In this article, I explore the compatibility of inference to the best explanation (IBE) with several influential models and accounts of scientific explanation. First, I explore the different conceptions of IBE and limit my discussion to two: the heuristic conception and the objective Bayesian conception. Next, I discuss five models of scientific explanation with regard to each model’s compatibility with IBE. I argue that Kitcher’s unificationist account supports IBE; Railton’s deductive–nomological–probabilistic model, Salmon’s statistical-relevance model, and van Fraassen’s (...) erotetic account are incompatible with IBE; and Salmon’s causal–mechanical model is merely consistent with IBE. In short, many influential models of scientific explanation do not support IBE. I end by outlining three possible conclusions to draw: (1) either philosophers of science or defenders of IBE have seriously misconstrued the concept of explanation, (2) philosophers of science and defenders of IBE do not use the term ‘explanation’ univocally, and (3) the ampliative conception of IBE, which is compatible with any model of scientific explanation, deserves a closer look. (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.

Humeanism about laws of nature — the view that the laws reduce to the Humean mosaic — is a popular view, but currently existing versions face powerful objections. The non-supervenience objection, the non-fundamentality objection and the explanatory circularity objection have all been thought to cause problems for the Humean. However, these objections share a guiding thought — they are all based on the idea that there is a certain kind of divergence between the practice of science and the metaphysical picture (...) suggested by Humeanism. -/- I suggest that the Humean can respond to these objections not by rejecting this divergence, but by arguing that is appropriate. In particular the Humean can, in the spirit of Loewer (2012), distinguish between scientific and metaphysical explanation — this is motivated by differing aims of explanation in science and metaphysics. And they can further leverage this into distinctions between scientific and metaphysical fundamentality and scientific and metaphysical possibility. We can use these distinctions to respond to the objections that the Humean faces. (shrink)

Philosophers of science typically associate the causal‐mechanical view of scientific explanation with the work of Railton and Salmon. In this paper I shall argue that the defects of this view arise from an inadequate analysis of the concept of mechanism. I contrast Salmon’s account of mechanisms in terms of the causal nexus with my own account of mechanisms, in which mechanisms are viewed as complex systems. After describing these two concepts of mechanism, I show how the complex‐systems approach avoids (...) certain objections to Salmon’s account of causal‐mechanical explanation. I conclude by discussing how mechanistic explanations can provide understanding by unification. (shrink)

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

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)

Theories of rights seem well equipped to explain widely accepted claims about the morality of harming. But can they explain popular claims about the morality of imposing risks of harm? Many think not. But a plausible theory of rights can explain those claims if it says we have the right that others not impose risks of harm upon us. That is a good reason to believe we have that right. There are many objections to the claim that we have that (...) right, but none of them are sound. Among the topics covered are: the permissibility of rights infringements, trivial rights infringements, the permissibility of risk impositions, the aggregation of rights, consent, self-defense, punishment, and compensation. (shrink)

This paper presents and argues for an account of objectual understanding that aims to do justice to the full range of cases of scientific understanding, including cases in which one does not have an explanation of the understood phenomenon. According to the proposed account, one understands a phenomenon just in case one grasps a sufficiently accurate and comprehensive model of the ways in which it or its features are situated within a network of dependence relations; one’s degree of understanding (...) is proportional to the comprehensiveness and accuracy of such a model. I compare this account with accounts of scientific understanding that explicate understanding in terms of having an explanation of the understood phenomenon. I discuss three distinct types of cases in which scientific understanding does not amount to possessing an explanation of any kind, and argue that the proposed model-based account can accommodate these cases while still retaining a strong link between understanding and explanation. (shrink)

This paper tries to get a grip on two seemingly conflicting intuitions about reductionism in quantum mechanics. On the one hand it is received wisdom that quantum mechanics puts an end to ‘reductionism’. Quantum-entanglement is responsible for such features of quantum mechanics as holism, the failure of supervenience and emergence. While I agree with these claims I will argue that it is only part of the story. Quantum mechanics provides us with thorough-going reductionist explanations. I will distinguish two kinds of (...) micro-explanation (or micro-‘reduction’). I will argue that even though quantum-entanglement provides an example for the failure of one kind of micro-explanation it does not affect the other. Contrary to a recent paper by Kronz and Tiehen I claim that the explanation of the dynamics of quantum mechanical systems is just as reductionist as it used to be in classical mechanics. (shrink)

According to a number of recent philosophers, knowledge has an intimate relationship with rationality. Some philosophers hold, in particular, that rational agents do things for good motivating reasons, and that p can be one’s motivating reason for -ing (acting/believing/fearing/etc.) only if one knows that p. This paper argues against this view and in favor of the view that p cannot be one’s motivating reason for -ing—in the relevant sense—unless there is an appropriate explanatory connection between the fact that p and (...) one’s -ing. I argue that this view offers a better account of the cases alleged to support the knowledge view. (shrink)

Is the relationship between psychology and neuroscience one of autonomy or mutual constraint and integration? This volume includes new papers from leading philosophers seeking to address this issue by deepening our understanding of the similarities and differences between the explanatory patterns employed across these domains.

In his 1978 paper “Mathematical Explanation”, Mark Steiner attempts to modernize the Aristotelian idea that to explain a mathematical statement is to deduce it from the essence of entities figuring in the statement, by replacing talk of essences with talk of “characterizing properties”. The language Steiner uses is reminiscent of language used for proofs deemed “pure”, such as Selberg and Erdős’ elementary proofs of the prime number theorem avoiding the complex analysis of earlier proofs. Hilbert characterized pure proofs as (...) those that use only “means that are suggested by the content of the theorem”, a characterization we have elsewhere called “topical purity”. In this paper we will examine the connection between Steiner’s account of mathematical explanation and topical purity. Are Steiner-explanatory proofs necessarily topically pure? Are topically pure proofs necessarily Steiner-explanatory? Answers to these questions will shed light on the general question of the relation between purity and explanatory power. (shrink)

It is a widespread assumption in philosophy of science that data is what is explained by theory—that data itself is not explanatory. I draw on instances of representational and explanatory practice from mammalian chronobiology to suggest that this assumption is unsustainable. In many instances, biologists employ representations of data in explanatory ways that are not reducible to constraints on or evidence for representations of mechanisms. Data graphs are used to exemplify relationships between quantities in the mechanism, and often these representations (...) are necessary for explaining particular aspects of the phenomena under study. I argue that this kind of representation is distinct from representing laws or generalizations, and its primary purpose is to convey particular types or patterns of quantitative relationships. The benefit of the analysis is two-fold. First, it provides a more accurate account of explanatory practice in broadly mechanistic analysis in biology. Second, it suggests that there is not an explanatory “fundamental” type of representation in biology. Rather, the practice of explanation consists in the construction of different types of representations and their employment for distinct explanatory purposes. (shrink)

The ontic conception of scientific explanation has been constructed and motivated on the basis of a putative lexical ambiguity in the term explanation. I raise a puzzle for this ambiguity claim, and then give a deflationary solution under which all ontically-rendered talk of explanation is merely elliptical; what it is elliptical for is a view of scientific explanation that altogether avoids the ontic conception. This result has revisionary consequences for New Mechanists and other philosophers of science, (...) many of whom have assimilated their conception of explanation to the ontic conception. (shrink)

According to some philosophers, computational explanation is proprietary
to psychology—it does not belong in neuroscience. But neuroscientists routinely offer computational explanations of cognitive phenomena. In fact, computational explanation was initially imported from computability theory into the science of mind by neuroscientists, who justified this move on neurophysiological grounds. Establishing the legitimacy and importance of computational explanation in neuroscience is one thing; shedding light on it is another. I raise some philosophical questions pertaining to computational explanation and outline (...) some promising answers that are being developed by a number of authors. (shrink)

Philosophers have cataloged a range of genealogical methods by which different sorts of normative conclusions can be established. Although such methods provide diverging ways of pursuing genealogical inquiry, they typically converge in eschewing historiographic methodology, in favor of a uniquely philosophical approach. In contrast, one genealogist who drew on historiographic methodology is Michel Foucault. This article presents the motivations and advantages of Foucault's genealogical use of such a methodology. It advances two mains claims. First, that Foucault's early 1970s work employs (...) a distinct genealogical method, which borrows from contemporary historiographic models of explanation to expand the range of objects that are proper to genealogical accounts of historical change. I demonstrate how Foucault modifies two central commitments of Nietzsche by broadening the dimensions of genealogical inquiry and explanation. Second, that historical method has normative relevance for genealogy, insofar as different historiographic choices can lead to different normative conclusions. I motivate this second claim by explaining how Foucault's multidimensional genealogical method expands both (a) the range of objects that are subject to evaluative assessment, and (b) the set of possible prescriptive recommendations that follow from such assessment. (shrink)

In this article I argue that there are two different types of understanding: the understanding we get from explanations, and the understanding we get from unification. This claim is defended by first showing that explanation and unification are not as closely related as has sometimes been thought. A critical appraisal of recent proposals for understanding without explanation leads us to discuss the example of a purely classificatory biology: it turns out that such a science can give us understanding (...) of the world through unification of the phenomena, even though it does not give us any explanations. The two types of understanding identified in this paper, while strictly separate, do have in common that both consist in seeing how the individual phenomena of the universe hang together. Explanations give us connections between the phenomena through the asymmetric, ‘vertical’ relation of determination; unifications give us connections through the symmetric, ‘horizontal’ relation of kinship. We then arrive at a general definition of understanding as knowledge of connections between the phenomena, and indicate that there might be more than two types of understanding. (shrink)

In this essay I defend a theory of psychological explanation that is based on the joint commitment to direct reference and computationalism. I offer a new solution to the problem of Frege Cases. Frege Cases involve agents who are unaware that certain expressions corefer (e.g. that 'Cicero' and 'Tully' corefer), where such knowledge is relevant to the success of their behavior, leading to cases in which the agents fail to behave as the intentional laws predict. It is generally agreed (...) that Frege Cases are a major problem, if not the major problem, that this sort of theory faces. In this essay, I hope to show that the theory can surmount the Frege Cases. (shrink)

The aim of this series is to bring together important recent writings in major areas of philosophical inquiry, selected from a variety of sources, mostly periodicals, which may not be conveniently available to the university student or the general reader. The editor of each volume contributes an introductory essay on the items chosen and on the questions with which they deal. A selective bibliography is appended as a guide to further reading. This volume presents a selection of the most important (...) recent writings on the nature of explanation. It covers a broad range of topics from the philosophy of science to the central philosophical terrain of the theory of knowledge. The distinguished contributors include Peter Achinstein, Wesley C. Salmon, Carl G. Hempel, Philip Kitcher, Bas C. van Fraassen, Jaegwon Kim, B. Brody, Timothy McCarthy, Peter Railton, David Lewis, Peter Lipton, James Woodward, and Robert J. Matthews. (shrink)

This article explores the difficulties raised for social scientific investigation by the absence of experiment, critically reviewing realist responses to the problem such as those offered by Bhaskar, Collier and Sayer. It suggests that realist arguments for a shift from prediction to explanation, the use of abstraction, and reliance upon interpretive forms of investigation fail to demonstrate that these approaches compensate for the lack of experimental control. Instead, it is argued that the search for regularities, when suitably conceived, provides (...) the best alternative to experiment for the social sciences. (shrink)

Discussion of moral explanation has reached an impasse, with proponents of contemporary ethical naturalism upholding the explanatory integrity of moral facts and properties, and opponents--including both antirealists and non-naturalistic realists--insisting that such robustly explanatory pretensions as moral theory has be explained away. I propose that the key to solving the problem lies in the question whether instances of moral properties are causally efficacious. It is argued that, given the truth of contemporary ethical naturalism, moral properties are causally efficacious if (...) the properties of the special sciences are. (shrink)

When someone encounters an explanation perceived as weak, this may lead to a feeling of deprivation or tension that can be resolved by engaging in additional learning. This study examined to what extent children respond to weak explanations by seeking additional learning opportunities. Seven‐ to ten‐year‐olds (N = 81) explored questions and explanations (circular or mechanistic) about 12 animals using a novel Android tablet application. After rating the quality of an initial explanation, children could request and receive additional (...) information or return to the main menu to choose a new animal to explore. Consistent with past research, there were both developmental and IQ‐related differences in how children evaluated explanation quality. But across development, children were more likely to request additional information in response to circular explanations than mechanistic explanations. Importantly, children were also more likely to request additional information in direct response to explanations that they themselves had assigned low ratings, regardless of explanation type. In addition, there was significant variability in both children's explanation evaluation and their exploration, suggesting important directions for future research. The findings support the deprivation theory of curiosity and offer implications for education. (shrink)

Philosophers of psychology debate, among other things, which psychological models, if any, are (or provide) mechanistic explanations. This should seem a little strange given that there is rough consensus on the following two claims: 1) a mechanism is an organized collection of entities and activities that produces, underlies, or maintains a phenomenon, and 2) a mechanistic explanation describes, represents, or provides information about the mechanism producing, underlying, or maintaining the phenomenon to be explained (i.e. the explanandum phenomenon) (Bechtel and (...) Abrahamsen 2005; Craver 2007). If there is a rough consensus on what mechanisms are and that mechanistic explanations describe, represent, or provide information about them, then how is there no consensus on which psychological models are (or provide) mechanistic explanations? Surely the psychological models that are mechanistic explanations are the models that describe, represent, or provide information about mechanisms. That is true, of course; the trouble arises when determining what exactly that involves. Philosophical disagreement over which psychological models are mechanistic explanations is often disagreement about what it means to describe, represent, or provide information about a mechanism, among other things (Hochstein 2016; Levy 2013). In addition, one's position in this debate depends on a host of other seemingly arcane metaphysical issues, such as the nature of mechanisms, computational and functional properties (Piccinini 2016), and realization (Piccinini and Maley 2014), as well as the relation between models, methodologies, and explanations (Craver 2014; Levy 2013; Zednik 2015). Although I inevitably advocate a position, my primary aim in this chapter is to spell out all these relationships and canvas the positions that have been taken (or could be taken) with respect to mechanistic explanation in psychology, using dynamical systems models and cognitive models (or functional analyses) as examples. (shrink)

Abstraction and idealization are the two notions that are most often discussed in the context of assumptions employed in the process of model building. These notions are also routinely used in philosophical debates such as that on the mechanistic account of explanation. Indeed, an objection to the mechanistic account has recently been formulated precisely on these grounds: mechanists cannot account for the common practice of idealizing difference-making factors in models in molecular biology. In this paper I revisit the debate (...) and I argue that the objection does not stand up to scrutiny. This is because it is riddled with a number of conceptual inconsistencies. By attempting to resolve the tensions, I also draw several general lessons regarding the difficulties of applying abstraction and idealization in scientific practice. Finally, I argue that more care is needed only when speaking of abstraction and idealization in a context in which these concepts play an important role in an argument, such as that on mechanistic explanation. (shrink)

In this paper, I explicate desiderata for accounts of explanation in historiography. I argue that a fully developed account of explanation in historiography must explicate many explanation-related notions in order to be satisfactory. In particular, it is not enough that an account defines the basic structure of explanation. In addition, the account of explanation must be able to explicate notions such as minimal explanation, complete explanation, historiographical explanation, explanatory depth, explanatory competition, and (...) explanatory goal. Moreover, the account should also tell how explananda can be chosen in a motivated way. Furthermore, the account should be able to clarify notions that are closely connected with explanation such as historical contingency. Finally, it is important that the account is able to recognize when explanation-related notions and issues are so closely intertwined that we are in danger of not seeing the differences between them. In other words, I argue that a satisfactory account of explanation in historiography must have the power to explicate central explanation-related notions and to clarify discussions where the differences between the notions are obscure. In order to explicate these desiderata, I formulate a counterfactual account of explanation and show how that account is able to explicate explanation-related notions and clarify issues that are connected with historiographical explanations. The success of the counterfactual account suggests that historiographical explanations do not differ fundamentally from explanations in many other fields. (shrink)

What features will something have if it counts as an explanation? And will something count as an explanation if it has those features? In the second half of the 20th century, philosophers of science set for themselves the task of answering such questions, just as a priori conceptual analysis was generally falling out of favor. And as it did, most philosophers of science just moved on to more manageable questions about the varieties of explanation and discipline-specific scientific (...) explanation. Often, such shifts are sound strategies for problem-solving. But leaving fallow certain basic conceptual issues can also result in foundational debates. (shrink)

If physical reality is nonseparable, as quantum mechanics suggests, then it may contain processes of a quite novel kind. Such nonseparable processes could connect space-like separated events without violating relativity theory or any defensible locality condition. Appeal to nonseparable processes could ground theoretical explanations of such otherwise puzzling phenomena as the two-slit experiment, and EPR- type correlations. We find such phenomena puzzling because they threaten cherished conceptions of how causes operate to produce their effects. But nonseparable processes offer us an (...) alternative deal of natural order, conformity to which makes such phenomena seem quite normal and not at all unexpected. Attempts to answer the further question, as to whether an appeal to a nonseparable process provides a genuine "causal" explanation, have something to teach us about our concept of causation, but do not threaten to undermine the value of the explanation itself. (shrink)

Explanation is a perennially hot topic in philosophy of science. Yet philosophers have exhibited a curious blind spot to the questions of how explanatory projects develop over time, as well as what processes are involved in generating their developmental trajectories. This paper examines these questions using research into the end-Permian mass extinction as a case study. It takes as its jumping-off point the observation that explanations of historical events tend to grow more complex over time, but it goes beyond (...) this observation by scrutinizing the processes responsible for generating this pattern. Surveying several decades of research into the end-Permian extinction, I suggest that the principal “driver” of explanation in geohistory is non-explanatory work: work that is undertaken to increase our descriptive understanding of a phenomenon, not to test a particular explanatory claim. Non-explanatory work drives explanation by imposing or eliminating demands on explanation, and by furnishing new resources for constructing explanatory models. Explanations grow more complex because the demands on explanation tend to increase with ongoing characterization of the target phenomenon, and characterization tends grows the roster of explanatory resources. However, the fact that non-explanatory work sometimes eliminates demands on explanation means that this trend is not irreversible. I suggest that to achieve a more rounded view of the dynamics of explanation, philosophers should ask how research into complex phenomena is organized, as well as how explanatory progress depends upon the coordination of different kinds of material and epistemic resources. (shrink)