This paper distinguishes bruteness from fundamentality by developing a theory of stochastic grounding that makes room for non-fundamental bruteness. Stochastic grounding relations, which only underwrite incomplete explanations, arise when the fundamental level underdetermines derivative levels. The framework is applied to fission cases, showing how one can break symmetries and mitigate bruteness whilst avoiding arbitrariness and hypersensitivity.

What features will something have if it counts as an explanation? And will something count as an explanation if it has those features? In the second half of the 20th century, philosophers of science set for themselves the task of answering such questions, just as a priori conceptual analysis was generally falling out of favor. And as it did, most philosophers of science just moved on to more manageable questions about the varieties of explanation and discipline-specific scientific explanation. Often, such (...) shifts are sound strategies for problem-solving. But leaving fallow certain basic conceptual issues can also result in foundational debates. (shrink)

This paper argues that if propensities are displayed in objective physical chances then the appropriate representation of these chances is as indexed probability functions. Two alternative formal models, or accounts, for the relation between propensity properties and their chancy or probabilistic manifestations, in terms of conditionals and conditional probability are first reviewed. It is argued that both confront important objections, which are overcome by the account in terms of indexed probabilities. A number of further advantages of the indexed probability account (...) are discussed, which suggest that it is promising as a general theory of objective physical chance. The paper ends with a discussion of the indexical character of the objective chances that are grounded in propensities. (shrink)

In this paper we discuss three interrelated questions. First: is explanation in mathematics a topic that philosophers of mathematics can legitimately investigate? Second: are the specific aims that philosophers of mathematical explanation set themselves legitimate? Finally: are the models of explanation developed by philosophers of science useful tools for philosophers of mathematical explanation? We argue that the answer to all these questions is positive. Our views are completely opposite to the views that Mark Zelcer has put forward recently. Throughout this (...) paper, we show why Zelcer’s arguments fail. (shrink)

A definition of causation as probability-raising is threatened by two kinds of counterexample: first, when a cause lowers the probability of its effect; and second, when the probability of an effect is raised by a non-cause. In this paper, I present an account that deals successfully with problem cases of both these kinds. In doing so, I also explore some novel implications of incorporating into the metaphysical investigation considerations of causal psychology.

According to one large family of views, scientific explanations explain a phenomenon (such as an event or a regularity) by subsuming it under a general representation, model, prototype, or schema (see Bechtel, W., & Abrahamsen, A. (2005). Explanation: A mechanist alternative. Studies in History and Philosophy of Biological and Biomedical Sciences, 36(2), 421–441; Churchland, P. M. (1989). A neurocomputational perspective: The nature of mind and the structure of science. Cambridge: MIT Press; Darden (2006); Hempel, C. G. (1965). Aspects of scientific (...) explanation. In C. G. Hempel (Ed.), Aspects of scientific explanation (pp. 331–496). New York: Free Press; Kitcher (1989); Machamer, P., Darden, L., & Craver, C. F. (2000). Thinking about mechanisms. Philosophy of Science, 67(1), 1–25). My concern is with the minimal suggestion that an adequate philosophical theory of scientific explanation can limit its attention to the format or structure with which theories are represented. The representational subsumption view is a plausible hypothesis about the psychology of understanding. It is also a plausible claim about how scientists present their knowledge to the world. However, one cannot address the central questions for a philosophical theory of scientific explanation without turning one’s attention from the structure of representations to the basic commitments about the worldly structures that plausibly count as explanatory. A philosophical theory of scientific explanation should achieve two goals. The first is explanatory demarcation. It should show how explanation relates with other scientific achievements, such as control, description, measurement, prediction, and taxonomy. The second is explanatory normativity. It should say when putative explanations succeed and fail. One cannot achieve these goals without undertaking commitments about the kinds of ontic structures that plausibly count as explanatory. Representations convey explanatory information about a phenomenon when and only when they describe the ontic explanations for those phenomena. (shrink)

GRW Theory postulates a stochastic mechanism assuring that every so often the wave function of a quantum system is `hit', which leaves it in a localised state. How are we to interpret the probabilities built into this mechanism? GRW theory is a firmly realist proposal and it is therefore clear that these probabilities are objective probabilities (i.e. chances). A discussion of the major theories of chance leads us to the conclusion that GRW probabilities can be understood only as either single (...) case propensities or Humean objective chances. Although single case propensities have some intuitive appeal in the context of GRW theory, on balance it seems that Humean objective chances are preferable on conceptual grounds because single case propensities suffer from various well know problems such as unlimited frequency tolerance and lack of a rationalisation of the principal principle. (shrink)

We present a probabilistic extension to active path analyses of token causation. The extension uses the generalized notion of intervention presented in : we allow an intervention to set any probability distribution over the intervention variables, not just a single value. The resulting account can handle a wide range of examples. We do not claim the account is complete --- only that it fills an obvious gap in previous active-path approaches. It still succumbs to recent counterexamples by Hiddleston, because it (...) does not explicitly consider causal processes. We claim three benefits: a detailed comparison of three active-path approaches, a probabilistic extension for each, and an algorithmic formulation. (shrink)

Single-case and long-run propensity theories are among the main objective interpretations of probability. There have been various objections to these theories, e.g. that it is difficult to explain why propensities should satisfy the probability axioms and, worse, that propensities are at odds with these axioms, that the explication of propensities is circular and accordingly not informative, and that single-case propensities are metaphysical and accordingly non-scientific. We consider various propensity theories of probability and their prospects in light of these objections. We (...) argue that while propensity theories face challenges, these challenges do not undermine their validity as prospective interpretations of probability in science. (shrink)

I present a new definition of verisimilitude, framed in terms of causes. Roughly speaking, according to it a scientific model is approximately true if it captures accurately the strengths of the causes present in any given situation. Against much of the literature, I argue that any satisfactory account of verisimilitude must inevitably restrict its judgments to context-specific models rather than general theories. We may still endorse—and only need—a relativized notion of scientific progress, understood now not as global advance but rather (...) as the mastering of particular problems. This also sheds new light on longstanding difficulties surrounding language-dependence and models committed to false ontologies. (shrink)

The failure to recognize a correlation as spurious can lead people to adopt strategies to bring about a specific outcome that manipulate something other than a cause of the outcome. However, in a 2008 paper appearing in the journal Analysis, Bert Leuridan, Erik Weber and Maarten Van Dyck suggest that knowledge of spurious correlations can, at least sometimes, justify adopting a strategy aiming at bringing about some change. This claim is surprising and, if true, throws into question the claim of (...) Nancy Cartwright and others that knowledge of laws of association is insufficient for distinguishing effective and ineffective strategies. This paper examines the nature of spurious correlations and their value in crafting strategies for change. The conclusion of the paper is that while knowledge of a spurious correlation may have practical value, the value depends on either having knowledge of the causal structure underlying the correlation or it depends on the use of ‘causal criteria’. (shrink)

In this paper I adduce a new argument in support of the claim that IBE is an autonomous form of inference, based on a familiar, yet surprisingly, under-discussed, problem for Hume’s theory of induction. I then use some insights thereby gleaned to argue for the claim that induction is really IBE, and draw some normative conclusions.

Jonathan Kvanvig has argued that “objectual” understanding, i.e. the understanding we have of a large body of information, cannot be reduced to explanatory concepts. In this paper, I show that Kvanvig fails to establish this point, and then propose a framework for reducing objectual understanding to explanatory understanding.

The anti-causal prophecies of last century have been disproved. Causality is neither a ‘relic of a bygone’ nor ‘another fetish of modern science’; it still occupies a large part of the current debate in philosophy and the sciences. This investigation into causal modelling presents the rationale of causality, i.e. the notion that guides causal reasoning in causal modelling. It is argued that causal models are regimented by a rationale of variation, nor of regularity neither invariance, thus breaking down the dominant (...) Human paradigm. The notion of variation is shown to be embedded in the scheme of reasoning behind various causal models: e.g. Rubin’s model, contingency tables, and multilevel analysis. It is also shown to be latent – yet fundamental – in many philosophical accounts. Moreover, it has significant consequences for methodological issues: the warranty of the causal interpretation of causal models, the levels of causation, the characterisation of mechanisms, and the interpretation of probability. This book offers a novel philosophical and methodological approach to causal reasoning in causal modelling and provides the reader with the tools to be up to date about various issues causality rises in social science. (shrink)

An approach to inference to the best explanation integrating a Popperianconception of natural laws together with a modified Hempelian account of explanation, one the one hand, and Hacking's law of likelihood (in its nomicguise), on the other, which provides a robust abductivist model of sciencethat appears to overcome the obstacles that confront its inductivist,deductivist, and hypothetico-deductivist alternatives.This philosophy of scienceclarifies and illuminates some fundamental aspects of ontology and epistemology, especially concerning the relations between frequencies and propensities. Among the most important (...) elements of this conception is thecentral role of degrees of nomic expectability in explanation, prediction,and inference, for which this investigation provides a theoretical defense. (shrink)

Philosophers agree that scientific explanations aim to produce understanding, and that good ones succeed in this aim. But few seriously consider what understanding is, or what the cues are when we have it. If it is a psychological state or process, describing its specific nature is the job of psychological theorizing. This article examines the role of understanding in scientific explanation. It warns that the seductive, phenomenological sense of understanding is often, but mistakenly, viewed as a cue of genuine understanding. (...) The article closes with a discussion of several new paths of research that tie the psychology of scientific explanation to cognate notions of learning, testimony, and understanding. (shrink)

The causal impacts of genes and environment on any one biological trait are inextricably entangled, and consequently it is widely accepted that it makes no sense in singleton cases to privilege either factor for particular credit. On the other hand, at a population level it may well be the case that one of the factors is responsible for more variation than the other. Standard methodological practice in biology uses the statistical technique of analysis of variance to measure this latter kind (...) of causal efficacy. In this paper, I argue that: 1) analysis of variance is in fact badly suited to this role; and. (shrink)

: At the turn of the twentieth century, comparative studies of human culture (ethnology) gave way to studies of the details of individual societies (ethnography). While many writers have noticed a political sub-text to this paradigm shift, they have regarded political interests as extrinsic to the change. The central historical issue is why anthropologists stopped asking global, comparative questions and started asking local questions about features of particular societies. The change in questions cannot be explained by empirical factors alone, and (...) following Jarvie, this essay argues that political factors motivate the change. Jarvie's understanding of the role played by egalitarian politics is criticized, and the essay develops a new model of how political or moral values can become constitutive of scientific inquiry. On the erotetic view of explanation, whether one proposition explains another depends on the choice of contrast class and relevance criterion. Since political or moral values can motivate these choices, explanation can depend on non-epistemic values. The essay argues that the comparative questions of nineteenth-century ethnology presupposed that Europeans were superior to other races. It closes by arguing that Fanz Boas recognized the political values implicit in nineteenth-century ethnology and rejected its questions on those grounds. (shrink)

I Introduction This essay will canvass recent philosophical accounts of human agency that deploy a notion of 'self' (or 'agent') causation. Some of these accounts try to explicate this notion, whereas others only hint at its nature by way of contrast with the causality exhibited by impersonal physical systems. In these latter theories, the authors' main argumentative burden is that the apparent fundamental differences between personal and impersonal causal activity strongly suggest mind-body dualism. I begin by noting two distinct, yet (...) not commonly distinguished, philosophical motivations for pursuing an agent-causal account of human agency. In the course of discussing the accounts that some philosophers have developed in response to these considerations, I reconsider both the linkage of agent causation with mind-body dualism and its sharp cleavage from impersonal (or 'event') causation. (shrink)

By a macro-level feature, I understand any feature that supervenes on, and is thus realized in, lower-level features. Recent discussions by Kim have suggested that such features cannot be causally relevant insofar as they are not classically reducible to lower-level features. This seems to render macro-level features causally irrelevant. I defend the causal relevance of some such features. Such features have been thought causally relevant in many examples that have underpinned philosophical work on causality. Additionally, in certain typical biological cases, (...) we conceive of causally relevant features at various compatible levels of analysis. When elaborated, these points make a strong prima facie case for macro-level causal relevance. However, we might abandon both the philosophical guideposts and the corresponding explanatory practice in the special sciences were we convinced that no reflective philosophical account could provide for the causal relevance there supposed. I show that such drastic measures are not necessary, for we can make sense of macro-level causal relevance by drawing on Paul Humphreys' recent work in ways suggested by the concrete examples considered here. (shrink)

Humeans are often accused of positing laws which fail to explain or are involved in explanatory circularity. Here, I will argue that these arguments are confused, but not because of anything to do with Humeanism: rather, they rest on false assumptions about causal explanation. I’ll show how these arguments can be neatly sidestepped if one takes on two plausible commitments which are motivated independently of Humeanism: first, that laws don’t directly feature in scientific explanation and second, the view that explanation (...) is contrastive. After outlining and motivating these views, I show how they bear on explanation-based arguments against Humeanism. (shrink)

Descriptions of social norms can be explanatory. The erotetic approach to explanation provides a useful framework. I describe one very broad kind of explanation-seeking why-question, a genus that is common to the special sciences, and argue that descriptions of norms can serve as an answer to such why-questions. I draw upon Woodward’s recent discussion of the explanatory role of generalizations with a significant degree of invariance. Descriptions of norms provide what is, in effect, a generalization regarding the kind of historically (...) contingent system— a group or society, a generalization with a significant degree of invariance. Key Words: explanation • invariance • norms • social sciences • erotetic • laws. (shrink)

I advance a new theory of causal relevance, according to which causal claims convey information about conditional probability functions. This theory is motivated by the problem of disjunctive factors, which haunts existing probabilistic theories of causation. After some introductory remarks, I present in Section 3 a sketch of Eells's (1991) probabilistic theory of causation, which provides the framework for much of the discussion. Section 4 explains how the problem of disjunctive factors arises within this framework. After rejecting three proposed solutions, (...) I offer in Section 6 a new approach to causation that avoids the problem. Decision-theoretic considerations also support the new approach. Section 8 develops the consequences of the new theory for causal explanation. The resulting theory of causal explanation incorporates the new insights while respecting important work on scientific explanation by Salmon (1971), Railton (1981), and Humphreys (1989). My conclusions are enumerated in Section 9. (shrink)

The investigation of probabilistic causality has been plagued by a variety of misconceptions and misunderstandings. One has been the thought that the aim of the probabilistic account of causality is the reduction of causal claims to probabilistic claims. Nancy Cartwright (1979) has clearly rebutted that idea. Another ill-conceived idea continues to haunt the debate, namely the idea that contextual unanimity can do the work of objective homogeneity. It cannot. We argue that only objective homogeneity in combination with a causal interpretation (...) of Bayesian networks can provide the desired criterion of probabilistic causality. (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.

Van Fraassen and others have urged that judgements of explanations are relative to why-questions; explanations should be considered good in so far as they effectively answer why-questions. In this paper, I evaluate van Fraassen's theory with respect to mathematical explanation. I show that his theory cannot recognize any proofs as explanatory. I also present an example that contradicts the main thesis of the why-question approach—an explanation that appears explanatory despite its inability to answer the why-question that motivated it. This example (...) shows how explanatory judgements can be context-dependent without being why-question-relative. (shrink)

I argue that causation is a contrastive relation: c-rather-than-C* causes e-rather-than-E*, where C* and E* are contrast classes associated respectively with actual events c and e. I explain why this is an improvement on the traditional binary view, and develop a detailed definition. It turns out that causation is only well defined in ‘uniform’ cases, where either all or none of the members of C* are related appropriately to members of E*.

A framework for representing a specific kind of emergent property instance is given. A solution to a generalized version of the exclusion argument is then provided and it is shown that upwards and downwards causation is unproblematical for that kind of emergence. One real example of this kind of emergence is briefly described and the suggestion made that emergence may be more common than current opinions allow.

Laboratory experimentation was once considered impossible or irrelevant in economics. Recently, however, economic science has gone through a real ‘laboratory revolution’, and experimental economics is now a most lively subfield of the discipline. The methodological advantages and disadvantages of controlled experimentation constitute the main subject of this thesis. After a survey of the literature on experiments in philosophy and economics, the problem of testing normative theories of rationality is tackled. This philosophical issue was at the centre of a famous controversy (...) in decision theory, during which a methodology of normative falsification was first articulated and used to assess experimental results. In the third chapter, the methodological advantages of controlled experimentation are illustrated and discussed with examples taken from the experiments on the so-called ‘preference reversal’ phenomenon. Laboratory testing allows to establish with a high degree of certainty that certain phenomena lie behind the experimental data, by means of independent testing, elimination of alternative hypotheses, and the use of different instruments of observation. The fourth chapter is devoted to a conceptual analysis of the problem of ‘parallelism’. This is the problem of inferring from the occurrence of a phenomenon in the laboratory, to its instantiation also in non-laboratory environments. Experimental economists have discussed parallelism at length, and their views are presented and criticised. Eventually, it is argued that parallelism is a factual matter and as such can only be established on empirical grounds. The fifth chapter provides an example of how one can argue for parallelism, focusing on the case of experimentation on the ‘winner’s curse’ phenomenon. The role of experiments as ‘mediators’ between theoretical models and their target domain of application is illustrated, and the structure of parallelism arguments analysed in detail. Finally, in the last chapter, economic experiments are compared to simulations, in order to highlight their specific characteristics. (shrink)

In the current literature on scientific explanation unification became unfashionable in favour of causal approaches. We want to bring unification back into the picture. In this paper we demonstrate that resemblance questions do occur in scientific practice and that they cannot be properly answered without unification. Our examples show that resemblance questions about particular facts demand what we call causal network unification, while resemblance questions about regularities require what we call mechanism unification. We clarify how these types of unification relate (...) to Philip Kitcher’s account, but also to causal and mechanistic accounts of explanation. (shrink)

Recent pleas for more heterodoxy in explaining economic action have been defending a pluralism for economics. In this article, I analyse these defences by scrutinizing the pluralistic qualities in the work of one of the major voices of heterodoxy, Tony Lawson. This scrutiny will focus on Lawson's alternatives concerning ontology and explanation to mainstream economics. Subsequently, I will raise some doubts about Lawson's pluralism, and identify questions that will have to be addressed by heterodox economists in order to maintain the (...) claim of pluralism. (shrink)

In a recent article in this journal, Federica Russo and Jon Williamson argue that an analysis of causality in terms of probabilistic relationships does not do justice to the use of mechanistic evidence to support causal claims. I will present Ronald Giere's theory of probabilistic causation, and show that it can account for the use of mechanistic evidence (both in the health sciences—on which Russo and Williamson focus—and elsewhere). I also review some other probabilistic theories of causation (of Suppes, Eells, (...) and Humphreys) and show that they cannot account for the use of mechanistic evidence. I argue that these theories are also inferior to Giere's theory in other respects. (shrink)

To clarify and illuminate the place of probability in science Ellery Eells and James H. Fetzer have brought together some of the most distinguished philosophers ...

The paper offers the outlines of a response to the often-made suggestion that it is impossible to see how indeterminism could possibly provide us with anything that we might want in the way of freedom, anything that could really amount to control, as opposed merely to an openness in the flow of reality that would constitute the injection of chance, or randomness, into the unfolding of the processes which underlie our activity. It is suggested that the best first move for (...) the libertarian is to make a number of important concessions to the compatibilist. It should be conceded, in particular, that certain sorts of alternative possibilities are neither truly available to real, worldly agents nor required in order that those agents act freely; and it should be admitted also that it is the compatibilist who tends to give the most plausible sorts of analyses of many of the 'can' and 'could have' statements which seem to need to be assertible of those agents we regard as free. But these concessions do not bring compatibilism itself in their wake. The most promising version of libertarianism, it is argued, is based on the idea that agency itself (and not merely some special instances of it which we might designate with the honorific appellation 'free') is inconsistent with determinism. This version of libertarianism, it is claimed, can avoid the objection that indeterminism is as difficult to square with true agential control as determinism can sometimes seem to be. (shrink)

To explain an intentional action one must exhibit the agent’s reasons. Donald Davidson famously argued that the only clear way to understand action explanation is to hold that reasons are causes. Davidson’s discussion conflated two issues: whether reasons are causes and whether reasons causally explain intentional action. Contemporary work on explanation and normativity help disentangle these issues and ground an argument that intentional action explanations cannot be a species of causal explanation. Interestingly, this conclusion is consistent with Davidson’s conclusion that (...) reasons are causes. In other words, reasons are causes, but rationalizing explanations are not causal explanations. Key Words: action theory • explanation • causal explanation • rationality • Donald Davidson. (shrink)

It seems that hope springs eternal for the cherished idea that norms (or normativeprinciples) explain actions or regularities in actions. But it also seems thatthere are many ways of going wrong when taking norms and normative principlesas explanatory. The author argues that neither norms nor normative principles—insofar as they are the sort of things with normative force—is explanatoryof what is done. He considers the matter using both erotetic and ontic models ofexplanation. He further considers various understandings of norms. Key Words: (...) explanation • norms • social science • rationality. (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.

This paper explores the idea that laws express relationships between properties or universals as defended in Michael Tooley's recent book Causation: A Realist Approach. I suggest that the most plausible version of realism will take a different form than that advocated by Tooley. According to this alternative, laws are grounded in facts about the capacities and powers of particular systems, rather than facts about relations between universals. The notion of lawfulness is linked to the notion of invariance, rather than to (...) the metaphysical notion of a necessary connection. (shrink)

Scientists and laypeople alike use the sense of understanding that an explanation conveys as a cue to good or correct explanation. Although the occurrence of this sense or feeling of understanding is neither necessary nor sufficient for good explanation, it does drive judgments of the plausibility and, ultimately, the acceptability, of an explanation. This paper presents evidence that the sense of understanding is in part the routine consequence of two well-documented biases in cognitive psychology: overconfidence and hindsight. In light of (...) the prevalence of counterfeit understanding in the history of science, I argue that many forms of cognitive achievement do not involve a sense of understanding, and that only the truth or accuracy of an explanation make the sense of understanding a valid cue to genuine understanding. (shrink)

I argue that the orthodox account of probabilistic causation, on which probabilistic causes determine the probability of their effects, is inconsistent with certain ontological assumptions implicit in scientific practice. In particular, scientists recognize the possibility that properties of populations can cause the behavior of members of the populations. Such emergent population‐level causation is metaphysically impossible on the orthodoxy.

In this paper I offer an 'integrating account' of singular causation, where the term 'integrating' refers to the following program for analysing causation. There are two intuitions about causation, both of which face serious counterexamples when used as the basis for an analysis of causation. The 'process' intuition, which says that causes and effects are linked by concrete processes, runs into trouble with cases of 'misconnections', where an event which serves to prevent another fails to do so on a particular (...) occasion and yet the two events are linked by causal processes. The chance raising intuition, according to which causes raise the chance of their effects, easily accounts for misconnections but faces the problem of chance lowering causes, a problem easily accounted for by the process approach. The integrating program attempts to provide an analysis of singular causation by synthesising the two insights, so as to solve both problems. In this paper I show that extant versions of the integrating program due to Eells, Lewis, and Menzies fail to account for the chance-lowering counterexample. I offer a new diagnosis of the chance lowering case, and use that as a basis for an integrating account of causation which does solve both cases. In doing so, I accept various assumptions of the integrating program, in particular that there are no other problems with these two approaches. As an example of the process account, I focus on the recent CQ theory of Wesley Salmon (1997). (shrink)

Carl Hempel argued that probabilistic hypotheses are limited in what they can explain. He contended that a hypothesis cannot explain why E is true if the hypothesis says that E has a probability less than 0.5. Wesley Salmon and Richard Jeffrey argued to the contrary, contending that P can explain why E is true even when P says that E’s probability is very low. This debate concerned noncontrastive explananda. Here, a view of contrastive causal explanation is described and defended. It (...) provides a new limit on what probabilistic hypotheses can explain; the limitation is that P cannot explain why E is true rather than A if P assign E a probability that is less than or equal to the probability that P assigns to A. The view entails that a true deterministic theory and a true probabilistic theory that apply to the same explanandum partition are such that the deterministic theory explains all the true contrastive propositions constructable from that partition, whereas the probabilistic theory often fails to do so. (shrink)

An enticing view about explanation consists of two theses. First, there is the Relevance Thesis, the thesis that the truth of explanation sentences depends on a contextually selected relevance relation. The idea is that whether an utterance is true depends on what factors the context counts as relevant. Second, there is the Contrastivity Thesis, the thesis that the truth of explanation sentences depends on a contextually determined contrastive focus. This metalinguistic view is enticing, and elements of it have been defended (...) by van Fraassen, Woodward, Schaffer, and others. Nevertheless, the enticing view is flawed; both the Contrastivity Thesis and the Relevance Thesis are mistaken. (shrink)

This work consists of two parts. Part I will be a contribution to a philo- sophical discussion of the nature of causal explanation. It will present my contrastive counterfactual theory of causal explanation and show how it can be used to deal with a number of problems facing theories of causal explanation. Part II is a contribution to a discussion of the na- ture of interest explanation in social studies of science. The aim is to help to resolve some controversies (...) concerning interest explanation by explicating the concept of interest and its explanatory uses by using the account of explanation developed in Part I. (shrink)