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

F.A. Hayek argued that the sciences of complex phenomena, including (perhaps especially) economics, are limited to incomplete “explanations of the principle” and “pattern predictions.” According to Hayek, these disciplines suffer from (what I call) a data problem, i.e., the hopelessness of populating theoretical models with data adequate to full explanations and precise predictions. In Hayek’s terms, explanations in these fields are always a matter of “degree.” However, Hayek’s methodology implies a distinct theory problem: theoretical models of complex phenomena may (...) be underspecified so that, even were all the data available, a full explanation could not be inferred from the model. Where the sciences of complex phenomena are subject to both the data and theory problems, explanations and predictions will be of even lesser “predictive degree.” The paper also considers how to interpret Hayek’s claim that pattern predictions are falsifiable. (shrink)

From the early-1950s on, F.A. Hayek was concerned with the development of a methodology of sciences that study systems of complex phenomena. Hayek argued that the knowledge that can be acquired about such systems is, in virtue of their complexity (and the comparatively narrow boundaries of human cognitive faculties), relatively limited. The paper aims to elucidate the implications of Hayek’s methodology with respect to the specific dimensions along which the scientist’s knowledge of some complex phenomena may be limited. Hayek’s fallibilism (...) was an essential (if not always explicit) aspect of his arguments against the defenders of both socialism ([1935] 1948, [1940] 1948) and countercyclical monetary policy ([1975] 1978); yet, despite the fact that his conceptions of both complex phenomena and the methodology appropriate to their investigation imply that ignorance might beset the scientist in multiple respects, he never explicated all of these consequences. The specificity of a scientific prediction depends on the extent of the scientist’s knowledge concerning the phenomena under investigation. The paper offers an account of the considerations that determine the extent to which a theory’s implications prohibit the occurrence of particular events in the relevant domain. This theory of “predictive degree” both expresses and – as the phenomena of scientific prediction are themselves complex in Hayek’s sense – exemplifies the intuition that the specificity of a scientific prediction depends on the relevant knowledge available. (shrink)

This paper describes a formal measure of epistemic justification motivated by the dual goal of cognition, which is to increase true beliefs and reduce false beliefs. From this perspective the degree of epistemic justification should not be the conditional probability of the proposition given the evidence, as it is commonly thought. It should be determined instead by the combination of the conditional probability and the prior probability. This is also true of the degree of incremental confirmation, and I (...) argue that any measure of epistemic justification is also a measure of incremental confirmation. However, the degree of epistemic justification must meet an additional condition, and all known measures of incremental confirmation fail to meet it. I describe this additional condition as well as a measure that meets it. The paper then applies the measure to the conjunction fallacy and proposes an explanation of the fallacy. (shrink)

A down-to-earth admission of abstract objects can be based on detailed explanation of where the objectivity of mathematics comes from, and how a ‘thin’ notion of object emerges from objective mathematical discourse or practices. We offer a sketch of arguments concerning both points, as a basis for critical scrutiny of the idea that mathematical and social objects are essentially of the same kind—which is criticized. Some authors have proposed that mathematical entities are indeed institutional objects, a product of our (...) collective imposition of function onto reality (the phrase comes from Searle) and of surrogation or hypostasis. Yet there are significant disanalogies between the typical social objects and mathemata, on which basis I argue that one should make a clear distinction between both. The comparison of mathematical with social objects helps understanding how non-physical objects can figure prominently in our explanations of reality. Yet mathematical objects have a different kind of cognitive grounding, and the more elementary of them emerge under relatively very simple sociocultural conditions. The differences are also reflected in the wide scope of use of mathematical concepts, and the much higher degree of variation found among social objects. On the basis of all of these features, I defend the thesis that one can significantly distinguish degrees of objectivity, and I use the distinction to articulate a graded ontology where one can locate the different kinds of mathematical and social objects. (shrink)

The purpose of this article is to compare the theory that there are degrees of truth with putnam's intuitionist theory as rival solutions to the sorites paradox. I argue that intuitionist logic lacks explanatory support and is self-Defeating. The degree theory on the other hand offers an illuminating explanation of the sorites fallacy.

This article analyzes the evolution of Mersenne's views concerning the validity of Galileo's theory of acceleration. After publishing, in 1634, a treatise designed to present empirical evidence in favor of Galileo's odd-number law, Mersenne developed over the years the feeling that only the elaboration of a physical proof could provide sufficient confirmation of its validity. In the present article, I try to show that at the center of Mersenne's worries stood Galileo's assumption that a falling body had to pass in (...) its acceleration through infinite degrees of speed. His extensive discussions with, or his reading of, Descartes, Gassendi, Baliani, Fabri, Cazre, Deschamps, Le Tenneur, Huygens, and Torricelli led Mersenne to believe that the hypothesis of a passage through infinite degrees of speed was incompatible with any mechanistic explanation of free fall. (shrink)

Our purpose in this paper is to contribute to a practice-based characterization of scientific inference. We want to explore whether Brandom’s pragmatist–inferentialist framework can suitably accommodate several types of ampliative inference common in scientific reasoning and explanation (probabilistic reasoning, abduction and idealisation). First, we argue that Brandom’s view of induction in terms of merely permissive inferences is inadequate; in order to overcome the shortcoming of Brandom’s proposal, we put forward an alternative conception of inductive, probabilistic reasoning by appeal to (...) the notion of degrees of commitment. Moreover, we examine the sorts of inferential commitments operative in other types of ampliative inferences, such as abduction or reasoning involving idealizations and assumptions. We suggest that agents engaging in these forms of reasoning often undertake restricted inferential commitments, whose scope and reach are more limited that in the case of the commitments associated with full beliefs. (shrink)

In this survey we discuss work of Levin and V’yugin on collections of sequences that are non-negligible in the sense that they can be computed by a probabilistic algorithm with positive probability. More precisely, Levin and V’yugin introduced an ordering on collections of sequences that are closed under Turing equivalence. Roughly speaking, given two such collections $\mathcal {A}$ and $\mathcal {B}$, $\mathcal {A}$ is below $\mathcal {B}$ in this ordering if $\mathcal {A}\setminus \mathcal {B}$ is negligible. The degree structure (...) associated with this ordering, the Levin–V’yugin degrees, can be shown to be a Boolean algebra, and in fact a measure algebra. We demonstrate the interactions of this work with recent results in computability theory and algorithmic randomness: First, we recall the definition of the Levin–V’yugin algebra and identify connections between its properties and classical properties from computability theory. In particular, we apply results on the interactions between notions of randomness and Turing reducibility to establish new facts about specific LV-degrees, such as the LV-degree of the collection of 1-generic sequences, that of the collection of sequences of hyperimmune degree, and those collections corresponding to various notions of effective randomness. Next, we provide a detailed explanation of a complex technique developed by V’yugin that allows the construction of semi-measures into which computability-theoretic properties can be encoded. We provide two examples of the use of this technique by explicating a result of V’yugin’s about the LV-degree of the collection of Martin-Löf random sequences and extending the result to the LV-degree of the collection of sequences of DNC degree. (shrink)

Our purpose in this paper is to contribute to a practice-based characterization of scientific inference. We want to explore whether Brandom’s pragmatist–inferentialist framework can suitably accommodate several types of ampliative inference common in scientific reasoning and explanation (probabilistic reasoning, abduction and idealisation). First, we argue that Brandom’s view of induction in terms of merely permissive inferences is inadequate; in order to overcome the shortcoming of Brandom’s proposal, we put forward an alternative conception of inductive, probabilistic reasoning by appeal to (...) the notion of degrees of commitment. Moreover, we examine the sorts of inferential commitments operative in other types of ampliative inferences, such as abduction or reasoning involving idealizations and assumptions. We suggest that agents engaging in these forms of reasoning often undertake restricted inferential commitments, whose scope and reach are more limited that in the case of the commitments associated with full beliefs. (shrink)

An increasingly popular theory of moral responsibility, Attributionism, identifies attitudes as the locus of direct responsibility. And yet, two agents with qualitatively identical attitudes may differ in their responsibility due to a difference in whether they act on those attitudes. On the most plausible interpretation of Attributionism, attitude duplicates differ in their responsibility only with respect to the scope of what they’re responsible for: one agent is responsible for only their attitudes, while the other is responsible for their attitudes and (...) for acting in a way that reflects those attitudes. Against this, I argue that attitude duplicates may also differ with respect to their degrees of praiseworthiness, and that this is best explained by either the effort or sacrifice instantiated in one’s actions—explanations unavailable to Attributionism. If this is correct, then Attributionism fails to provide an adequate account of praiseworthiness, and therefore fails as a theory of moral responsibility. (shrink)

In this paper I am concerned with the question of whether degrees of belief can figure in reasoning processes that are executed by humans. It is generally accepted that outright beliefs and intentions can be part of reasoning processes, but the role of degrees of belief remains unclear. The literature on subjective Bayesianism, which seems to be the natural place to look for discussions of the role of degrees of belief in reasoning, does not address the question of whether degrees (...) of belief play a role in real agents’ reasoning processes. On the other hand, the philosophical literature on reasoning, which relies much less heavily on idealizing assumptions about reasoners than Bayesianism, is almost exclusively concerned with outright belief. One possible explanation for why no philosopher has yet developed an account of reasoning with degrees of belief is that reasoning with degrees of belief is not possible for humans. In this paper, I will consider three arguments for this claim. I will show why these arguments are flawed, and conclude that, at least as far as these arguments are concerned, it seems like there is no good reason why the topic of reasoning with degrees of belief has received so little attention. (shrink)

The recent failures and scandals involving many large businesses have highlighted the importance of corporate social responsibility as a fundamental factor in the soundness of the free market system. The corporate social responsiveness orientation of business executives plays an important role in corporate decision making since managers make important decisions on behalf of their corporations. This paper explores whether there is a relationship between an individual's degree of religiousness and his or her corporate social responsiveness (CSR) orientation. The results (...) of a survey of 473 business students found a significant relationship between degree of religiousness and attitudes toward the economic and ethical components of CSR. Some explanations as well as limited generalizations and implications are developed. (shrink)

Many theorists think nowadays that vagueness is a widespread phenomenon that affects and infects almost all terms and concepts of our thought and language, and for some philosophers degree of truth theories are the best way to cope with vagueness and sorites susceptible concepts. In this paper I argue that many of the allegedly vague concepts are not vague in the last analysis the philosopher or scientist could offer if compelled to, and that much of the vagueness of the (...) properly vague ones comes from its contextual dependence alone. I also argue that degree of truth approaches -- particularly the infinitist ones -- and fuzzy logics do not solve practically any of the puzzles brought about by vagueness and sorites arguments, and conversely they have many additional problems of their own. Concerning recalcitrant cases of vagueness, I would tentatively commend the epistemic theory of vagueness, from an inference to the best explanation. (shrink)

There is a debate in philosophy of mind about the nature of reason explanations of action, and this volume is testament to a resurgence of interest in non-causal accounts. In Teleological Realism: Mind, Agency, and Explanation,2 I have proposed a non-causal account according to which common-sense reason explanations of action are irreducibly teleological in form. I claim that we explain behavior by citing the state of affairs towards which the agent was directing her behavior, i. e., by citing the (...) purpose or goal of the behavior. I will not be defending that account of action explanation here, but will be assuming it and applying it to the free will debate. I will argue that the teleological account of action explanation leads to a view of free will with some interesting and attractive features. Philosophical accounts of free will typically propose some sort of criterion for determining which behaviors count as free, e. g., that the agent could have done otherwise, or that the behavior was in accord with the agent’s second-order volitions. The account is then usually used to answer the question of whether we have free will, and especially whether we can have free will even if determinism is true. To test these accounts, philosophers make arguments of various sorts, but the primary method is with cases. Here’s the recipe for an objection to an account of free will: come up with a case where the theory says that the agent is free, but our intuition says that the agent is unfree, or vice versa. I won’t question the method of cases in principle; it’s what we have and it makes some sense. On the picture of analytic philosophy as conceptual analysis, it makes perfect sense. Philosophers put forward a precisely spelled out version of our concept of free will; but if such an account is at odds with firm intuitions in particular cases, then it can’t be what we mean. We know that the situation is not really so simple as that. Our ordinary concept of free will might be messy and not perfectly consistent; accordingly, any particular theory might get a few cases ›wrong‹ as judged by our intuitions.. (shrink)

Agent-based modelling has become a well-established method in social epistemology and philosophy of science but the question of what kind of explanations these models provide remains largely open. This paper is dedicated to this issue. It starts by distinguishing between real-world phenomena, real-world possibilities, and logical possibilities as different kinds of targets which agent-based models can represent. I argue that models representing the former two kinds provide how-actually explanations or causal how-possibly explanations. In contrast, models that represent logical possibilities provide (...) epistemically opaque how-possibly explanations. While highly idealised ABMs in the form in which they are initially proposed typically fall into the last category, the epistemic opaqueness of explanations they provide can be reduced by validation procedures. To this purpose, an examination of results of simulations in terms of classes of models can be particularly helpful. I illustrate this point by discussing a class of ABMs of scientific interaction and the claim that a high degree of interaction can impede scientific inquiry. (shrink)

Implicit contextual factors mean that the boundary between causal and noncausal explanation is not as neat as one might hope: as the phenomenon to be explained is given descriptions with varying degrees of granularity, the nature of the favored explanation alternates between causal and non-causal. While it is not surprising that different descriptions of the same phenomenon should favor different explanations, it is puzzling why re-describing the phenomenon should make any difference for the causal nature of the favored (...) explanation. I argue that this is a problem for the ontic framework of causal and noncausal explanation, and instead propose a pragmatic-modal account of causal and non-causal explanation. This account has the added advantage of dissolving several important disagreements concerning the status of non-causal explanation. (shrink)

Second, there is a form of ampliative inference that has come to be called ‘inference to the best explanation,’ or more briefly ‘explanatory inference.’ Roughly: From the fact that a certain hypothesis would explain the data at hand better than any other available hypothesis, we infer with some degree of confidence that that leading hypothesis is correct. There is no question but that this inference is often performed. Arguably, every human being performs it many times in a day, (...) perhaps without letup. (shrink)

The target article presents a thought-provoking approach to the relation of neuroscience and art. However, at least two issues pose potential difficulties. The first concerns whether is a coherent topic for scientific study. The second concerns the degree to which processing fluency can explain aesthetic feeling or may simply be one component of a more complex account.

The basic idea behind the Competitive Exclusion Principle is that species that have similar or identical niches cannot stably coexist in the same place for long periods of time when their common resources are limiting. A more exact definition of the CEP states that, in equilibrium, n number of sympatric species competing for a common set of limiting resources cannot stably coexist indefinitely on fewer than n number of resources. The magnitude or intensity of competition between species is proportional to (...) the degree of overlap in their niches or use of resources. Species that stably coexist do so because there are “important differences” in their niches or use of common limiting resources. (shrink)

In this paper, I offer an explication of the notion of local explanation. In the literature, local explanations are considered as metaphysically and methodologically satisfactory: local explanations reveal the contingency of science and provide a methodologically sound historiography of science. However, the lack of explication of the notion of local explanation makes these claims difficult to assess. The explication provided in this paper connects the degree of locality of an explanans to the degree of contingency of (...) the explanandum. Moreover, the explication is shown to be compatible with the methodological need for a general consideration in the historiography of science. In this way, the explication satisfies the need to explicate an important notion, connects local explanations and contingency, and enables us to see how local explanations and general considerations can be connected. However, the explication also sheds critical light on many claims and expectations that are associated with local explanations and their satisfactoriness. (shrink)

In this article, the author shows how earlier institutional explanations of union strength are theoretically and methodologically flawed. At odds with earlier research, the author argues that two institutional properties—the degree of centralization in the bargaining system and the workplace access of the union movement— will interactively influence the unionization process. The results of empirical tests speak in favor of the stated hypothesis. The combination of centralized bargaining and workplace access does not only positively influence the aggregate density levels (...) but also cushions the effects of industrial, occupational, and demographic factors on the probability of being a union member. (shrink)

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

Cases of 'convergence' could play an important role in the construction and corroboration of adaptive hypotheses. In particular, they could inform us about the evolutionary histories of novel traits. However, there is a problem of causal depth in the use of analogies. Natural Selection's affect on phenotype is constrained by phylogenetic history to a degree that we are unfounded in projecting adaptive stories from one lineage to another. I will argue for two approaches to resolve this issue. First, by (...) constraining our catchment area to closely related lineages we can control for developmental noise. Second, by integrating analogies into explanations which incorporate other streams of evidence or bootstrapping an analogous model across many instantiations, we can overcome the problem of causal depth. (shrink)

This paper champions the view (REG) that the concept of a normative reason for an agent S to perform an action A is that of an explanation why it would be good (in some way, to some degree) for S to do A. REG has numerous virtues, but faces some significant challenges which prompt many philosophers to be skeptical that it can correctly account for all our reasons. I demonstrate how five different puzzles about normative reasons can be (...) solved by attention to the concept of goodness, and in particular observing the ways in which it—and consequently, talk about reasons—is sensitive to context (ends and information). Rather than asking simply whether or not certain facts are reasons for S to do A, we need to explore the contexts in which it is and is not correct to describe a certain fact as “a reason” for S to do A. These five puzzles concern: (1) reasons for attitudes of the “right kind”, (2) evidence as reasons, (3) normative facts as reasons, (4) subjective reasons, and (5) attitudes as reasons. (shrink)

While it is commonly accepted that justified beliefs must be strongly supported by evidence and that support comes in degrees, the question of how much evidential support one needs in order to have a justified belief remains. In this paper, I consider how the question about degrees of evidential support connects with recent debates between consequentialist and deontological explanations of epistemic norms. I argue that explaining why strong, but not conclusive, evidential support is required for justification should be one explanandum (...) that such theories seek to explain. Furthermore, I argue that foundational theories that appeal to the promotion of epistemic value (especially consequentialism, but perhaps also some versions of epistemic deontology) are better suited to provide such an explanation. (shrink)

Gauss’s quadratic reciprocity theorem is among the most important results in the history of number theory. It’s also among the most mysterious: since its discovery in the late 18th century, mathematicians have regarded reciprocity as a deeply surprising fact in need of explanation. Intriguingly, though, there’s little agreement on how the theorem is best explained. Two quite different kinds of proof are most often praised as explanatory: an elementary argument that gives the theorem an intuitive geometric interpretation, due to (...) Gauss and Eisenstein, and a sophisticated proof using algebraic number theory, due to Hilbert. Philosophers have yet to look carefully at such explanatory disagreements in mathematics. I do so here. According to the view I defend, there are two important explanatory virtues—depth and transparency—which different proofs (and other potential explanations) possess to different degrees. Although not mutually exclusive in principle, the packages of features associated with the two stand in some tension with one another, so that very deep explanations are rarely transparent, and vice versa. After developing the theory of depth and transparency and applying it to the case of quadratic reciprocity, I draw some morals about the nature of mathematical explanation. (shrink)

Issues concerning scientific explanation have been a focus of philosophical attention from Pre- Socratic times through the modern period. However, recent discussion really begins with the development of the Deductive-Nomological (DN) model. This model has had many advocates (including Popper 1935, 1959, Braithwaite 1953, Gardiner, 1959, Nagel 1961) but unquestionably the most detailed and influential statement is due to Carl Hempel (Hempel 1942, 1965, and Hempel & Oppenheim 1948). These papers and the reaction to them have structured subsequent discussion (...) concerning scientific explanation to an extraordinary degree. After some general remarks by way of background and orientation (Section 1), this entry describes the DN model and its extensions, and then turns to some well-known objections (Section 2). It next describes a variety of subsequent attempts to develop alternative models of explanation, including Wesley Salmon's Statistical Relevance (Section 3) and Causal Mechanical (Section 4) models and the Unificationist models due to Michael Friedman and Philip Kitcher (Section 5). Section 6 provides a summary and discusses directions for future work. (shrink)

Defenders of Inference to the Best Explanation claim that explanatory factors should play an important role in empirical inference. They disagree, however, about how exactly to formulate this role. In particular, they disagree about whether to formulate IBE as an inference rule for full beliefs or for degrees of belief, as well as how a rule for degrees of belief should relate to Bayesianism. In this essay I advance a new argument against non-Bayesian versions of IBE. My argument focuses (...) on cases in which we are concerned with multiple levels of explanation of some phenomenon. I show that in many such cases, following IBE as an inference rule for full beliefs leads to deductively inconsistent beliefs, and following IBE as a non-Bayesian updating rule for degrees of belief leads to probabilistically incoherent degrees of belief. (shrink)

This paper identifies one way that a mathematical proof can be more explanatory than another proof. This is by invoking a more abstract kind of entity than the topic of the theorem. These abstract mathematical explanations are identified via an investigation of a canonical instance of modern mathematics: the Galois theory proof that there is no general solution in radicals for fifth-degree polynomial equations. I claim that abstract explanations are best seen as describing a special sort of dependence relation (...) between distinct mathematical domains. This case study highlights the importance of the conceptual, as opposed to computational, turn of much of modern mathematics, as recently emphasized by Tappenden and Avigad. The approach adopted here is contrasted with alternative proposals by Steiner and Kitcher. (shrink)

Comparing different causes’ importance, and apportioning responsibility between them, requires making good sense of the notion of partial explanation, that is, of degree of explanation. How much is this subjective, how much objective? If the causes in question are probabilistic, how much is the outcome due to them and how much to simple chance? I formulate the notion of degree of causation, or effect size, relating it to influential recent work in the literature on causation. I (...) examine to what extent mainstream social science methods--both quantitative and qualitative--succeed in establishing effect sizes so understood. The answer turns out to be, roughly: only to some extent. Next, the standard understanding of effect size, even though widespread, still has several underappreciated consequences. I detail some of those. Finally, I discuss the separate issue of explanandum-dependence, which is essential to assessing any cause’s explanatory importance and yet which has been comparatively neglected. (shrink)

What makes for a good explanation of a person’s actions? Their reasons, or soa natural reply goes. But how do reasons function as part of explanations, that is, within an account of the causes of action? Here philosophers divide concerning the logical relation in which reasons stand to actions. For, tradition holds, reasons evaluatively characterized must be causally inert, inasmuch as the normative features cannot be found in any account of the empirical/descriptive. To countenance reasons as causes thus seems (...) to imply some degree of normative involvement in causal explanation. Mark Risjord opts for full normative involvement while David Henderson insistently denies a role to norms in explanation. Stueber occupies an intermediate position here. I question just whether there exists some "special" problem regarding norms, at least in the form which, I take it, all three of the authors I discuss assume there to be one. Key Words: reasons • causes • norms • rules • explanation. (shrink)

Carl G. Hempel has often stated that inductive-statistical explanations, as he conceives them, are inductive arguments. This discussion note raises the question of whether such arguments are to be understood as (1) arguments of the traditional sort, containing premises and conclusions, governed by some sort of inductive "acceptance rules," or (2) something more closely akin to Carnap's degree of confirmation statements which occur in an inductive logic which entirely eschews inductive "acceptance rules." Hempel's writings do not seem unequivocal on (...) this issue. It is suggested that adoption of construal (2) would remove the need for Hempel's high probability requirement on I-S explanations. (shrink)

Several philosophers have argued that to capture the generality of certain scientific explanations, we must count mathematical facts among their explanantia. I argue that we can better understand these explanations by adopting a more nuanced stance toward mathematical representations, recognizing the role of mathematical representation schemata in representing highly abstract features of physical systems. It is by picking out these abstract but nonmathematical features that explanations appealing to mathematics achieve a high degree of generality. The result is a rich (...) conception of the role of mathematics in scientific explanations that does not require us to treat mathematical facts as explanantia. (shrink)

A naturalistic theory of rationalization is defended against a fundamental objection. The theory claims that: The rationalizing relation can be fully analysed in causal explanatory terms. However, is rendered problematic by the fact that: Rationalizations exhibit a higher degree of intensionality than ordinary physical causal explanations. To show that can be maintained in the face of , I develop an account of on which and may be reconciled. ;The opening chapter gives an account of the intensionality of ordinary physical (...) causal explanations by developing a counterfactual analysis of causal relevance. Chapter II examines the nature and intensionality of rationalizations. It is argued that despite , a rationalization partly involves a causal relevance relation between its explanans and explanandum. ;In Chapter III, I consider an argument which implies that is false: Davidson's argument that there can be no psychophysical laws. An attempt is made to give a clear and compelling representation of this argument. As I interpret it, the argument depends on the alleged insolubility of the problem of causal deviance in action. ;Chapter IV develops a general theory of deviance according to which any functional system may produce output in a deviant way, and applies this theory to agents. A negative consequence of the theory is that an action may be performed in a deviant way even if the agent's intention causally explains the action . A positive consequence of the theory is that an action is performed in a non-deviant way just in case there is an appropriate causal explanation of why the agent's intention causes him to act. My specific suggestion is that an agent performs an action in a non-deviant way when and only when his intention causes him to act because he "knows how" to act in that way. ;In the last chapter, it is argued that our solution to the problem of deviance can be adapted to account for in causal explanatory terms. In this way and are reconciled. (shrink)

An increasingly common form of naturalism associated with the study of morality is what might be called “scientific naturalism,” which takes as its subject matter various empirical phenomena associated with talk of “morality” and aims to subject them to scientific inquiry, just like any other empirical phenomena. This is unproblematic when it comes to scientific investigations into the origins of the human capacity for normative guidance or moral emotions, or the neurophysiology associated with moral feeling and behavior, but things get (...) much more complicated when it comes to the project of explaining our moral beliefs. It is, of course, an empirical phenomenon that we hold the moral beliefs we do, so it may seem obvious that this too can be causally explained using scientific tools. But, while there is room for scientific inquiry into causal factors, such as evolutionary influences, that have plausibly helped to shape many moral beliefs to some degree, it is a mistake to assume that our moral beliefs across the board can best be explained through appeal exclusively to scientifically accessible causes. This scientific naturalist exclusivity assumption is in fact deeply problematic, overlooking (or prematurely dismissing) the possibility that at least many of our moral beliefs are best explained through our grasping of good reasons for them – considerations we correctly understand as justifying them, though this is not something that shows up in scientific causal explanations. It is easy to miss this point about the potential role of the appreciation of justification by the believing mind when considering moral judgments simply from the external perspective of an amoral anthropologist, but it becomes clear when taking up the internal perspective of the committed moral agent, as when thinking about why we ourselves believe that human trafficking is wrong. This matters because, while science is invoked by those who purport to provide “debunking explanations” of our moral beliefs across the board (showing them to result simply from causal factors insensitive to any objective moral facts), they are actually relying on the scientific naturalist exclusivity assumption, thus begging the question against their opponents, who hold that we have knowledge of objective morality as a result of grasping good reasons for it. I explore these complexities surrounding the explanation of our moral beliefs and argue that while the picture advocated by debunkers remains a possibility, it is certainly not established by science, and recent arguments purporting to debunk the idea of knowable, objective morality fail. (shrink)

Research in neurocriminology has explored the link between neural functions and structures and the psychopathic disposition. This online experiment aimed to assess the effect of communicating the neuroscience of psychopathy on the degree to which lay people exhibited attitudes characteristic of psychopathy in particular in terms of moral behaviour. If psychopathy is blamed on the brain, people may feel less morally responsible for their own psychopathic tendencies. In the study, participants read false feedback about their own psychopathic traits supposedly (...) inferred from their Facebook likes, described either in neurobiological or cognitive terms. Participants were randomly allocated to read that they either had above-average or below-average psychopathic traits. We found no support for the hypothesis that the neuroscientific explanation of psychopathy influences moral behaviour. This casts doubt on the fear that communicating the neuroscience of psychopathy will promote psychopathic attitudes. (shrink)

During the 1930s and 1940s, American physical organic chemists employed electronic theories of reaction mechanisms to construct models offering explanations of organic reactions. But two molecular rearrangements presented enormous challenges to model construction. The Claisen and Cope rearrangements were predominantly inaccessible to experimental investigation and they confounded explanation in theoretical terms. Drawing on the idea that models can be autonomous agents in the production of scientific knowledge, I argue that one group of models in particular were functionally autonomous from (...) the Hughes–Ingold theory. Cope and Hardy’s models of the Claisen and Cope rearrangements were resources for the exploration of the Hughes–Ingold theory that otherwise lacked explanatory power. By generating ‘how-possibly’ explanations, these models explained how these rearrangements could happen rather than why they did happen. Furthermore, although these models were apparently closely connected to theory in terms of their construction, I argue that partial autonomy issued in extra-logical factors concerning the attitudes of American chemists to the Hughes–Ingold theory. And in the absence of a complete theoretical hegemony, a degree of consensus was reached concerning modelling the Claisen rearrangement mechanism.Keywords: Models; Explanation; Physical organic chemistry; Rearrangements. (shrink)

Recent work on the interpretation of counterfactual conditionals has paid much attention to the role of causal independencies. One influential idea from the theory of Causal Bayesian Networks is that counterfactual assumptions are made by intervention on variables, leaving all of their causal non-descendants unaffected. But intervention is not applicable across the board. For instance, backtracking counterfactuals, which involve reasoning from effects to causes, cannot proceed by intervention in the strict sense, for otherwise they would be equivalent to their consequents. (...) We discuss these and similar cases, focusing on two factors which play a role in determining whether and which causal parents of the manipulated variable are affected: Speakers' need for an explanation of the hypothesized state of affairs, and differences in the ‘resilience’ of beliefs that are independent of degrees of certainty. We describe the relevant theoretical notions in some detail and provide experimental evidence that these factors do indeed affect speakers' interpretation of counterfactuals. (shrink)

Some, if not most, philosophy program admissions committee members assume that they can determine that one applicant will likely manifest a higher degree of philosophical skill than another applicant on the basis of differences between their materials. I challenge this assumption by explaining how applicants’ materials in significant measure reflect the racially unjust environment in which they manifest their philosophical skill. I explain how applicants’ racial-group membership in similar measure determines what these materials consist in.

This paper describes an alternative to the common view that explanation in the special sciences involves subsumption under laws. According to this alternative, whether or not a generalization can be used to explain has to do with whether it is invariant rather than with whether it is lawful. A generalization is invariant if it is stable or robust in the sense that it would continue to hold under a relevant if it is stable or robust in the sense that (...) it would continue to hold under a relevant class of changes. Unlike lawfulness, invariance comes in degrees and has other features that are well suited to capture the characteristics of explanatory generalizations in the special sciences. For example, a generalization can be invariant even if it has exceptions or holds only over a limited spatio-temporal interval. The notion of invariance can be used to resolve a number of dilemmas that arise in standard treatments of explanatory generalizations in the special sciences. (shrink)

This paper provides a new approach to inference to the best explanation based on a new coherence measure for comparing how well hypotheses explain the evidence. It addresses a number of criticisms of the use of probabilistic measures in this context by Clark Glymour, including limitations of earlier work on IBE. Computer experiments are used to show that the new approach finds the truth with a high degree of accuracy in hypothesis selection tasks and that in some cases (...) its accuracy is greater than hypothesis selection based on maximizing posterior probability. Hence, by overcoming some of the problems with the previous approach, this work provides a more adequate defence of IBE and suggests that IBE not only tracks truth but also has practical advantages over the previous approach. Applications of the new approach to parameter estimation and model selection are also explored. (shrink)

No agreed-upon account of mirror reversal is currently available although it has been discussed for more than two thousand years since Plato. Mirror reversal usually refers to recognized left-right reversal of a mirror image. Depending on the nature and layout of a reflected object, however, top-bottom reversal may be recognized instead of left-right reversal; no reversal at all may be recognized; and the presence or absence of reversal may not be decidable. Takano (1998) proposed a psycho-optic theory to explain all (...) these cases of mirror image recognition in a consistent manner. The proposed theory assumes different causes of mirror reversal depending on whether an object's left-right axis is parallel or perpendicular to a mirror's surface. This theory was later criticized in that it provided no explanation when the left-right axis is neither parallel nor perpendicular but at an intermediate angle between zero and 90 degrees with a mirror. This article completes the theory by presenting psycho-optic anal.. (shrink)

The use of idealized scientific theories in explanations of empirical facts and regularities is problematic in two ways: they don’t satisfy the condition that the explanans is true, and they may fail to entail the explanandum. An attempt to deal with the latter problem was proposed by Hempel and Popper with their notion of approximate explanation. A more systematic perspective on idealized explanations was developed with the method of idealization and concretization by the Poznan school in the 1970s. If (...) idealizational laws are treated as counterfactual conditionals, they can be true or truthlike, and the concretizations of such laws may increase their degree of truthlikeness. By replacing Hempel’s truth requirement with the condition that an explanatory theory is truthlike one can distinguish several important types of approximate, corrective, and contrastive explanations by idealized theories. The conclusions have important consequences for the debates about scientific realism and anti-realism. (shrink)