Scientific realists claim that the best of successful rival theories is (approximately) true. Relative realists object that we cannot make the absolute judgment that a theory is successful, and that we can only make the relative judgment that it is more successful than its competitor. I argue that this objection is undermined by the cases in which empirical equivalents are successful. Relative realists invoke the argument from a bad lot to undermine scientific realism and to support relative realism. In response, (...) I construct the argument from double spaces. It is similar to the argument from a bad lot, but threatens many philosophical inferences, including relative realists’ inference from comparative success to comparative truth. (shrink)

__In this paper I investigate unification as a virtue of explanation. I the first part of the paper I give a brief exposition of the unification account of Schurz and Lambert and Schurz. I illustrate the advantages of this account in comparison to the older unification accounts of Friedman and Kitcher. In the second part I discuss several comments and objections to the Schurz-Lambert account that were raised by Weber and van Dyck, Gijsberg and de Regt. In the third and (...) final part, I argue that explanation should be understood as a prototype concept which contains nomic expectability, causality and unification as prototypical virtues of explanations, although none of these virtues provides a sufficient and necessary "defining condition" of explanation. (shrink)

Stemming from the realization of the importance of the role of explanation in the science classroom, the Next Generation Science Standards call for appropriately supporting students to learn science, argue from evidence, and provide explanations. Despite the ongoing emphasis on explanations in the science classroom, there seems to be no well-articulated framework that supports students in constructing adequate scientific explanations, or that helps teachers assess student explanations. Our motivation for this article is twofold: First, we think that the ways in (...) which researchers in science education have studied scientific explanation are, at best, leaves much to be desired and, at worst, simply incomplete. Second, we believe that research about the teaching and learning of explanation in science classrooms must be guided by explicit models or frameworks that specify elements involved in constructing explanations particularly applicable to science. More importantly, we think that the development of such models or guidelines should be based on theoretical and philosophical foundations. In order to develop these frameworks or guidelines, we first outline and clarify models of scientific explanation developed by philosophers of science over the last few decades. In the second section of this article, we present a more recent philosophical work on scientific explanation, the pragmatic approach to studying scientific explanations. This approach suggests a toolbox for analyzing scientists’ scientific explanations, which provides a useful instrument to science education. In Section 3, we discuss the ways by which the previous two sections are useful in developing a K-12 scientific explanation schema. Implications for future research on students’ explanations are discussed. (shrink)

We argue that neuroeconomics should be a mechanistic science. We defend this view as preferable both to a revolutionary perspective, according to which classical economics is eliminated in favour of neuroeconomics, and to a classical economic perspective, according to which economics is insulated from facts about psychology and neuroscience. We argue that, like other mechanistic sciences, neuroeconomics will earn its keep to the extent that it either reconfigures how economists think about decision-making or how neuroscientists think about brain mechanisms underlying (...) behaviour. We discuss some ways that the search for mechanisms can bring about such top-down and bottom-up revision, and we consider some examples from the recent neuroeconomics literature of how varieties of progress of this sort might be achieved. (shrink)

Evidence-based medicine (EBM) makes use of explicit procedures for grading evidence for causal claims. Normally, these procedures categorise evidence of correlation produced by statistical trials as better evidence for a causal claim than evidence of mechanisms produced by other methods. We argue, in contrast, that evidence of mechanisms needs to be viewed as complementary to, rather than inferior to, evidence of correlation. In this paper we first set out the case for treating evidence of mechanisms alongside evidence of correlation in (...) explicit protocols for evaluating evidence. Next we provide case studies which exemplify the ways in which evidence of mechanisms complements evidence of correlation in practice. Finally, we put forward some general considerations as to how the two sorts of evidence can be more closely integrated by EBM. (shrink)

ABSTRACT The exclusion problem is meant to show that non-reductive physicalism leads to epiphenomenalism: if mental properties are not identical with physical properties, then they are not causally efficacious. Defenders of a difference-making account of causation suggest that the exclusion problem can be solved because mental properties can be difference-making causes of physical effects. Here, we focus on what we dub an incompatibilist implementation of this general strategy and argue against it from a non-reductive physicalist perspective. Specifically, we argue that (...) incompatibilism undermines either the non-reductionist or the physicalist aspirations of non-reductive physicalism. (shrink)

Randomized controlled trials (RCTs) are widely taken as the gold standard for establishing causal conclusions. Ideally conducted they ensure that the treatment ‘causes’ the outcome—in the experiment. But where else? This is the venerable question of external validity. I point out that the question comes in two importantly different forms: Is the specific causal conclusion warranted by the experiment true in a target situation? What will be the result of implementing the treatment there? This paper explains how the probabilistic theory (...) of causality implies that RCTs can establish causal conclusions and thereby provides an account of what exactly that causal conclusion is. Clarifying the exact form of the conclusion shows just what is necessary for it to hold in a new setting and also how much more is needed to see what the actual outcome would be there were the treatment implemented. (shrink)

In this paper, I consider the relationship between Inference to the Best Explanation and Bayesianism, both of which are well-known accounts of the nature of scientific inference. In Sect. 2, I give a brief overview of Bayesianism and IBE. In Sect. 3, I argue that IBE in its most prominently defended forms is difficult to reconcile with Bayesianism because not all of the items that feature on popular lists of “explanatory virtues”—by means of which IBE ranks competing explanations—have confirmational import. (...) Rather, some of the items that feature on these lists are “informational virtues”—properties that do not make a hypothesis \ more probable than some competitor \ given evidence E, but that, roughly-speaking, give that hypothesis greater informative content. In Sect. 4, I consider as a response to my argument a recent version of compatibilism which argues that IBE can provide further normative constraints on the objectively correct probability function. I argue that this response does not succeed, owing to the difficulty of defending with any generality such further normative constraints. Lastly, in Sect. 5, I propose that IBE should be regarded, not as a theory of scientific inference, but rather as a theory of when we ought to “accept” H, where the acceptability of H is fixed by the goals of science and concerns whether H is worthy of commitment as research program. In this way, IBE and Bayesianism, as I will show, can be made compatible, and thus the Bayesian and the proponent of IBE can be friends. (shrink)

I examine an intuitive property of folk-psychological explanations I call self-sufficiency. I argue that individualism cannot honor this property and work toward distilling an account of psychological explanation that does honor it, given some fairly standard assumptions. In doing so, my preference for an Externalist individuation of intentional state will emerge unambiguously. The assumptions I rely on are fairly standard but not uncontroversial. Yet not always do I attempt to defend them from objections. My goal is an account of folk (...) psychology consistent with our every-day practices rather than the deduction of an idealized psychology from first principles. I conclude with some applications offered as evidence that the goal was achieved. (shrink)

Contributing to the recent debate on whether or not explanations ought to be differentiated from arguments, this article argues that the distinction matters to science education. I articulate the distinction in terms of explanations and arguments having to meet different standards of adequacy. Standards of explanatory adequacy are important because they correspond to what counts as a good explanation in a science classroom, whereas a focus on evidence-based argumentation can obscure such standards of what makes an explanation explanatory. I provide (...) further reasons for the relevance of not conflating explanations with arguments (and having standards of explanatory adequacy in view). First, what guides the adoption of the particular standards of explanatory adequacy that are relevant in a scientific case is the explanatory aim pursued in this context. Apart from explanatory aims being an important aspect of the nature of science, including explanatory aims in classroom instruction also promotes students seeing explanations as more than facts, and engages them in developing explanations as responses to interesting explanatory problems. Second, it is of relevance to science curricula that science aims at intervening in natural processes, not only for technological applications, but also as part of experimental discovery. Not any argument enables intervention in nature, as successful intervention specifically presupposes causal explanations. Students can fruitfully explore in the classroom how an explanatory account suggests different options for intervention. (shrink)

Whereas an inference (deductive as well as inductive) is usually viewed as being valid in virtue of its argument form, the present paper argues that scientific reasoning is material inference, i.e., justified in virtue of its content. A material inference is licensed by the empirical content embodied in the concepts contained in the premises and conclusion. Understanding scientific reasoning as material inference has the advantage of combining different aspects of scientific reasoning, such as confirmation, discovery, and explanation. This approach explains (...) why these different aspects (including discovery) can be rational without conforming to formal schemes, and why scientific reasoning is local, i.e., justified only in certain domains and contingent on particular empirical facts. The notion of material inference also fruitfully interacts with accounts of conceptual change and psychological theories of concepts. (shrink)

This essay analyzes and develops recent views about explanation in biology. Philosophers of biology have parted with the received deductive-nomological model of scientific explanation primarily by attempting to capture actual biological theorizing and practice. This includes an endorsement of different kinds of explanation (e.g., mathematical and causal-mechanistic), a joint study of discovery and explanation, and an abandonment of models of theory reduction in favor of accounts of explanatory reduction. Of particular current interest are philosophical accounts of complex explanations that appeal (...) to different levels of organismal organization and use contributions from different biological disciplines. The essay lays out one model that views explanatory integration across different disciplines as being structured by scientific problems. I emphasize the philosophical need to take the explanatory aims pursued by different groups of scientists into account, as explanatory aims determine whether different explanations are competing or complementary and govern the dynamics of scientific practice, including interdisciplinary research. I distinguish different kinds of pluralism that philosophers have endorsed in the context of explanation in biology, and draw several implications for science education, especially the need to teach science as an interdisciplinary and dynamic practice guided by scientific problems and explanatory aims. (shrink)

Christopher Hitchcocks discussion of my use of screening-off in analyzing the causal process of natural selection raises some interesting issues to which I am pleased to reply. The bulk of his article is devoted to some fairly general points in the theory of explanation. In particular, he questions whether or not my point that phenotype screens off genotype from reproductive success (in cases of organismic selection) supports my claim that the explanation of differential reproductive success should be in terms of (...) phenotypic differences, not genotypic differences. I will respond to this and show why the two supposed counter-examples to my position fail. (shrink)

In this paper I critically examine the Generality Problem and argue that it does not succeed as an objection to reliabilism. Although those who urge the Generality Problem are correct in claiming that any process token can be given indefinitely many descriptions that pick out indefinitely many process types, they are mistaken in thinking that reliabilists have no principled way to distinguish between relevant and irrelevant process types.

Non-skeptical robust realists about normativity, mathematics, or any other domain of non- causal truths are committed to a correlation between their beliefs and non- causal, mind-independent facts. Hartry Field and others have argued that if realists cannot explain this striking correlation, that is a strong reason to reject their theory. Some consider this argument, known as the Benacerraf–Field argument, as the strongest challenge to robust realism about mathematics, normativity, and even logic. In this article I offer two closely related accounts (...) for the type of explanation needed in order to address Field's challenge. I then argue that both accounts imply that the striking correlation to which robust realists are committed is explainable, thereby discharging Field's challenge. Finally, I respond to some objections and end with a few unresolved worries. (shrink)

This paper replies to criticisms of the author's accounts of intending ("journal of philosophy", 1973), wanting ("philosophical studies", 1973), and common-sense explanations of intentional actions; and it extends the nomological theory of intentional action developed in those and other articles. the paper argues, negatively, that theoretical construct accounts of intentional concepts do not entail implausible views of self-knowledge, nor assimilate reasons to mechanical causes; and, positively, that both the way in which reasons render intelligible the actions they explain and the (...) apparently non-contingent relation certain reasons bear to the actions they explain can be accommodated by a sound nomological theory of intentional action. (shrink)

Deep learning (DL) has become increasingly central to science, primarily due to its capacity to quickly, efficiently, and accurately predict and classify phenomena of scientific interest. This paper seeks to understand the principles that underwrite scientists’ epistemic entitlement to rely on DL in the first place and argues that these principles are philosophically novel. The question of this paper is not whether scientists can be justified in trusting in the reliability of DL. While today’s artificial intelligence exhibits characteristics common to (...) both scientific instruments and scientific experts, this paper argues that the familiar epistemic categories that justify belief in the reliability of instruments and experts are distinct, and that belief in the reliability of DL cannot be reduced to either. Understanding what can justify belief in AI reliability represents an occasion and opportunity for exciting, new philosophy of science. (shrink)

Surprisingly, many ethical realists and anti-realists, naturalists and not, all accept some version of the following normative appeal to the natural (NAN): evaluative and normative facts hold solely in virtue of natural facts, where their naturalness is part of what fits them for the job. This paper argues not that NAN is false but that NAN has no adequate non-parochial justification (a justification that relies only on premises which can be accepted by more or less everyone who accepts NAN) to (...) back up this consensus. I show that we cannot establish versions of NAN which are interesting in their own right (and not merely as instances of a general naturalistic ontology) by appealing to the nature of natural properties or the kind of in-virtue-of relation to which NAN refers, plus other plausible nonparochial assumptions. On the way, I distinguish different types of 'in virtue of claims. I conclude by arguing that the way in which assessment of meta-ethical hypotheses is theory-dependent predicts the failure of non-parochial justifications of NAN. (shrink)

Do component forces exist in conjoined circumstances? Cartwright (1980) says no; Creary (1981) says yes. I'm inclined towards Cartwright's side in this matter, but find several problems with her argumentation. My primary aim here is to present a better, distinctly causal, argument against component forces: very roughly, I argue that the joint posit of component and resultant forces in conjoined circumstances gives rise to a threat of causal overdetermination, avoidance of which best proceeds via eliminativism about component forces. A secondary (...) aim is to show that rejecting component forces does not require, pace Cartwright, rejecting certain attractive theses about what laws of nature express and the role such laws play in scientific explanations. (shrink)

Our goal in this paper is to experimentally investigate whether folk conceptions of explanation are psychologistic. In particular, are people more likely to classify speech acts as explanations when they cause understanding in their recipient? The empirical evidence that we present suggests this is so. Using the side-effect effect as a marker of mental state ascriptions, we argue that lay judgments of explanatory status are mediated by judgments of a speaker’s and/or audience’s mental states. First, we show that attributions of (...) both understanding and explanation exhibit a side-effect effect. Next, we show that when the speaker’s and audience’s level of understanding is stipulated, the explanation side-effect effect goes away entirely. These results not only extend the side-effect effect to attributions of understanding, they also suggest that attributions of explanation exhibit a side-effect effect because they depend upon attributions of understanding, supporting the idea that folk conceptions of explanation are psychologistic. (shrink)

Some non-reductionists claim that so-called ‘exclusion arguments’ against their position rely on a notion of causal sufficiency that is particularly problematic. I argue that such concerns about the role of causal sufficiency in exclusion arguments are relatively superficial since exclusionists can address them by reformulating exclusion arguments in terms of physical sufficiency. The resulting exclusion arguments still face familiar problems, but these are not related to the choice between causal sufficiency and physical sufficiency. The upshot is that objections to the (...) notion of causal sufficiency can be answered in a straightforward fashion and that such objections therefore do not pose a serious threat to exclusion arguments. (shrink)

In Salmon's discussion of his account of statistical relevance and statistical explanation there is a peculiarity in the selection of examples. Where he wishes to show that statistical accounts are reasonably treated as explanatory, he draws examples from the social sciences, such as juvenile delinquency. But when he explains the concept of 'causal' relevance, the examples are selected from the natural sciences. This conceals difficulties with salmon's account of causality in the face of multiple causes such as are characteristic of (...) the social sciences. Salmon's account is shown not to escape difficulties associated with Simon's earlier approach. (shrink)

The article begins by describing two longstanding problems associated with direct inference. One problem concerns the role of uninformative frequency statements in inferring probabilities by direct inference. A second problem concerns the role of frequency statements with gerrymandered reference classes. I show that past approaches to the problem associated with uninformative frequency statements yield the wrong conclusions in some cases. I propose a modification of Kyburg’s approach to the problem that yields the right conclusions. Past theories of direct inference have (...) postponed treatment of the problem associated with gerrymandered reference classes by appealing to an unexplicated notion of projectability . I address the lacuna in past theories by introducing criteria for being a relevant statistic . The prescription that only relevant statistics play a role in direct inference corresponds to the sort of projectability constraints envisioned by past theories. (shrink)

“The Explanatory Gap” is a label for the idea that we cannot explain consciousness in terms of brain activity. There are many different formulations of the explanatory gap, but all discussion about it assumes that there is only one gap, which consists of the absence of a deductive explanation. This assumption is mistaken. In this paper, I show that the position that deductive explanation is privileged in this case is unmotivated. I argue that whether or not there is an explanatory (...) gap depends on the kind of explanation in question, so there is no single, unified explanatory gap but only the absence and (perhaps) presence of different sorts of explanation. (shrink)

It is widely held that the size of a probability makes no difference to the quality of a probabilistic explanation. I argue that explanatory practice in statistical physics belies this claim. The claim has gained currency only because of an impoverished conception of probabilistic processes and an unwarranted assumption that all probabilistic explanations have a single form.

The aim of the paper is to explicate the concept of causal independence between sets of factors and Reichenbach's screening-off-relation in probabilistic terms along the lines of Suppes' probabilistic theory of causality (1970). The probabilistic concept central to this task is that of conditional stochastic independence. The adequacy of the explication is supported by proving some theorems about the explicata which correspond to our intuitions about the explicanda.

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)

Richard Boyd and Nicholas Sturgeon develop distinctive naturalistic arguments for scientific realism and moral realism. Each defends a realist position by an inference to the best explanation. In this paper, I suggest that these arguments for realism should be reformulated, with the law of likelihood replacing inference to the best explanation. The resulting arguments for realism do not work.

Recently, Fred Gifford attempted to explicate the meaning of the term genetic as applied to phenotypic traits. He takes as his primary goal the explication of how the term is used and tries to avoid conclusions about how it should be used. He proposes two independent criteria (DF and PI) which together capture much of what biologists mean when they describe traits as genetic. Although Gifford's approach is extremely insightful in many ways, I argue that his analysis is not sufficiently (...) critical concerning the adequacy of common usage.In particular, while DF is a perfectly legitimate and useful measure of heritability in populations, it is not necessarily a genetic one and should not be labeled as such. PI on the other hand, although very intuitive, depends on an extremely problematic distinction between causes and mere conditions (e.g., genes and epigenetic factors). Both criteria will be highly relative and both, via what I term the new problem of genetics, will inspire contradictory analyses based on the same data. (shrink)

There is a recent interest within both philosophy of science as well as within epistemology to provide a defensible account of understanding. In the present article I build on insights from previous work in attempt to provide an account of two related forms of understanding in terms of the ability to form rational intentions when using specific types of mental representations. I propose first that “understanding that X” requires that one form a representation of X and, further, that one must (...) be capable of forming rational intentions using this representation across a range of conceivable conditions. I then propose that “understanding why X” requires that one possess a representation of a successful explanation for why X, and that one must be similarly capable of forming rational intentions using this representation across a range of conceivable conditions. I conclude the manuscript by reviewing objections and considering the way this account relates to other literature on explanation and understanding. (shrink)

It is widely held that it is difficult, if not impossible, to apply causal theory to the domain of quantum mechanics. However, there are several recent scientific explanations that appeal crucially to quantum processes, and which are most naturally construed as causal explanations. They come from two relatively new fields: quantum biology and quantum technology. We focus on two examples, the explanation for the optical interferometer LIGO and the explanation for the avian magneto-compass. We analyse the explanation for the avian (...) magneto-compass from the perspective of Woodward's interventionist theory and provide a causal model. Furthermore, we show how worries expressed by Woodward about quantum causation are circumvented in these cases, concluding that these kinds of explanations are most naturally construed as causal. (shrink)

Darwin'suse of final cause accords with the Aristotelian idea of finalcauses as explanatory types – as opposed to mechanical causes, which arealways particulars. In Wright's consequence etiology, anadaptation is explained by particular events, namely, its past consequences;hence, that etiology is mechanistic at bottom. This justifies Ghiselin'scharge that such versions of teleology trivialize the subject, But a purelymechanistic explanation of an adaptation allows it to appear coincidental.Patterns of outcome, whether biological or thermodynamic, cannot be explainedbytracing causal chains, even were that possible. (...) They are explicanda of aspecialkind. The form of their explanation, in statistical mechanics or by naturalselection, is not captured by statistical variants of the covering-law model orrelated models of explanation. In them as in classical teleology, types ofoutcome are cited to explain why there are outcomes of those types. But onlywhen types are explanatory by being selected for, as inexplanations of animal and human behavior as well as in Darwin's theory ofnatural selection, but not in statistical mechanics, is the explanationteleological. Darwin's theory is nontrivially teleological. (shrink)

This paper describes the development of theories of scientific explanation since Hempel's earliest models in the 1940ies. It focuses on deductive and probabilistic whyexplanations and their main problems: lawlikeness, explanation-prediction asymmetries, causality, deductive and probabilistic relevance, maximal specifity and homogenity, the height of the probability value. For all of these topic the paper explains the most important approaches as well as their criticism, including the author's own accounts. Three main theses of this paper are: (1) Both deductive and probabilistic explanations (...) are important in science, not reducible to each other. (2) One must distinguish between (cause giving) explanations and (reason giving) justifications and predictions. (3) The adequacy of deductive as well as probabilistic explanations is relative to a pragmatically given background knowledge-which does not exclude, however, the possibility of purely semantic models. (shrink)