Causal Accounts of Explanation

In the recent literature on causal and non-causal scientific explanations, there is an intuitive assumption according to which an explanation is non-causal by virtue of being abstract. In this context, to be ‘abstract’ means that the explanans in question leaves out many or almost all causal microphysical details of the target system. After motivating this assumption, we argue that the abstractness assumption, in placing the abstract and the causal character of an explanation in tension, is misguided in ways that are (...) independent of which view of causation or causal explanation one takes to be most accurate. On major accounts of causation, as well as on major accounts of causal explanation, the abstractness of an explanation is not sufficient for it being non-causal. That is, explanations are not non-causal by dint of being abstract. (shrink)

The recent use of typicality in statistical mechanics for foundational purposes has stirred an important debate involving both philosophers and physicists. While this debate customarily focuses on technical issues, in this paper I try to approach the problem from an epistemological angle. The discussion is driven by two questions: (1) What does typicality add to the concept of measure? (2) What kind of explanation, if any, does typicality yield? By distinguishing the notions of `typicality-as-vast-majority' and `typicality-as-best-exemplar', I argue that the (...) former goes beyond the concept of measure. Furthermore, I also argue that typicality aims at providing us with a form of causal explanation of equilibrium. (shrink)

Kausales Denken spielt sowohl im Alltag wie auch im wissenschaftlichen Forschungsprozess eine zentrale Rolle. Es erlaubt uns, Phänomene vorherzusagen, zu kontrollieren und zu verstehen. Kausales Denken geht über die Angabe der Ursachen eines Phänomens hinaus: Wollen wir verstehen, warum ein Fahrrad fährt, so versuchen wir, Schritt für Schritt nachzuvollziehen, wie die einzelnen Bestandteile des Fahrrads zusammenwirken, um miteinander die Bewegung zu produzieren. Wir sind an dem Mechanismus interessiert, durch den das Phänomen zustande kommt. Dieses Vorgehen wird in der Wissenschaftsphilosophie wie (...) auch in der Kognitionspsychologie mit Hilfe mechanistischer Theorien kausalen Denkens beschrieben. Der Sammelband bringt erstmals Vertreter beider Disziplinen in sechs aufeinander abgestimmten Beiträgen zusammen. Neben einer Diskussion der Kernmerkmale mechanistischen Denkens stehen insbesondere Fragen nach dem Erwerb mechanistischer Denkstrukturen und nach der Rolle von Handlungen und Handlungserfahrungen im Fokus. (shrink)

This article makes three claims concerning the concept of contingency. First, we argue that the word contingency is used in far too many ways to be useful. Its many meanings are detrimental to clarity of discussion and thought in history and the social sciences. We show how there are eight distinct uses of the word and illustrate this with numerous examples from the social sciences and history, highlighting the scope for confusion caused by the many, often contradictory uses of the (...) term. Second, we impose some order on these uses through developing a threefold classification of contingency based on assumptions about possible worlds and determinism. Finally, we discuss why we believe that one of the classes is a special use of the word without relevance to the social sciences, while the two remaining classes are nothing more than a variety of the “no hidden factors” argument in the debate on indeterminism and determinism. (shrink)

In this paper I develop a theory of contrastive why questions that establishes under what conditions it is sensible to ask "why p rather than q?". p and q must be outcomes of a single type of causal process.

The present paper advances an analogy between cases of extra-mathematical explanation and cases of what might be termed ‘extra-logical explanation’: the explanation of a physical fact by a logical fact. A particular case of extra-logical explanation is identified that arises in the philosophical literature on time travel. This instance of extra-logical explanation is subsequently shown to be of a piece with cases of extra-mathematical explanation. Using this analogy, we argue extra-mathematical explanation is part of a broader class of non-causal explanation. (...) This has important implications for extra-mathematical explanation, for time travel and for theories of explanation more generally. (shrink)

We argue that there is no tension between Reid's description of science and his claim that science is based on the principles of common sense. For Reid, science is rooted in common sense since it is based on the idea that fixed laws govern nature. This, however, does not contradict his view that the scientific notions of causation and explanation are fundamentally different from their common sense counterparts. After discussing these points, we dispute with Cobb's and Benbaji's interpretations of Reid's (...) views on causation and explanation. Finally, we present Reid's views from the perspective of the contemporary debate on scientific explanation. (shrink)

Omissions – any events, actions, or things that do not occur – are central to numerous debates in causation and ethics. This article surveys views on what omissions are, whether they are causally efficacious, and how they ground moral responsibility.

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)

Bellʼs 1964 theorem causes a severe problem for the notion that correlations require explanation, encapsulated in Reichenbachʼs principle of common cause. Despite being a hallmark of scientific thought, dropping the principle has been widely regarded as much less bitter medicine than the perceived alternative—dropping relativistic causality. Recently, however, some authors have proposed that modified forms of Reichenbachʼs principle could be maintained even with relativistic causality. Here we break down Reichenbachʼs principle into two independent assumptions—the principle of common cause proper and (...) factorization of probabilities. We show how Bellʼs theorem can be derived from these two assumptions plus relativistic causality and the law of total probability for actual events, and we review proposals to drop each of these assumptions in light of the theorem. In particular, we show that the non-commutative common causes of Hofer-Szabó and Vecsernyés fail to have an analogue of the notion that the common causes can explain the observed correlations. Moreover, we show that their definition can be satisfied trivially by any quantum product state for any quantum correlations. We also discuss how the conditional states approach of Leifer and Spekkens fares in this regard. (shrink)

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

Path-dependence offers a promising way of understanding the role historicity plays in explanation, namely, how the past states of a process can matter in the explanation of a given outcome. The two main existing accounts of path-dependence have sought to present it either in terms of dynamic landscapes or branching trees. However, the notions of landscape and tree both have serious limitations and have been criticized. The framework of causal networks is both more fundamental and more general that that of (...) landscapes and trees. Within this framework, I propose that historicity in networks should be understood as symmetry breaking. History matters when an asymmetric bias towards an outcome emerges in a causal network. This permits a quantitative measure for how path-dependence can occur in degrees, and offers suggestive insights into how historicity is intertwined both with causal structure and complexity. (shrink)

This paper critiques the new mechanistic explanatory program on grounds that, even when applied to the kinds of examples that it was originally designed to treat, it does not distinguish correct explanations from those that blunder. First, I offer a systematization of the explanatory account, one according to which explanations are mechanistic models that satisfy three desiderata: they must 1) represent causal relations, 2) describe the proper parts, and 3) depict the system at the right ‘level.’ Second, I argue that (...) even the most developed attempts to fulfill these desiderata fall short by failing to appropriately constrain explanatorily apt mechanistic models. -/- *This paper used to be called "The Emperor's New Mechanisms". (shrink)

The interventionist account of causal explanation, in the version presented by Jim Woodward, has been recently claimed capable of buttressing the widely felt—though poorly understood—hunch that high-level, relatively abstract explanations, of the sort provided by sciences like biology, psychology and economics, are in some cases explanatorily optimal. It is the aim of this paper to show that this is mistaken. Due to a lack of effective constraints on the causal variables at the heart of the interventionist causal-explanatory scheme, as presently (...) formulated it is either unable to prefer high-level explanations to low, or systematically overshoots, recommending explanations at so high of a level as to be virtually vacuous. (shrink)

Among the factors necessary for the occurrence of some event, which of these are selectively highlighted in its explanation and labeled as causes — and which are explanatorily omitted, or relegated to the status of background conditions? Following J. S. Mill, most have thought that only a pragmatic answer to this question was possible. In this paper I suggest we understand this ‘causal selection problem’ in causal-explanatory terms, and propose that explanatory trade-offs between abstraction and stability can provide a principled (...) solution to it. After sketching that solution, it is applied to a few biological examples, including to a debate concerning the ‘causal democracy’ of organismal development, with an anti-democratic (though not a gene-centric) moral. (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)

I offer an account of how the quantum theory we have helps us explain so much. The account depends on a pragmatist interpretation of the theory: this takes a quantum state to serve as a source of sound advice to physically situated agents on the content and appropriate degree of belief about matters concerning which they are currently inevitably ignorant. The general account of how to use quantum states and probabilities to explain otherwise puzzling regularities is then illustrated by showing (...) how we can explain single-particle interference phenomena, the stability of matter, and interference of Bose–Einstein condensates. Finally, I note some open problems and relate this account to alternative approaches to explanation that emphasize the importance of causation, of unification, and of structure. 1 Introduction2 Two Requirements on Explanations in Physics3 What We Can use Quantum Theory to Explain4 The Function of Quantum States and Born Probabilities5 How These Functions Contribute to the Explanatory Task6 Example One: Single-Particle Interference7 Example Two: Explanation of the Stability of Matter8 Example Three: Bose Condensation9 Conclusion. (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)

In this paper we will show that Hempel's covering law model can't deal very well with explanations that are based on incomplete knowledge. In particular the symmetry thesis, which is an important aspect of the covering law model, turns out to be problematic for these explanations. We will discuss an example of an electric circuit, which clearly indicates that the symmetry of explanation and prediction does not always hold. It will be argued that an alternative logic for causal explanation is (...) needed. And we will investigate to what extent non-monotonic epistemic logic can provide such an alternative logical framework. Finally we will show that our non-monotonic logical analysis of explanation is not only suitable for simple cases such as the electric circuit, but that it also sheds new light on more controversial causal explanations such as Milton Friedman's explanation of the business cycle. (shrink)

A number of philosophers have recently suggested that some abstract, plausibly non-causal and/or mathematical, explanations explain in a way that is radically dif- ferent from the way causal explanation explain. Namely, while causal explanations explain by providing information about causal dependence, allegedly some abstract explanations explain in a way tied to the independence of the explanandum from the microdetails, or causal laws, for example. We oppose this recent trend to regard abstractions as explanatory in some sui generis way, and argue (...) that a prominent ac- count of causal explanation can be naturally extended to capture explanations that radically abstract away from microphysical and causal-nomological details. To this end, we distinguish di erent senses in which an explanation can be more or less abstract, and analyse the connection between explanations’ abstractness and their explanatory power. According to our analysis abstract explanations have much in common with counterfactual causal explanations. (shrink)

When evaluating the success of causal theories of explanation the focus has typically been on the legitimacy of causal relations and on putative examples of explanations that we cannot capture in causal terms. Here I motivate the existence of a third kind of problem: the difficulty of accounting for explanatory disputes. Moreover, I argue that this problem remains even if the first two are settled and that it threatens to undercut one of the central motivations for causal accounts of explanation, (...) namely, the causal account of the directionality of scientific explanation. (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)

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

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)

Most defenders of the new mechanistic approach accept ontic constraints for successful scientific explanation (Illari 2013; Craver 2014). The minimal claim is that scientific explanations have objective truthmakers, namely mechanisms that exist in the physical world independently of any observer and that cause or constitute the phenomena-to- be-explained. How can this idea be applied to type-level explanations? Many authors at least implicitly assume that in order for mechanisms to be the truthmakers of type-level explanation they need to be regular (Andersen (...) 2012; Sheredos 2015). One problem of this assumption is that most mechanisms are (highly) stochastic in the sense that they “fail more often than they succeed” (Bogen 2005; Andersen 2012). How can a mechanism type whose instances are more likely not to produce an instance of a particular phenomenon type be the truthmaker of the explanation of that particular phenomenon type? In this paper, I will give an answer to this question. I will analyze the notion of regularity and I will discuss Andersen's suggestion for how to cope with stochastic mechanisms. I will argue that her suggestion cannot account for all kinds of stochastic mechanisms and does not provide an answer as to why regularity grounds type-level explanation. According to my analysis, a mechanistic type- level explanation is true if and only if at least one of the following two conditions is satisfied: the mechanism brings about the phenomenon more often than any other phenomenon (comparative regularity) or the phenomenon is more often brought about by the mechanism than by any other mechanism/causal sequence (comparative reverse regularity). (shrink)

Constitutivemechanisticexplanationsexplainapropertyofawholewith the properties of its parts and their organization. Carl Craver’s mutual manipulability criterion for constitutive relevance only captures the explanatory relevance of causal properties of parts and leaves the organization side of mechanistic explanation unaccounted for. We use the contrastive counterfactual theory of explanation and an account of the dimensions of organization to build a typology of organizational dependence. We analyse organizational explanations in terms of such dependencies and emphasize the importance of modular organizational motifs. We apply this framework (...) to two cases from social science and systems biology, both fields in which organization plays a crucial explanatory role: agent-based simulations of residential segregation and the recent work on network motifs in transcription regulation networks. (shrink)

Analogies to machines are commonplace in the life sciences, especially in cellular and molecular biology — they shape conceptions of phenomena and expectations about how they are to be explained. This paper offers a framework for thinking about such analogies. The guiding idea is that machine-like systems are especially amenable to decompositional explanation, i.e., to analyses that tease apart underlying components and attend to their structural features and interrelations. I argue that for decomposition to succeed a system must exhibit causal (...) orderliness, which I explicate in terms of differentiation among parts and the significance of local relations. I also discuss what makes a model depict its target as machine-like, suggesting that a key issue is the degree of detail with respect to the target’s parts and their interrelations. (shrink)

We sley Salmon, in his influential and detailed book, Four Decades of Scientific Explanation, argues that the pragmatic approach to scientific explanation, “construed as the claim that scientific explanation can be explicated entirely in pragmatic terms” (1989, 185) is inadequate. The specific inadequacy ascribed to a pragmatic account is that objective relevance relations cannot be incorporated into such an account. Salmon relies on the arguments given in Kitcher and Salmon (1987) to ground this objection. He also suggests that Peter Railton’s (...) concepts of the ideal explanatory text and explanatory information (Railton 1981) can provide what the pragmatic approach lacks. This suggestion is not a conclusion of course; we read it as the promotion of part of a research program aimed at forging a greater consensus on scientific explanation-an admirable goal. However, we do not see the pragmatic approach as inadequate. We will show that a synthetic account inspired by Salmon’s adaptation of Railton would be equivalent to van Fraassen’s pragmatic account in three respects: accepting or rejecting requests for explanation; the practice of giving scientific explanations; and the evaluation of the goodness of explanations. We include all three under the general rubric of explanatory “practice.” Admittedly these are not the only three features by which an account of explanation might be evaluated. Roughly, we mean to show that a synthetic account cannot do a better job of accounting for the scientific practices which are of importance to the constructive empiricist, and therefore no argument can be presented to the constructive empiricist to convince her that by her own standards the synthetic account is superior. (shrink)

Our ordinary causal concept seems to fit poorly with how our best physics describes the world. We think of causation as a time-asymmetric dependence relation between relatively local events. Yet fundamental physics describes the world in terms of dynamical laws that are, possible small exceptions aside, time symmetric and that relate global time slices. My goal in this paper is to show why we are successful at using local, time-asymmetric models in causal explanations despite this apparent mismatch with fundamental physics. (...) In particular, I will argue that there is an important connection between time asymmetry and locality, namely: understanding the locality of our causal models is the key to understanding why the physical time asymmetries in our universe give rise to time asymmetry in causal explanation. My theory thus provides a unified account of why causation is local and time asymmetric and thereby enables a reply to Russell’s famous attack on causation. (shrink)

Those who have emphasised Nietzsche’s naturalism have often claimed that he emulates natural scientific methods by offering causal explanations of psychological, social, and moral phenomena. In order to render Nietzsche’s method consistent with his methodology, such readers of Nietzsche have also claimed that his objections are based on a limited scepticism concerning the veracity of causal explanations. My contention is that proponents of this reading are wrong about both Nietzsche’s methodology and his method. I argue for this by: first, showing (...) that Nietzsche was suspicious of causal explanations not only on sceptical grounds but also for reasons provided by his psychological analysis of our tendency to look for causes; and second, arguing for a non-causal interpretation of Nietzsche’s approach to psychological explanation. (shrink)

The principle of the common cause claims that if an improbable coincidence has occurred, there must exist a common cause. This is generally taken to mean that positive correlations between non-causally related events should disappear when conditioning on the action of some underlying common cause. The extended interpretation of the principle, by contrast, urges that common causes should be called for in order to explain positive deviations between the estimated correlation of two events and the expected value of their correlation. (...) The aim of this paper is to provide the extended reading of the principle with a general probabilistic model, capturing the simultaneous action of a system of multiple common causes. To this end, two distinct models are elaborated, and the necessary and sufficient conditions for their existence are determined. (shrink)

Partial explanations are everywhere. That is, explanations citing causes that explain some but not all of an effect are ubiquitous across science, and these in turn rely on the notion of degree of explanation. I argue that current accounts are seriously deficient. In particular, they do not incorporate adequately the way in which a cause’s explanatory importance varies with choice of explanandum. Using influential recent contrastive theories, I develop quantitative definitions that remedy this lacuna, and relate it to existing measures (...) of degree of causation. Among other things, this reveals the precise role here of chance, as well as bearing on the relation between causal explanation and causation itself. (shrink)

Causalists about explanation claim that to explain an event is to provide information about the causal history of that event. Some causalists also endorse a proportionality claim, namely that one explanation is better than another insofar as it provides a greater amount of causal information. In this chapter I consider various challenges to these causalist claims. There is a common and influential formulation of the causalist requirement – the ‘Causal Process Requirement’ – that does appear vulnerable to these anti-causalist challenges, (...) but I argue that they do not give us reason to reject causalism entirely. Instead, these challenges lead us to articulate the causalist requirement in an alternative way. This alternative articulation incorporates some of the important anti-causalist insights without abandoning the explanatory necessity of causal information. For example, proponents of the ‘equilibrium challenge’ argue that the best available explanations of the behaviour of certain dynamical systems do not appear to provide any causal information. I respond that, contrary to appearances, these equilibrium explanations are fundamentally causal, and I provide a formulation of the causalist thesis that is immune to the equilibrium challenge. I then show how this formulation is also immune to the ‘epistemic challenge’ – thus vindicating (a properly formulated version of) the causalist thesis. (shrink)

Since the publication of Carl Hempel and Paul Oppenheim's ground-breaking work "Studies in the Logic of Explanation," the theory of explanation has remained a major topic in the philosophy of science. This valuable collection provides readers with the opportunity to study some of the classic essays on the theory of explanation along with the best examples of the most recent work being done on the topic. In addition to the original Hempel and Oppenheim paper, the volume includes Scriven's critical reaction (...) to it, Wilfrid Sellars's discussion of the problem of theoretical explanation, and pieces by Salmon, Railton, van Fraassen, Friedman, Kitcher, and Achinstein in which they demonstrate the vitality of the subject by extending the scope of the inquiry. (shrink)

This paper discusses methodological similarities between Collingwood's approach to causation and contemporary manipulability-based views. Firstly, I argue that on both approaches there is a preoccupation with the origin of causal concepts which further connects to the aim of establishing the priority of a certain concept/sense of causation as more fundamental. The significant difference lies in Collingwood's focus on the logical and historical priority (Collingwood's sense I) while in more recent theories the focus has been on psychology (i.e., on different philosophical (...) concepts of causation tested in psychological setting-- Woodward, Waskan, Gijsbers & de Bruin). Secondly, I argue that on both Collingwood's views and contemporary approaches (especially Menzies & Price, Price, but also Woodward) there is an important connection between causation and the agent's perspective. This can be subsumed under what Collingwood identifies as the main presupposition underlying causal thought: the relation between the agent's perceived situation and the agent's desired situation/ goal. More broadly, the recent views on causation under discussion share Collingwood's aim of elucidating the problem of causation through investigating causal knowledge and thus can be integrated with his wider project of addressing metaphysical issues through the means of epistemology. (shrink)

Causal accounts of scientific explanation are currently broadly accepted (though not universally so). My first task in this paper is to show that, even for a causal approach to explanation, significant features of explanatory practice are not determined by settling how causal facts bear on the phenomenon to be explained. I then develop a broadly causal approach to explanation that accounts for the additional features that I argue an explanation should have. This approach to explanation makes sense of several aspects (...) of actual explanatory practice, including the widespread use of equilibrium explanations, the formulation of distinct explanations for a single event, and the tight relationship between explanations of events and explanations of causal regularities. (shrink)

Michael Strevens offers an account of causal explanation according to which explanatory practice is shaped by counterbalanced commitments to representing causal influence and abstracting away from overly specific details. In this paper, I challenge a key feature of that account. I argue that what Strevens calls explanatory frameworks figure prominently in explanatory practice because they actually improve explanations. This suggestion is simple but has far-reaching implications. It affects the status of explanations that cite multiply realizable properties; changes the explanatory role (...) of causal factors with small effect; and undermines Strevens’ titular explanatory virtue, depth. This results in greater coherence with explanatory practice and accords with the emphasis that Strevens places on explanatory patterns. Ultimately, my suggestion preserves a tight connection between explanation and the creation of understanding by taking into account explanations’ role in communication. (shrink)

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)

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)

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

Renormalization group (RG) methods are an established strategy to explain how it is possible that microscopically different systems exhibit virtually the same macro behavior when undergoing phase-transitions. I argue – in agreement with Robert Batterman – that RG explanations are non-causal explanations. However, Batterman misidentifies the reason why RG explanations are non-causal: it is not the case that an explanation is non- causal if it ignores causal details. I propose an alternative argument, according to which RG explanations are non-causal explanations (...) because their explanatory power is due to the application mathematical operations, which do not serve the purpose of representing causal relations. (shrink)