embodied the first piece of perfect knowledge, accounts, in part at least, for the historical fact of the rapid demise of the Aristotelian patterns as the new science developed. On the basis of this discussion, the inadequacies of the attack on the deductive model on historical grounds by Toulmin come to be seen. (shrink)

Abstract: Situations that social scientists and others explain by using concepts like "custom" and "norm" often tend to be situations in which many other kinds of explanations (for example, biological, psychological, economic, historical) seem plausible as well. Do these other explanations compete with the custom or norm explanations, or do they complement them? We need to consider this question carefully and not just assume that various accounts are all permissible at different levels of analysis. In this article I describe two (...) families of noncompeting accounts: (1) explanations of different (but similarly described) facts, and (2) accounts that seem to differ but are really different parts or versions of the same underlying explanation. I argue that while many types of apparent competitors don't really compete with norms, there are usually some that do. These competing accounts will usually undermine the norm account. (shrink)

Scientists and laypeople alike use the sense of understanding that an explanation conveys as a cue to good or correct explanation. Although the occurrence of this sense or feeling of understanding is neither necessary nor sufficient for good explanation, it does drive judgments of the plausibility and, ultimately, the acceptability, of an explanation. This paper presents evidence that the sense of understanding is in part the routine consequence of two well-documented biases in cognitive psychology: overconfidence and (...) hindsight. In light of the prevalence of counterfeit understanding in the history of science, I argue that many forms of cognitive achievement do not involve a sense of understanding, and that only the truth or accuracy of an explanation make the sense of understanding a valid cue to genuine understanding. (shrink)

Lately, philosophers of mathematics have been exploring the notion of mathematical explanation within mathematics. This project is supposed to be analogous to the search for the correct analysis of scientific explanation. I argue here that given the way philosophers have been using “ explanation,” the term is not applicable to mathematics as it is in science.

Can there be mathematical explanations of physical phenomena? In this paper, I suggest an affirmative answer to this question. I outline a strategy to reconstruct several typical examples of such explanations, and I show that they fit a common model. The model reveals that the role of mathematics is explicatory. Isolating this role may help to re-focus the current debate on the more specific question as to whether this explicatory role is, as proposed here, also an explanatory one.

This paper argues that besides mechanistic explanations, there is a kind of explanation that relies upon “topological” properties of systems in order to derive the explanandum as a consequence, and which does not consider mechanisms or causal processes. I first investigate topological explanations in the case of ecological research on the stability of ecosystems. Then I contrast them with mechanistic explanations, thereby distinguishing the kind of realization they involve from the realization relations entailed by mechanistic explanations, and explain how (...) both kinds of explanations may be articulated in practice. The second section, expanding on the case of ecological stability, considers the phenomenon of robustness at all levels of the biological hierarchy in order to show that topological explanations are indeed pervasive there. Reasons are suggested for this, in which “neutral network” explanations are singled out as a form of topological explanation that spans across many levels. Finally, I appeal to the distinction of explanatory regimes to cast light on a controversy in philosophy of biology, the issue of contingence in evolution, which is shown to essentially involve issues about realization. (shrink)

This paper offers a new account of metaphysical explanation. The account is modelled on Kitcher’s unificationist approach to scientific explanation. We begin, in Sect. 2, by briefly introducing the notion of metaphysical explanation and outlining the target of analysis. After that, we introduce a unificationist account of metaphysical explanation before arguing that such an account is capable of capturing four core features of metaphysical explanations: irreflexivity, non-monotonicity, asymmetry and relevance. Since the unificationist theory of metaphysical (...) class='Hi'>explanation inherits irreflexivity and non-monotonicity directly from the unificationist theory of scientific explanation that underwrites it, we focus on demonstrating how the account can secure asymmetry and relevance. (shrink)

Explanation and understanding are intimately connected notions, but the nature of that connection has generally not been considered a topic worthy of serious philosophical investigation. Most authors have avoided making reference to the notion of understanding in their accounts of explanation because they fear that any mention of the epistemic states of the individuals involved compromises the objectivity of explanation. Understanding is a pragmatic notion, they argue, and pragmatics should be kept at a safe distance from the (...) universal features of explanation. My main contention in this dissertation is that there is a sense in which it is meaningful and useful to talk about objective understanding, and that to characterize this notion it is necessary to formulate an account of objective explanation that makes reference to the beliefs and epistemic goals of the participants in a cognitive enterprise. ;My account of explanation is based on the belief-doubt model of inquiry first proposed by Peirce. Using the tools provided by decision theory, and the models of belief revision developed by Isaac Levi and by Alchourron, Gardenfors, and Makinson, I analyze the objective and pragmatic conditions that a piece of information must fulfill to be both explanatory and epistemically useful to an inquiring agent. The objective basis for an explanation is provided by the relation of probabilistic relevance that the fact described by the explanans bares to the fact described by the explanandum. But an explanation is much more than its foundation. As an epistemological notion, a potential explanation can 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 an explanation in terms of its credibility, its content, and its explanatory value. I argue that although an objective measure of the credibility and content of an explanation can be established, in many cases a complete determination of its explanatory value will ultimately depend on the interests and goals of the individual inquirers. (shrink)

This paper examines explanations that turn on non-local geometrical facts about the space of possible configurations a system can occupy. I argue that it makes sense to contrast such explanations from "geometry of motion" with causal explanations. I also explore how my analysis of these explanations cuts across the distinction between kinematics and dynamics.

Explanation is asymmetric: if A explains B, then B does not explain A. Tradition- ally, the asymmetry of explanation was thought to favor causal accounts of explanation over their rivals, such as those that take explanations to be inferences. In this paper, we develop a new inferential approach to explanation that outperforms causal approaches in accounting for the asymmetry of explanation.

This book introduces readers to the topic of explanation. The insights of Plato, Aristotle, J.S. Mill and Carl Hempel are examined, and are used to argue against the view that explanation is merely a problem for the philosophy of science. Having established its importance for understanding knowledge in general, the book concludes with a bold and original explanation of explanation.

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

In scientific explanations, the explanans theory is sometimes incommensurable with the explanandum empirical data. How is this possible, especially when the explanation is deductive in nature? This paper attempts to solve the puzzle without relying on any particular theory of reference. For us, it is rather obvious that the geometric idea of projection plays a key role in Keplers explanation of Tycho Brahes empirical data. We discover that a similar mechanism operates in theoretic explanations in general. In short, (...) all theoretic explanations are projective explanations. If so, there should be no logical reason why explanans theories cannot be incommensurable with explanandum data. For illustration, we analyse Einsteins explanation of the results of the Michelson–Morley experiment in some detail. (shrink)

Explanations in the life sciences frequently involve presenting a model of the mechanism taken to be responsible for a given phenomenon. Such explanations depart in numerous ways from nomological explanations commonly presented in philosophy of science. This paper focuses on three sorts of differences. First, scientists who develop mechanistic explanations are not limited to linguistic representations and logical inference; they frequently employ diagrams to characterize mechanisms and simulations to reason about them. Thus, the epistemic resources for presenting mechanistic explanations are (...) considerably richer than those suggested by a nomological framework. Second, the fact that mechanisms involve organized systems of component parts and operations provides direction to both the discovery and testing of mechanistic explanations. Finally, models of mechanisms are developed for specific exemplars and are not represented in terms of universally quantified statements. Generalization involves investigating both the similarity of new exemplars to those already studied and the variations between them. (shrink)

Competing Explanations of Competing Explanations: Accounting for Conflict Between Scientific and Folk ExplanationsThis paper focuses on the level of people’s explanatory reasoning. It examines why laypeople prefer folk explanations of various physical or biological phenomena to alternative, well‐understood scientific explanations. Shtulman and Legare call this psychological phenomenon “explanatory co‐existence.” On the basis of new experimental data, they evaluate two possible accounts of explanatory co‐existence, a theory‐based and an associative account, and argue that a theory‐based account is the better supported.

Back cover: This book develops a philosophical account that reveals the major characteristics that make an explanation in the life sciences reductive and distinguish them from non-reductive explanations. Understanding what reductive explanations are enables one to assess the conditions under which reductive explanations are adequate and thus enhances debates about explanatory reductionism. The account of reductive explanation presented in this book has three major characteristics. First, it emerges from a critical reconstruction of the explanatory practice of the life (...) sciences itself. Second, the account is monistic since it specifies one set of criteria that apply to explanations in the life sciences in general. Finally, the account is ontic in that it traces the reductivity of an explanation back to certain relations that exist between objects in the world (such as part-whole relations and level relations), rather than to the logical relations between sentences. Beginning with a disclosure of the meta-philosophical assumptions that underlie the author’s analysis of reductive explanation, the book leads into the debate about reduction(ism) in the philosophy of biology and continues with a discussion on the two perspectives on explanatory reduction that have been proposed in the philosophy of biology so far. The author scrutinizes how the issue of reduction becomes entangled with explanation and analyzes two concepts, the concept of a biological part and the concept of a level of organization. The results of these five chapters constitute the ground on which the author bases her final chapter, developing her ontic account of reductive explanation. (shrink)

R. J. Hankinson traces the history of ancient Greek thinking about causation and explanation, from its earliest beginnings through more than a thousand years to the middle of the first millennium of the Christian era. He examines ways in which the Ancient Greeks dealt with questions about how and why things happen as and when they do, about the basic constitution and structure of things, about function and purpose, laws of nature, chance, coincidence, and responsibility.