When cognitive scientists are looking for the neural basis of consciousness or the computational processes underlying vision, what are they looking to find? I argue for a new account of this explanatory project in cognitive science (and the special sciences more generally) on which it is best understood on close analogy with causal explanation in the special sciences. Causal explanations cite causal difference-makers: they explain how certain events causally depend on other events. Generative explanations cite generative difference-makers: they explain how (...) certain events obtain in virtue of (and so are generated by) other events. I show how that this generative difference-making account (GDM) extends well regarded developments in philosophical work on causal explanation, helps to usefully clarify and expands the hypothesis space of a key project in cognitive science – that of understanding how underlying nonmental processes give rise to the mental, including consciousness. In section 2, I develop GDM by close analogy with causal explanation, and locate both of them as species of a more general project in the special sciences: that of discovering what makes a difference to what. In section 3, I motivate GDM by contrasting it with other rival accounts, including correlationist, identity, and grounding accounts, as well as Carl Craver’s constitutive relevance account. In section 4, I tie all of the strands of the preceding discussion together to show how GDM provides a new and compelling response to the so-called hard problem of consciousness. (shrink)

This paper argues against the view that the standard explanation of phase transitions in statistical mechanics may be considered a causal explanation, a distortion that can nevertheless successfully represent causal relations.

In a recent paper, Barry Loewer attempts to defend Humeanism about laws of nature from a charge that Humean laws are not adequately explanatory. Central to his defense is a distinction between metaphysical and scientific explanations: even if Humeans cannot offer further metaphysical explanations of particular features of their “mosaic,” that does not preclude them from offering scientific explanations of these features. According to Marc Lange, however, Loewer’s distinction is of no avail. Defending a transitivity principle linking scientific explanantia to (...) their metaphysical grounds, Lange argues that a charge of explanatory inadequacy resurfaces once this intuitive principle is in place. This paper surveys, on behalf of the Humean, three strategies for responding to Lange’s criticism. The ready availability of these strategies suggests that Lange’s argument may not bolster anti-Humean convictions, since the argument rests on premises that those not antecedently sharing these convictions may well reject. The three strategies also correspond to three interesting ways of thinking about relations of grounding linking Humean laws and their instances, all of which are consistent with theses of Humean supervenience, and some of which have been heretofore overlooked. (shrink)

In his later years, Wesley Salmon believed that the two dominant models of scientific explanation (his own causal-mechanical model and the unificationist model) were reconcilable. Salmon envisaged a 'new consensus' about explanation: he suggested that the two models represent two 'complementary' types of explanation, which may 'peacefully coexist' because they illuminate different aspects of scientific understanding. This paper traces the development of Salmon's ideas and presents a critical analysis of his complementarity thesis. Salmon's thesis is rejected on the basis of (...) two objections, and an alternative view of the relation between different types of explanation is proposed. (shrink)

Veel wetenschappers, filosofen en theologen zijn van mening dat God nooit opgevoerd mag worden als verklaring voor een verschijnsel. Eén argument dat ze hiervoor aandragen is dat het op de een of andere manier in de aard van wetenschap zit dat God er geen rol in kan spelen. In dit artikel ga ik in op een specifieke versie van dit argument. Ik vraag me af of de aard van wetenschappelijke verklaringen uitsluit dat God als verklaringsgrond wordt genoemd. Om die vraag (...) te beantwoorden ga ik na of de door wetenschapsfilosofen ontwikkelde standaardmodellen van wetenschappelijk verklaren ruimte bieden aan theïstische verklaringen. Dat blijkt inderdaad zo te zijn, enige kwalificaties daargelaten. De conclusie moet dan ook luiden dat de aard van wetenschappelijke verklaringen niet zodanig is dat theïstische verklaringen uitgesloten zijn. (shrink)

Deductive Cogency holds that the set of propositions towards which one has, or is prepared to have, a given type of propositional attitude should be consistent and closed under logical consequence. While there are many propositional attitudes that are not subject to this requirement, e.g. hoping and imagining, it is at least prima facie plausible that Deductive Cogency applies to the doxastic attitude involved in propositional knowledge, viz. belief. However, this thought is undermined by the well-known preface paradox, leading a (...) number of philosophers to conclude that Deductive Cogency has at best a very limited role to play in our epistemic lives. I argue here that Deductive Cogency is still an important epistemic requirement, albeit not as a requirement on belief. Instead, building on a distinction between belief and acceptance introduced by Jonathan Cohen and recent developments in the epistemology of understanding, I propose that Deductive Cogency applies to the attitude of treating propositions as given in the context of attempting to understand a given phenomenon. I then argue that this simultaneously accounts for the plausibility of the considerations in favor of Deductive Cogency and avoids the problematic consequences of the preface paradox. (shrink)

According to the reward-prediction error hypothesis of dopamine, the phasic activity of dopaminergic neurons in the midbrain signals a discrepancy between the predicted and currently experienced reward of a particular event. It can be claimed that this hypothesis is deep, elegant and beautiful, representing one of the largest successes of computational neuroscience. This paper examines this claim, making two contributions to existing literature. First, it draws a comprehensive historical account of the main steps that led to the formulation and subsequent (...) success of the RPEH. Second, in light of this historical account, it explains in which sense the RPEH is explanatory and under which conditions it can be justifiably deemed deeper than the incentive salience hypothesis of dopamine, which is arguably the most prominent contemporary alternative to the RPEH. (shrink)

In a recent paper, Kaplan (Synthese 183:339–373, 2011) takes up the task of extending Craver’s (Explaining the brain, 2007) mechanistic account of explanation in neuroscience to the new territory of computational neuroscience. He presents the model to mechanism mapping (3M) criterion as a condition for a model’s explanatory adequacy. This mechanistic approach is intended to replace earlier accounts which posited a level of computational analysis conceived as distinct and autonomous from underlying mechanistic details. In this paper I discuss work in (...) computational neuroscience that creates difficulties for the mechanist project. Carandini and Heeger (Nat Rev Neurosci 13:51–62, 2012) propose that many neural response properties can be understood in terms of canonical neural computations. These are “standard computational modules that apply the same fundamental operations in a variety of contexts.” Importantly, these computations can have numerous biophysical realisations, and so straightforward examination of the mechanisms underlying these computations carries little explanatory weight. Through a comparison between this modelling approach and minimal models in other branches of science, I argue that computational neuroscience frequently employs a distinct explanatory style, namely, efficient coding explanation. Such explanations cannot be assimilated into the mechanistic framework but do bear interesting similarities with evolutionary and optimality explanations elsewhere in biology. (shrink)

The concepts of atoms and bonds in molecules which appeared in chemistry during the nineteenth century are unavoidable to explain the structure and the reactivity of the matter at a chemical level of understanding. Although they can be criticized from a strict reductionist point of view, because neither atoms nor bonds are observable in the sense of quantum mechanics, the topological and statistical interpretative approaches of quantum chemistry (quantum theory of atoms in molecules, electron localization function and maximum probability domain) (...) provide consistent definitions which accommodate chemistry and quantum mechanics. (shrink)

I develop a non-representationalist account of mathematical thought, on which the point of mathematical theorizing is to provide us with the conceptual capacity to structure and articulate information about the physical world in an epistemically useful way. On my view, accepting a mathematical theory is not a matter of having a belief about some subject matter; it is rather a matter of structuring logical space, in a sense to be made precise. This provides an elegant account of the cognitive utility (...) of mathematics. Further, it makes explicit how the brand of non-representationalism I develop is compatible with there being substantive rationality constraints on our mathematical theorizing. (shrink)

There is a widely shared belief that the higher-level sciences can provide better explanations than lower-level sciences. But there is little agreement about exactly why this is so. It is often suggested that higher-level explanations are better because they omit details. I will argue instead that the preference for higher-level explanations is just a special case of our general preference for informative, logically strong, beliefs. I argue that our preference for informative beliefs entirely accounts for why higher-level explanations are sometimes (...) better—and sometimes worse—than lower-level explanations. The result is a step in the direction of the unity of science hypothesis. 1Introduction2Background: Is Omitting Details an Explanatory Virtue? 2.1Anti-reductionist arguments2.2Reductionist argument2.3Logical strength3Bases, Links and Logical Strength4Functionalism and Fodor’s Argument5Two Generalizations6Should the Base Really Be Maximally Strong?7Anti-reductionist Arguments Regarding the Base8Should the Antecedent of the Link Really Be Maximally Weak? (shrink)

In an incendiary 2010 Nature article, M. A. Nowak, C. E. Tarnita, and E. O. Wilson present a savage critique of the best-known and most widely used framework for the study of social evolution, W. D. Hamilton’s theory of kin selection. More than a hundred biologists have since rallied to the theory’s defence, but Nowak et al. maintain that their arguments ‘stand unrefuted’. Here I consider the most contentious claim Nowak et al. defend: that Hamilton’s rule, the core explanatory principle (...) of kin selection theory, ‘almost never holds’. I first distinguish two versions of Hamilton’s rule in contemporary theory: a special version (HRS) that requires restrictive assumptions, and a general version (HRG) that does not. I then show that Nowak et al. are most charitably construed as arguing that HRS almost never holds, while HRG buys its generality at the expense of explanatory power. While their arguments against HRS are fairly uncontroversial, their arguments against HRG are more contentious, yet these have been largely overlooked in the ensuing furore. I consider the arguments for and against the explanatory value of HRG, with a view to assessing what exactly is at stake in the debate. I suggest that the debate hinges on issues concerning the causal interpretability of regression coefficients, and concerning the explanatory function Hamilton’s rule is intended to serve. (shrink)

It is often thought that metaphysical grounding underwrites a distinctive sort of metaphysical explanation. However, it would be a mistake to think that all metaphysical explanations are underwritten by metaphysical grounding. In service of this claim, I offer a novel kind of metaphysical explanation called metaphysical explanation by constraint, examples of which have been neglected in the literature. I argue that metaphysical explanations by constraint are not well understood as grounding explanations.

This article discusses minimal model explanations, which we argue are distinct from various causal, mechanical, difference-making, and so on, strategies prominent in the philosophical literature. We contend that what accounts for the explanatory power of these models is not that they have certain features in common with real systems. Rather, the models are explanatory because of a story about why a class of systems will all display the same large-scale behavior because the details that distinguish them are irrelevant. This story (...) explains patterns across extremely diverse systems and shows how minimal models can be used to understand real systems. (shrink)

The articulation of an overarching account of scientific explanation has long been a central preoccupation for the philosophers of science. Although a while ago the literature was dominated by two approaches—a causal account and a unificationist account—today the consensus seems to be that the causal account has won. In this paper, I challenge this consensus and attempt to revive unificationism. More specifically, I aim to accomplish three goals. First, I add new criticisms to the standard anti-unificationist arguments, in order to (...) motivate the need for a revision of the doctrine. Second, and most importantly, I sketch such a revised version. Then I argue that, contrary to widespread belief, the causal account and this revised unificationist account of explanation are compatible. Moreover, I also maintain that the unificationist account has priority, since a most satisfactory theory of explanation can be obtained by incorporating the causal account, as a sub-component of the unificationist account. The driving force behind this reevaluation of the received view in the philosophy of explanation is a reconsideration of the role of scientific understanding. (shrink)

Bogen and Woodward’s distinction between data and phenomena raises the need to understand the structure of the data-to-phenomena and theory-to-phenomena inferences. I suggest that one way to study the structure of these inferences is to analyze the role of the assumptions involved in the inferences: What kind of assumptions are they? How do these assumptions contribute to the practice of identifying phenomena? In this paper, using examples from atmospheric dynamics, I develop an account of the practice of identifying the target (...) in the data-to-phenomena and theory-to-phenomena inferences in which assumptions about spatiotemporal scales play a central role in the identification of parameters that describe the target system. I also argue that these assumptions are not only empirical but they are also idealizing and abstracting. I conclude the paper with a reflection on the role of idealizations in modeling. (shrink)

People often answer why-questions with what we call experiential explanations: narratives or stories with temporal structure and concrete details. In contrast, on most theories of the epistemic function of explanation, explanations should be abstractive: structured by general relationships and lacking extraneous details. We suggest that abstractive and experiential explanations differ not only in level of abstraction, but also in structure, and that each form of explanation contributes to the epistemic goals of individual learners and of science. In particular, experiential explanations (...) support mental simulation and survive transitions across background theories; as a result, they support learning and help us translate between competing frameworks. Experiential explanations play an irreducible role in human cognition – and perhaps in science. (shrink)

The present paper aims to complement causal model approaches to causal explanation by Woodward [15], Halpern and Pearl [5], and Strevens [14]. It centres on a strengthened Ramsey Test of conditionals: α ≫ γ iff, after sus- pending judgment about α and γ, an agent can infer γ from the supposition of α. It has been shown by Andreas and Gu ̈nther [1] that such a conditional can be used as starting point of an analysis of ‘because’ in natural language. (...) In what follows, we shall refine this analysis so as to yield a fully fledged account of causal explanation. (shrink)

In this dissertation, I argue that understanding possesses unique epistemic value. I propose and defend a novel account of understanding that I call the management account of understanding, which is the view that an agent A understands a subject matter S just in case A has the ability to extract the relevant information and exploit it with the relevant cognitive capacities to answer questions in S. Since inquiry is the process of raising and answering questions, I argue that without understanding, (...) it would be impossible to engage in successful inquiry. I argue that understanding is indispensable for effective cognition and that it is irreducible to other epistemic categories, such as knowledge, justification, or rationality. Understanding is an irreducible component of epistemic excellence. In arguing for this account, I focus on the nature and requirements of cognition and pay less attention to intuitions about hypothetical cases, in contrast to previous approaches to understanding. I draw upon psychology and cognitive science, especially work on the frame problem, to demonstrate the importance (and difficulty) of finding relevant information and exploiting it in relevant ways to answer questions. One’s cognitive system must be organized in such a way that one has the ability to think the relevant thoughts in the relevant ways to answer the relevant questions. This reveals well-defined directions in which future research on understanding should move. In addition to proposing and defending the management account of understanding, I explore several features of understanding, including some interesting consequences of the management account. I argue that the management account and commonly used methods of measuring degrees of understanding imply that understanding can be based on false beliefs. I argue that the management account (and any account of understanding that implies understanding is an ability) implies that understanding can be acquired by luck. I also argue that understanding is ontologically prior to explanation: a good explanation is essentially an act that produces understanding in the relevant cognitive background. (shrink)

All physical theories, from classical Newtonian mechanics to relativistic quantum field theory, entail propositions concerning the geometric structure of spacetime. To give an example, the general theory of relativity entails that spacetime is curved, smooth, and four-dimensional. In this dissertation, I take the structural commitments of our theories seriously and ask: how is such structure instantiated in the physical world? Mathematically, a property like 'being curved' is perfectly well-defined insofar as we know what it means for a mathematical space to (...) be curved. But what could it mean to say that the physical world is curved? Call this the problem of physical geometry. The problem of physical geometry is a plea for foundations--a request for fundamental truth conditions for physical-geometric propositions. My chief claim is that only a substantival theory of spacetime--a theory according to which spacetime is an entity in its own right, existing over and above the material content of the world--can supply the necessary truth conditions. (shrink)

It is commonly held that p is a reason for A to ϕ only if p explains why A ought to ϕ. I argue that this view must be rejected because there are reasons for A to ϕ that would be redundant in any ex...

A scientific explanatory project, part-whole explanation, and a kind of science, part-whole science are premised on identifying, investigating, and using parts and wholes. In the biological sciences, mechanistic, structuralist, and historical explanations are part-whole explanations. Each expresses different norms, explananda, and aims. Each is associated with a distinct partitioning frame for abstracting kinds of parts. These three explanatory projects can be complemented in order to provide an integrative vision of the whole system, as is shown for a detailed case study: (...) the tetrapod limb. My diagnosis of part-whole explanation in the biological sciences as well as in other domains exploring evolved, complex, and integrated systems (e.g., psychology and cognitive science) cross-cuts standard philosophical categories of explanation: causal explanation and explanation as unification. Part-whole explanation is itself one essential aspect of part-whole science. (shrink)

What is understanding? My goal in this paper is to lay out a new approach to this question and clarify how that approach deals with certain issues. The claim is that understanding is a matter of compressing information about the understood so that it can be mentally useful. On this account, understanding amounts to having a representational kernel and the ability to use it to generate the information one needs regarding the target phenomenon. I argue that this ambitious new account (...) can accommodate much of the data that has motivated theories of understanding in philosophy of science, and can also be generally applicable in epistemology and daily life as well. (shrink)

In this paper, I consider the relationship between coming to understand why something must be the case and coming to understand why it actually is the case in some particular instance. Peter Lipton uses the possibility of coming to understand a phenomenon via a necessity proof as an argument that there can be understanding with no explanation. Lipton’s argument has come under criticism, at least partially because one might think that understanding why something must be the case has a different (...) object from understanding the actual phenomenon. In this paper, I argue that that under certain circumstances it is fairly straightforward to come to understand an actual phenomenon on the basis of knowing why it had to be the case. Rather than relying on brute intuitions, my primary strategy will be to show that on least some modern accounts of understanding we can validate Lipton’s general point with respect to a variety of possible necessity relations. (shrink)

Some claim that Non- reductive Physicalism is an unstable position, on grounds that NRP either collapses into reductive physicalism, or expands into emergentism of a robust or ‘strong’ variety. I argue that this claim is unfounded, by attention to the notion of a degree of freedom—roughly, an independent parameter needed to characterize an entity as being in a state functionally relevant to its law-governed properties and behavior. I start by distinguishing three relations that may hold between the degrees of freedom (...) needed to characterize certain special science entities, and those needed to characterize their composing physical entities; these correspond to what I call ‘reductions’, ‘restrictions’, and ‘eliminations’ in degrees of freedom. I then argue that eliminations in degrees of freedom, in particular—when strictly fewer degrees of freedom are required to characterize certain special science entities than are required to characterize their composing physical entities—provide a basis for making sense of how certain special science entities can be both physically acceptable and ontologically irreducible to physical entities. (shrink)

Some claim that Non-reductive Physicalism is an unstable position, on grounds that NRP either collapses into reductive physicalism, or expands into emergentism of a robust or ‘strong’ variety. I argue that this claim is unfounded, by attention to the notion of a degree of freedom—roughly, an independent parameter needed to characterize an entity as being in a state functionally relevant to its law-governed properties and behavior. I start by distinguishing three relations that may hold between the degrees of freedom needed (...) to characterize certain special science entities, and those needed to characterize their composing physical entities; these correspond to what I call ‘reductions’, ‘restrictions’, and ‘eliminations’ in degrees of freedom. I then argue that eliminations in degrees of freedom, in particular—when strictly fewer degrees of freedom are required to characterize certain special science entities than are required to characterize their composing physical entities—provide a basis for making sense of how certain special science entities can be both physically acceptable and ontologically irreducible to physical entities. (shrink)

I problematize Grounding-based formulations of physicalism. More specifically, I argue, first, that motivations for adopting a Grounding-based formulation of physicalism are unsound; second, that a Grounding-based formulation lacks illuminating content, and that attempts to imbue Grounding with content by taking it to be a strict partial order are unuseful and problematic ; third, that conceptions of Grounding as constitutively connected to metaphysical explanation conflate metaphysics and epistemology, are ultimately either circular or self-undermining, and controversially assume that physical dependence is incompatible (...) with explanatory gaps; fourth, that in order to appropriately distinguish physicalism from strong emergentism, a Grounding-based formulation must introduce one and likely two primitives in addition to Grounding; and fifth, that understanding physical dependence in terms of Grounding gives rise to ‘spandrel’ questions, including, e.g., “What Grounds Grounding?”, which arise only due to the overly abstract nature of Grounding. (shrink)

According to Michael Friedman’s theory of explanation, a law X explains laws Y1, Y2, …, Yn precisely when X unifies the Y’s, where unification is understood in terms of reducing the number of independently acceptable laws. Philip Kitcher criticized Friedman’s theory but did not analyze the concept of independent acceptability. Here we show that Kitcher’s objection can be met by modifying an element in Friedman’s account. In addition, we argue that there are serious objections to the use that Friedman makes (...) of the concept of independent acceptability. (shrink)

If counterfactual dependence is sufficient for causation and if omissions can be causes, then all events have many more causes than common sense tends to recognize. This problem is standardly addressed by appeal to pragmatics. However, Carolina Sartorio [2010] has recently raised what I shall argue is a more interesting problem concerning omissions for counterfactual theories of causation—more interesting because it demands a more subtle pragmatic solution. I discuss the relationship between the idea that causes are proportional to their effects, (...) the idea that causation is contrastive, and the question of the dimensions along which causal explanations should be evaluated with respect to one another. (shrink)

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

Despite their best efforts, scientists may be unable to construct models that simultaneously exemplify every theoretical virtue. One explanation for this is the existence of tradeoffs: relationships of attenuation that constrain the extent to which models can have such desirable qualities. In this paper, we characterize three types of tradeoffs theorists may confront. These characterizations are then used to examine the relationships between parameter precision and two types of generality. We show that several of these relationships exhibit tradeoffs and discuss (...) what consequences those tradeoffs have for theoretical practice. (shrink)

This paper is an interpretation and defense of Richard Levins’ “The Strategy of Model Building in Population Biology,” which has been extremely influential among biologists since its publication 40 years ago. In this article, Levins confronted some of the deepest philosophical issues surrounding modeling and theory construction. By way of interpretation, I discuss each of Levins’ major philosophical themes: the problem of complexity, the brute-force approach, the existence and consequence of tradeoffs, and robustness analysis. I argue that Levins’ article is (...) concerned, at its core, with justifying the use of multiple, idealized models in population biology. (shrink)

I offer an explanation of why inertial and gravitational mass are equal in Newtonian gravitation. I then argue that this is an example of a kind of explanation that is not captured by standard philosophical accounts of scientific explanation. Moreover, this form of explanation is particularly important, at least in physics, because demands for this kind of explanation are used to motivate and shape research into the next generation of physical theories. I suggest that explanations of the sort I describe (...) reveal something important about one way in which physical theories may be related diachronically. (shrink)

The most compelling extant accounts of explanation casts all explanations as causal. Yet there are sciences, theoretical population biology in particular, that explain their phenomena by appeal to statistical, non-causal properties of ensembles. I develop a generalised account of explanation. An explanation serves two functions: metaphysical and cognitive. The metaphysical function is discharged by identifying a counterfactually robust invariance relation between explanans event and explanandum. The cognitive function is discharged by providing an appropriate description of this relation. I offer examples (...) of explanations from portfolio theory and population genetics that meet this characterisation. In each case the invariance relation holds between a statistical property of an ensemble and a change in structure of the ensemble. In neither case, however, does the statistical property cause the outcome it explains. There are genuine statistical, non-causal scientific explanations. (shrink)

Analysis of the adequacy of engineering design methods, as well as analysis of the utility of concepts of function often invoked in these methods, is a neglected topic in both philosophy of technology and in engineering proper. In this paper, I present an approach—dubbed an explanationist perspective—for assessing the adequacy of function-based design methods. Engineering design is often intertwined with explanation, for instance, in reverse engineering and subsequent redesign, knowledge base-assisted designing, and diagnostic reasoning. I argue that the presented approach (...) is useful for validating function-based design methods with respect to their explanatory elements and that it supports assessment of the explanatory and design utility of “function”, and the different conceptualizations thereof, as used in such engineering design methods. I deploy two key desiderata from the explanation literature to assess the viability of function-based design methods: explanatorily relevant difference-making factors and counterfactual understanding defined in terms of what-if-things-had-been-different questions. I explicate the approach and its merits in terms of two case studies drawn from the engineering functional modeling literature: reverse engineering and redesign and malfunction analysis. I close the paper by discussing ramifications of the presented approach for the philosophy of design and the philosophy of explanation. (shrink)

In this paper I apply the mechanistic account of explanation to engineering science. I discuss two ways in which this extension offers further development of the mechanistic view. First, functional individuation of mechanisms in engineering science proceeds by means of two distinct sub types of role function, behavior function and effect function, rather than role function simpliciter. Second, it offers refined assessment of the explanatory power of mechanistic explanations. It is argued that in the context of malfunction explanations of technical (...) systems, two key desiderata for mechanistic explanations, ‘completeness and specificity’ and ‘abstraction’, pull in opposite directions. I elaborate a novel explanatory desideratum to accommodate this explanatory context, dubbed ‘local specificity and global abstraction’, and further argue that it also holds for mechanistic explanations of malfunctions in the biological domain. The overall result is empirically-informed understanding of mechanistic explanation in engineering science, thus contributing to the ongoing project of understanding mechanistic explanation in novel or relatively unexplored domains. I illustrate these claims in terms of reverse engineering and malfunction explanations in engineering science. (shrink)

Current philosophical theorizing about technical functions is mainly focused on specifying conditions under which agents are justified in ascribing functions to technical artifacts. Yet, assessing the precise explanatory relevance of such function ascriptions is, by and large, a neglected topic in the philosophy of technical artifacts and technical functions. We assess the explanatory utility of ascriptions of technical functions in the following three explanation-seeking contexts: why was artifact x produced?, why does artifact x not have the expected capacity to ϕ?, (...) how does artifact x realize its capacity to ϕ? We argue that while function ascriptions serve a mere heuristic role in the first context, they have substantial explanatory leverage in the second and third context. In addition, we assess the relevance of function ascriptions in the context of engineering redesign. Here, function ascriptions also play a relevant role: they enable normative statements of the sort that component b functions better than component a. We unpack these claims by considering philosophical theories of technical functions, in particular the ICE theory, and engineering work on function ascription and explanation. We close the paper by relating our analysis to current debates on the explanatory power of mechanistic vis-à-vis functional explanations. (shrink)

In this paper we consider mechanistic explanations for biologic malfunctions. Drawing on Lipton’s work on difference making, we offer three reasons why one should distinguish i) mechanistic features that only make a difference to the malfunction one aims to explain, from ii) features that make a difference to both the malfunction and normal functioning. Recognition of the distinction is important for a) repair purposes, b) mechanism discovery, and c) understanding. This analysis extends current mechanistic thinking, which fails to appreciate the (...) distinction. We illustrate our contribution with a case on sleeping disorders as arising from disruptions of circadian rhythms. (shrink)

In this paper we assess the explanatory role of idealizations in ‘design explanations’, a type of functional explanation used in biology. In design explanations, idealizations highlight which factors make a difference to phenomena to be explained: hypothetical, idealized, organisms are invoked to make salient which traits of extant organisms make a difference to organismal fitness. This result negates the view that idealizations serve only pragmatic benefits, and complements the view that idealizations highlight factors that do not make a difference. This (...) analysis in particular strengthens the perspective that idealizations are means to highlight difference making factors, and identifies a novel, more direct role for idealizations in doing so. It thus offers a novel argument why in some explanatory contexts idealizations are in-eliminable. (shrink)

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

I aim to reconcile two apparently conflicting theses: (a) Everything that can be explained, can be explained in purely physical terms, that is, using the machinery of fundamental physics, and (b) some properties that play an explanatory role in the higher level sciences are irreducible in the strong sense that they are physically undefinable: their nature cannot be described using the vocabulary of physics. I investigate the contribution that physically undefinable properties typically make to explanations in the high-level sciences, and (...) I show that when they are explanatorily relevant, it is in virtue of their extension (or something close) alone. They are irreducible because physics cannot capture their nature; this is no obstacle, however, to physics' more or less capturing their extension, which is all that it need do to duplicate their explanatory power. In the course of the argument, I sketch the outlines of an account of the explanation of physically contingent regularities, such as the regularities found in most branches of biological inquiry, at the center of which is an account of the nature of contingent, empirical bridge principles. (shrink)

Philosophy and Phenomenological Research, Volume 99, Issue 3, Page 726-731, November 2019.

What do the words "ceteris paribus" add to a causal hypothesis, that is, to a generalization that is intended to articulate the consequences of a causal mechanism? One answer, which looks almost too good to be true, is that a ceteris paribus hedge restricts the scope of the hypothesis to those cases where nothing undermines, interferes with, or undoes the effect of the mechanism in question, even if the hypothesis's own formulator is otherwise unable to specify fully what might constitute (...) such undermining or interference. I will propose a semantics for causal generalizations according to which ceteris paribus hedges deliver on this promise, because the truth conditions for a causal generalization depend in part on the—perhaps unknown—nature of the mechanism whose consequences it is intended to describe. It follows that the truth conditions for causal hypotheses are typically opaque to the very scientists who formulate and test them. (shrink)

Given that an analysis of disposition ascription cannot be made in terms of a simple subjunctive conditional, we present a multiply qualified conditional analysis that places disposition ascription within an implicit fundamental causal conceptual typography within which a disposition ascription is embedded, framed, and understood. By placing the multiply qualified analysis within an implicit causal matrix involving a focal cause, pathway of influence, mechanism of action, contributing/partial cause, mediator, extrinsic moderator,, intrinsic moderator, and manifestation, we show how this analysis evades (...) counterexamples and arguments raised against the simple conditional analysis. We then indicate how the causal conceptual landscape provides a roadmap for unpacking and explicating parameters of the ceteris paribus qualifier to acquit the analysis of charges of being vacuous or irredeemably vague. (shrink)

In this essay, I propose a functionalist theory of grounding (functionalist-grounding). Specifically, I argue that grounding is a second-order phenomenon that is realized by relations that play the noncausal explanatoriness role. I also show that functionalist-grounding can deal with a powerful challenge. Appeals to explanatory unificationism have been made to argue that the success of noncausal explanations does not depend on the existence of grounding relations. Against this, I argue that a systematization involving functionalist-grounding is superior to its anti-relational counterpart.

Equilibrium explanations use an equilibrium to represent and explain a system’s dynamic behavior. They provide a system with the property of global stability: a system will converge towards and remain in equilibrium regardless of its initial conditions and dynamic process. Thus, equilibrium explanations are generally treated as non-causal explanations. There are two claims subsumed under that comprehensive thesis. The first claim is that equilibrium explanations do not identify any causes because a system with global stability resists manipulation. The second claim (...) is that even if equilibrium explanations do identify causes by manipulation, those causes are embedded in a system’s deeper, underlying structural relationships, and those causes are irrelevant to explaining a system’s behavior. Only the system’s structural relationships are relevant. But equilibrium explanations are not monolithic. I compare dynamic systems with multiple, competing equilibria to systems with a globally stable equilibrium. Equilibrium explanations of the former use intervention on a system’s initial conditions and dynamic process to manipulate equilibria, which identifies causes. Furthermore, a system’s initial conditions and dynamic process are relevant to explaining why one equilibrium is selected instead of another. I then apply these lessons to systems with a globally stable equilibrium and discuss when their corresponding equilibrium explanations have a proper role in the parent sciences. (shrink)

This paper argues that the philosophy of explanation can help inform core debates in value theory. Specifically, it argues that there is a consistent parallelism between the properties of explanation and the properties of justification such that one can reasonably infer that any property of explanation has a counterpart property of justification. Thus, by appealing to facts about the nature of explanation, one can derive various conclusions about the justifications offered by normative theorists. The paper illustrates this point by considering (...) a debate within political philosophy over whether inequality requires justification in a way that equality does not. Egalitarians typically presume an affirmative answer to this question. However, libertarian critics note that this justificatory asymmetry cannot be simply assumed without argument. This paper argues that, by appealing to the explanation-justification parallelism, one can resolve this debate in favor of the egalitarians, as there are two properties of explanation, the justificatory analogs of which vindicate the egalitarian presumption. (shrink)

Recent attempts to reconcile the ontic and epistemic approaches to explanation propose that our best explanations simply fulfill epistemic and ontic norms simultaneously. I aim to upset this armistice. Epistemic norms of attaining general and systematic explanations are, I argue, autonomous of ontic norms: they cannot be fulfilled simultaneously or in simple conjunction with ontic norms, and plausibly have priority over them. One result is that central arguments put forth by ontic theorists against epistemic theorists are revealed as not only (...) question-begging, but ultimately self-defeating. Another result is that a more nuanced reconciliation of the epistemic and ontic views is required: we should regard good explanatory practice as a dynamic process with distinct phases of epistemic and ontic success. (shrink)