A much-discussed idea in the causation literature is that it is preferable to invoke causes which are proportional to—neither too general nor too specific for—the effect. This article presents various ways of understanding this idea. In what sense are such causal claims ‘preferable’? And what is it for one event to be ‘proportional’ to another? In a companion article, ‘Proportionality in Causation, Part II: Applications and Challenges’, I discuss the principal applications of the resulting theories of proportionality, and the challenges (...) they face. (shrink)

Proportionality—the idea that causes are neither too general nor too specific for their effects—seems to recommend implausibly disjunctive causes (McGrath, 1998 ; Shapiro & Sober, 2012 ; Franklin-Hall, 2016 ). I argue that this problem should be avoided by appeal to the notion of cohesion. I propose an account of cohesion in terms of the similarity structure of property-spaces, argue that it is not objectionably mysterious, and that alternative approaches—based on naturalness, interventionism, and contrastivism—are inadequate without appeal to it. In (...) an appendix, I show how my proposal can be perspicuously formalized by adapting structural equation models. (shrink)

Our concern in this paper lies with a common argument from racial discrimination to realism about races: some people are discriminated against for being members of a particular race (i.e., racial discrimination exists), so some people must be members of that race (i.e., races exist). Error theorists have long responded that we can explain racial discrimination in terms of racial attitudes alone, so we need not explain it in terms of race itself. But to date there has been little detailed (...) discussion of whether it is better to explain racial discrimination in terms of race or in terms of racial attitudes alone. Our goal is to offer a novel and detailed argument in defense of explaining racial discrimination in terms of racial attitudes alone, by attending to the neglected phenomenon of misperception discrimination, which involves differential treatment due to misperceived race. We argue that the discriminatory action in misperception cases must be explained in the same way as cases where (according to the realist) the victim’s race is accurately perceived. Thus, the victim’s actual race cannot provide the best explanation. The main upshot of our argument is that explanatory arguments from racial discrimination to realism about race fail. (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.

I raise two objections against Christian List and Peter Menzies' influential account of high-level causation. Improving upon some of Stephen Yablo's earlier work, I develop an alternative theory which evades both objections. The discussion calls into question List and Menzies' main contention, namely, that the exclusion principle, applied to difference-making, is false.

Contemporary natural-language semantics began with the assumption that the meaning of a sentence could be modeled by a single truth condition, or by an entity with a truth-condition. But with the recent explosion of dynamic semantics and pragmatics and of work on non- truth-conditional dimensions of linguistic meaning, we are now in the midst of a shift away from a truth-condition-centric view and toward the idea that a sentence’s meaning must be spelled out in terms of its various roles in (...) conversation. This communicative turn in semantics raises historical questions: Why was truth-conditional semantics dominant in the first place, and why were the phenomena now driving the communicative turn initially ignored or misunderstood by truth-conditional semanticists? I offer a historical answer to both questions. The history of natural-language semantics—springing from the work of Donald Davidson and Richard Montague—began with a methodological toolkit that Frege, Tarski, Carnap, and others had created to better understand artificial languages. For them, the study of linguistic meaning was subservient to other explanatory goals in logic, philosophy, and the foundations of mathematics, and this subservience was reflected in the fact that they idealized away from all aspects of meaning that get in the way of a one-to-one correspondence between sentences and truth-conditions. The truth-conditional beginnings of natural- language semantics are best explained by the fact that, upon turning their attention to the empirical study of natural language, Davidson and Montague adopted the methodological toolkit assembled by Frege, Tarski, and Carnap and, along with it, their idealization away from non-truth-conditional semantic phenomena. But this pivot in explana- tory priorities toward natural language itself rendered the adoption of the truth-conditional idealization inappropriate. Lifting the truth-conditional idealization has forced semanticists to upend the conception of linguistic meaning that was originally embodied in their methodology. (shrink)

The concept of explanation is central to scientific practice. However, scientists explain phenomena in very different ways. That is, there are many different kinds of explanation; e.g. causal, mechanistic, statistical, or equilibrium explanations. In light of the myriad kinds of explanation identified in the literature, most philosophers of science have adopted some kind of explanatory pluralism. While pluralism about explanation seems plausible, it faces a dilemma Explanation beyond causation, Oxford University Press, Oxford, pp 39–56, 2018). Either there is nothing that (...) unifies all instances of scientific explanation that makes them count as explanations, or there is some set of unifying features, which seems incompatible with explanatory pluralism. Different philosophers have adopted different horns of this dilemma. Some argue that no unified account of explanation is possible. Others suggest that there is a set of necessary features that can unify all explanations under a single account Explanation beyond causation, Oxford University Press, Oxford, pp 74–95, 2018; Strevens in Depth: an account of scientific explanation, Harvard University Press, Cambridge, 2008). In this paper, we argue that none of the features identified by existing accounts of explanation are necessary for all explanations. However, we argue that a unified account can still be provided that accommodates pluralism. This can be accomplished, we argue, by reconceiving of scientific explanation as a cluster concept: there are multiple subsets of features that are sufficient for providing an explanation, but no single feature is necessary for all explanations. Reconceiving of explanation as a cluster concept not only accounts for the diversity of kinds of explanations, but also accounts for the widespread disagreement in the explanation literature and enables explanatory pluralism to avoid Pincock’s dilemma. (shrink)

Our approach aims at accounting for causal claims in terms of how the physical states of the underlying dynamical system evolve with time. Causal claims assert connections between two sets of physicals states—their truth depends on whether the two sets in question are genuinely connected by time evolution such that physical states from one set evolve with time into the states of the other set. We demonstrate the virtues of our approach by showing how it is able to account for (...) typical causes, causally relevant factors, being ‘the’ cause, and cases of overdetermination and causation by absences. (shrink)

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)

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...

Despite their importance in the history of philosophy and in particular in the work of Aristotle and Kant, mental capacities have been neglected in recent philosophical work. By contrast, the notion of a capacity is deeply entrenched in psychology and the brain sciences. Driven by the idea that a cognitive system has the capacity it does in virtue of its internal components and their organization, it is standard to appeal to capacities in cognitive psychology. The main benefit of invoking capacities (...) in an account of the mind is that it allows for an elegant counterfactual analysis of mental states: it allows us to analyze mental states on three distinct yet interrelated levels. A first level of analysis pertains to the function of mental capacities. A second level of analysis pertains to the mental capacities employed, irrespective of the context in which they are employed. A third level of analysis pertains to the mental capacities employed, taking into account the context in which they are employed. This paper develops an account of perceptual capacities. This account involves an analysis of their function, their individuation and possession conditions, the relation between perceptual capacities and their employment, as well as their informational and neural base conditions. (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)

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)

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)

In this paper, we argue that rather than exclusively focusing on trying to determine if an idealized model fits a particular account of scientific explanation, philosophers of science should also work on directly analyzing various explanatory schemas that reveal the steps and justification involved in scientists’ use of highly idealized models to formulate explanations. We develop our alternative methodology by analyzing historically important cases of idealized statistical modeling that use a three-step explanatory schema involving idealization, mathematical operation, and explanatory interpretation.

It is natural to think of causes as difference-makers. What exact difference causes make, however, is an open question. In this paper, I argue that the right way of understanding difference-making is in terms of causal processes: causes make a difference to a causal process that leads to the effect. I will show that this way of understanding difference-making nicely captures the distinction between causing an outcome and helping determine how the outcome happens and, thus, explains why causation is not (...) transitive. Moreover, the theory handles tricky cases that are problematic for competing accounts of difference-making. (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 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)

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)

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)

From Leibniz to Krauss philosophers and scientists have raised the question as to why there is something rather than nothing. Why-questions request a type of explanation and this is often thought to include a deductive component. With classical logic in the background only trivial answers are forthcoming. With free logics in the background, be they of the negative, positive or neutral variety, only question-begging answers are to be expected. The same conclusion is reached for the modal version of the Question, (...) namely ‘Why is there something contingent rather than nothing contingent?’. The categorial version of the Question, namely ‘Why is there something concrete rather than nothing concrete?’, is also discussed. The conclusion is reached that deductive explanations are question-begging, whether one works with classical logic or positive or negative free logic. I also look skeptically at the prospects of giving causal-counterfactual or probabilistic answers to the Question, although the discussion of the options is less comprehensive and the conclusions are more tentative. The meta-question, viz. ‘Should we not stop asking the Question’, is accordingly tentatively answered affirmatively. (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)

Most philosophical accounts on scientific theories are affected by three dogmas or ingrained attitudes. These dogmas have led philosophers to choose between analyzing the internal structure of theories or their historical evolution. In this paper, I turn these three dogmas upside down. I argue (i) that mathematical practices are not epistemically neutral, (ii) that the morphology of theories can be very complex, and (iii) that one should view theoretical knowledge as the combination of internal factors and their intrinsic historicity.

It is often claimed that the greatest value of the Bayesian framework in cognitive science consists in its unifying power. Several Bayesian cognitive scientists assume that unification is obviously linked to explanatory power. But this link is not obvious, as unification in science is a heterogeneous notion, which may have little to do with explanation. While a crucial feature of most adequate explanations in cognitive science is that they reveal aspects of the causal mechanism that produces the phenomenon to be (...) explained, the kind of unification afforded by the Bayesian framework to cognitive science does not necessarily reveal aspects of a mechanism. Bayesian unification, nonetheless, can place fruitful constraints on causal–mechanical explanation. 1 Introduction2 What a Great Many Phenomena Bayesian Decision Theory Can Model3 The Case of Information Integration4 How Do Bayesian Models Unify?5 Bayesian Unification: What Constraints Are There on Mechanistic Explanation?5.1 Unification constrains mechanism discovery5.2 Unification constrains the identification of relevant mechanistic factors5.3 Unification constrains confirmation of competitive mechanistic models6 ConclusionAppendix. (shrink)

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)

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)

One of the central aims of science is explanation: scientists seek to uncover why things happen the way they do. This chapter addresses what kinds of explanations are formulated in biology, how explanatory aims influence other features of the field of biology, and the implications of all of this for biology education. Philosophical treatments of scientific explanation have been both complicated and enriched by attention to explanatory strategies in biology. Most basically, whereas traditional philosophy of science based explanation on derivation (...) from scientific laws, there are many biological explanations in which laws play little or no role. Instead, the field of biology is a natural place to turn for support for the idea that causal information is explanatory. Biology has also been used to motivate mechanistic accounts of explanation, as well as criticisms of that approach. Ultimately, the most pressing issue about explanation in biology may be how to account for the wide range of explanatory styles encountered in the field. This issue is crucial, for the aims of biological explanation influence a variety of other features of the field of biology. Explanatory aims account for the continued neglect of some central causal factors, a neglect that would otherwise be mysterious. This is linked to the persistent use of models like evolutionary game theory and population genetic models, models that are simplified to the point of unreality. These explanatory aims also offer a way to interpret many biologists’ total commitment to one or another methodological approach, and the intense disagreements that result. In my view, such debates are better understood as arising not from different theoretical commitments, but commitments to different explanatory projects. Biology education would thus be enriched by attending to approaches to biological explanation, as well as the unexpected ways that these explanatory aims influence other features of biology. I suggest five lessons for teaching about explanation in biology that follow from the considerations of this chapter. (shrink)

What are scientific theories and how should they be represented? In this article, I propose a causal–structural account, according to which scientific theories are to be represented as sets of interrelated causal and credal nets. In contrast with other accounts of scientific theories (such as Sneedian structuralism, Kitcher’s unificationist view, and Darden’s theory of theoretical components), this leaves room for causality to play a substantial role. As a result, an interesting account of explanation is provided, which sheds light on explanatory (...) unification within a causalist framework. The theory of classical genetics is used as a case study. 1 Introduction2 The Theory of Classical Genetics3 Three Philosophical Accounts of the Theory of Classical Genetics3.1 The structuralist account3.2 Kitcher’s unificationism3.3 Darden and theory change in science4 A Common Lacuna: Where is Causality?5 Woodward’s Interventionist Account of Causation6 Causal Bayes Nets and Their Interrelations6.1 Causal Bayes nets6.2 Relations among causal nets6.3 Credal nets and their interrelations7 The Theory of the Gene and its Causal Graph8 A First Exemplar: Stem Length in Pea Plants8.1 Three crosses on stem length in pea plants8.2 The causal graph for stem length in pea plants8.3 Morgan’s explanatory principles and the credal net for stem length in pea plants9 Explaining Mendel’s Crosses: A Causal–Structural Account10 Monohybrid Crosses with Complete Dominance11 Exemplars,Explanatory Patterns, Generic Credal Nets, and Mechanism Schemas12 Incomplete Dominance13 Anomalies14 Multi-hybrid Crosses with Independent Assortment15 Multi-hybrid Crosses with Linkage and Crossing-Over16 Double Crossing-Over and the Linear Order of the Gene17 Causal–Structural Explanation18 Explanatory Unification19 Concluding Remarks. (shrink)

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)

Cancer is not one, but many diseases, and each is a product of a variety of causes acting (and interacting) at distinct temporal and spatial scales, or “levels” in the biological hierarchy. In part because of this diversity of cancer types and causes, there has been a diversity of models, hypotheses, and explanations of carcinogenesis. However, there is one model of carcinogenesis that seems to have survived the diversification of cancer types: the multi-stage model of carcinogenesis. This paper examines the (...) history of the multistage theory, and uses the theory as a case study in the limits and goals of unification as a theoretical virtue, comparing and contrasting it with “integrative” research. (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)

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)

Cases of overdetermination or preemption continue to play an important role in the debate about the proper interpretation of causal claims of the form "C was a cause of E". I argue that the best treatment of preemption cases is given by Mackie's venerable INUS account of causal claims. The Mackie account suffers, however, from problems of its own. Inspired by its ability to handle preemption, I propose a dramatic revision to the Mackie account – one that Mackie himself would (...) certainly have rejected – to solve these difficulties. The result is, I contend, a very attractive account of singular causal claims. (shrink)

General Relativity and the Standard Model often are touted as the most rigorously and extensively confirmed scientific hypotheses of all time. Nonetheless, these theories appear to have consequences that are inconsistent with evidence about phenomena for which, respectively, quantum effects and gravity matter. This paper suggests an explanation for why the theories are not disconfirmed by such evidence. The key to this explanation is an approach to scientific hypotheses that allows their actual content to differ from their apparent content. This (...) approach does not appeal to ceteris-paribus qualifiers or counterfactuals or similarity relations. And it helps to explain why some highly idealized hypotheses are not treated in the way that a thoroughly refuted theory is treated but instead as hypotheses with limited domains of applicability. (shrink)

The three cardinal aims of science are prediction, control, and explanation; but the greatest of these is explanation. Also the most inscrutable: prediction aims at truth, and control at happiness, and insofar as we have some independent grasp of these notions, we can evaluate science’s strategies of prediction and control from the outside. Explanation, by contrast, aims at scientific understanding, a good intrinsic to science and therefore something that it seems we can only look to science itself to explicate.

The optimality approach to modeling natural selection has been criticized by many biologists and philosophers of biology. For instance, Lewontin (1979) argues that the optimality approach is a shortcut that will be replaced by models incorporating genetic information, if and when such models become available. In contrast, I think that optimality models have a permanent role in evolutionary study. I base my argument for this claim on what I think it takes to best explain an event. In certain contexts, optimality (...) and game-theoretic models best explain some central types of evolutionary phenomena. ‡Thanks to Michael Friedman, Helen Longino, Michael Weisberg, and especially Elliott Sober for comments on earlier drafts of this paper. †To contact the author, please write to: Department of Philosophy, Stanford University, Stanford, CA 94305-2155; e-mail: [email protected]. (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)

In this paper, I argue that unification is neither necessary nor sufficient for explanation. Focusing on the versions of the unificationist theory of explanation of Kitcher and of Schurz and Lambert, I establish three theses. First, Kitcher’s criterion of unification is vitiated by the fact that it entails that every proposition can be explained by itself, a flaw that it is unable to overcome. Second, because neither Kitcher’s theory nor that of Schurz and Lambert can solve the problems of asymmetry (...) and accidental generalizations, it follows that unification is not sufficient to ground explanation. Third, some good explanations are disunifying, which entails that unification is not necessary for explanation either. (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)

Ecological neutral theory has been controversial as an alternative to niche theory for explaining community structure. Neutral theory, which explains community structure in terms of ecological drift, is frequently charged with being unrealistic, but commentators have usually not provided an account of theory or model realism. In this paper, I propose a framework for comparing the “realism” or accuracy of alternative theories within a domain with respect to the extent to which the theories abstract and idealize. Using this framework I (...) argue, contrary to most previous commentators, that neutral and niche theories are similarly realistic. Realism cannot provide a basis for accepting or rejecting either type of theory; instead, community ecologists should continue working with a plurality of models. While theoretical unification may become possible, we should treat a plurality of complementary, partial models as the expected situation within community ecology. (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)

This paper provides a conceptual framework that allows for distinguishing between different kinds of generalisation and applicability. It is argued that generalising models may bring epistemic benefits. They do so if they show that restrictive and unrealistic assumptions do not threaten the credibility of results derived from models. There are two different notions of applicability, generic and specific, which give rise to three different kinds of generalizations. Only generalising a result brings epistemic benefits concerning the truth of model components or (...) results. Abstracting the model and applying the model into new systems are not intrinsically epistemically beneficial in this way. The Dixit-Stiglitz model of monopolistic competition is used as an illustration. (shrink)

Many phenomena in the natural world are complex, so scientists study them through simplified and idealised models. Philosophers of science have sought to explain how these models relate to the world. On most accounts, models do not represent the world directly, but through target systems. However, our knowledge of target systems is incomplete. First, what is the process by which target systems come about? Second, what types of entity are they? I argue that the basic conception of target systems, on (...) which other conceptions depend, is as parts of the world. I outline the process of target system specification and show that it is a crucial step in modelling. I also develop an account of target system evaluation, based on aptness. Paying close attention to target system specification and evaluation can help scientists minimise the frequency and extent of mistakes, when they are using models to investigate phenomena in complex real-world systems. (shrink)

In this paper, I first outline the view developed in my recent book on the role of idealization in scientific understanding. I discuss how this view leads to the recognition of a number of kinds of variability among scientific representations, including variability introduced by the many different aims of scientific projects. I then argue that the role of idealization in securing understanding distances understanding from truth, but that this understanding nonetheless gives rise to scientific knowledge. This discussion will clarify how (...) my view relates to three other recent books on understanding by Henk de Regt, Catherine Elgin, and Kareem Khalifa. (shrink)

This dissertation focuses on teleology and functions in biology. More precisely, it focuses on the scientific legitimacy of teleofunctional attributions and explanations in biology. It belongs to a multi-faceted debate that can be traced back to at least the 1970s. One aspect of the debate concerns the naturalization of functions. Most authors try to reduce, translate or explain functions and teleology in terms of efficient causes so that they find their place in the framework of the natural sciences. Our approach (...) here is radically different, as we question the premise that teleological explanations are disguised causal explanations. On the contrary, we defend that they are acceptable in natural sciences and in biology in particular. We challenge the idea that teleological explanations are immature causal explanations, as well as the idea that teleology and functions are some sort of intentional explanations. We therefore reject the accusations of anthropomorphism, vitalism and finalism. On the contrary, we defend that teleology, causality and intentionality correspond to different, autonomous and complementary modes of representation of the outside world. -/- ———[FRANÇAIS]——— -/- Ce travail de thèse porte sur la téléologie et les fonctions en biologie. Plus précisément, il porte sur la légitimité scientifique des attributions et des explications téléofonctionnelles en biologie. Il s’inscrit dans le cadre d’un débat à plusieurs facettes que l’on peut faire remonter au moins jusqu’aux années 1970 et qui est encore très actif aujourd’hui. L’un des aspects du débat porte sur la naturalisation des fonctions, c’est-à-dire sur la manière de les réduire, de les traduire ou de les expliciter en termes de causes efficientes de sorte qu’elles trouvent leur place dans le cadre des sciences de la nature. Notre approche ici est radicalement différente, car nous remettons en question la prémisse selon laquelle les explications téléologiques seraient des explications causales déguisées. Nous défendons au contraire qu’elles sont acceptables en tant que telles aussi bien de façon générale que dans le domaine scientifique et en particulier en biologie. De façon générale, nous remettons en question l’idée selon laquelle la pensée téléologique serait une pensée causale immature, ainsi que sa dépendance présumée vis-à-vis de la psychologie, c’est-à-dire de l’intentionnalité. Nous rejetons donc les accusations d’anthropomorphisme, de vitalisme et de finalisme formulées contre elle. Nous défendons au contraire que la téléologie, la causalité et l’intentionnalité correspondent à des modes différents, autonomes et complémentaires de représentation du monde extérieur. (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)

Resumen: La capacidad unificadora de una teoría científica es un rasgo usualmente contemplado a la hora de evaluar su adecuación. Kitcher ha elucidado satisfactoriamente tal noción mediante su enfoque de los patrones explicativos. Sin embargo, su perspectiva adolece de ciertas carencias. Concretamente, sostendremos que el requisito de rigurosidad de los patrones para evaluar la capacidad unificadora debe ser repensado, pues atenta contra la heterogeneidad característica de las diferentes aplicaciones de teorías unificadoras. A su vez, mostraremos cómo estas dificultades bien pueden (...) ser subsanadas desde el marco del estructuralismo metateórico sin por ello resignar ninguna de las acertadas intuiciones de Kitcher. -/- Palabras clave: Explicación, Kitcher, estructuralismo metateórico, unificación, unificación espuria. -/- Abstract: Kitcher has satisfactorily explicated unification using his particular approach to scientific explanation. However, we believe that his perspective has certain problems, which have been inherited by more recent approaches to the topic. Specifically, the requirement of stringency of patterns that Kitcher proposes to determine the unifying power of an explanatory pattern undermines the typical and peculiar heterogeneity we can find in different applications of unifying theories. We will show how this topic can be better addressed by the perspective built by metatheoretical structuralism without sacrificing any of Kitcher’s correct intuitions. -/- Keywords: Explanation, Kitcher, metatheoretical structuralism, spurious unification, unification. (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.