The nature of scientific explanation is controversial. Some maintain that all scientific explanations have to be contrastive in nature (contrastivism). However, others argue that no scientific explanation is genuinely contrastive (non-contrastivism). In addition, a compatibilist view has been recently devloped. It is argued that the debate between contrastivism and non-contrastivism is merely a linguistic dispute rather than a genuine disagreement on the nature of scientific explanation. Scientific explanations are both contrastive and non-contrastive in some sense (compatibilism). This paper examines the (...) debate between contrastivism and non-contrastivism in scientific explanation. It begins with a critical review of the arguments for contrastivism, for non-contrastivism, and for compatibilism and concludes with some remarks on the prospect of the issue. (shrink)

The starting point in the development of probabilistic analyses of token causation has usually been the naïve intuition that, in some relevant sense, a cause raises the probability of its effect. But there are well-known examples both of non-probability-raising causation and of probability-raising non-causation. Sophisticated extant probabilistic analyses treat many such cases correctly, but only at the cost of excluding the possibilities of direct non-probability-raising causation, failures of causal transitivity, action-at-a-distance, prevention, and causation by absence and omission. I show that (...) an examination of the structure of these problem cases suggests a different treatment, one which avoids the costs of extant probabilistic analyses. (shrink)

The turn from deterministic to probabilistic explanations has been used to argue that social science does not explain human action in ways that are incompatible with free will, since, according to some accounts of probabilism, causal factors merely influence actions without determining them. I argue that the notion of nondetermining causal influence is a multifaceted and problematic idea, which notably is unclear about whether the probability is objective or subjective, whether it applies to individual occurrences or merely to sets of (...) occurrences, and whether it is possible for an occurrence to be "almost determined.". (shrink)

The perennial fear associated with the free will problem is the prospect of hard determinism being true. Unlike prevalent attempts to reject hard determinism by defending compatibilist analyses of freedom and responsibility, this article outlines a pragmatic argument to the effect that we are justified in betting that determinism is false even though we may retain the idea that free will and determinism are incompatible. The basic argument is that as long as we accept that libertarian free will is worth (...) wanting, there is a defensible rationale, given the uncertainty which remains as to whether determinism is true or false, to refrain from acting on hard determinism, and thus to bet that libertarian free will exists. The article closes by discussing two potentially decisive objections to this pragmatic argument. (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)

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)

This essay explains what the Causal Markov Condition says and defends the condition from the many criticisms that have been launched against it. Although we are skeptical about some of the applications of the Causal Markov Condition, we argue that it is implicit in the view that causes can be used to manipulate their effects and that it cannot be surrendered without surrendering this view of causation.

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)

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.

Two apparently mutually exclusive ideas about the relation between contrastive and non-contrastive explanations can be found in the literature. According to contrastivists, all explanation is contrastive explanation and the supposed existence of non-contrastive explanations can be revealed to be an illusion. According to non-contrastivists, on the other hand, contrastive explanation can be fully analysed in terms of non-contrastive explanation, and is thus not of fundamental importance. In the current article, I discuss the main arguments in favour of and against each (...) of the two positions. This discussion leads to the idea that contrastive explanations are to be understood as parts of a bigger, more complete non-contrastive explanation; but that all actual explanations explain only a limited set of contrasts. I conclude that, once the relation between contrastive and non-contrastive explanations is understood correctly, there remains no substantial issue to divide contrastivism and non-contrastivism. (shrink)

Defending or attacking either functionalism or computationalism requires clarity on what they amount to and what evidence counts for or against them. My goal here is not to evaluate their plausibility. My goal is to formulate them and their relationship clearly enough that we can determine which type of evidence is relevant to them. I aim to dispel some sources of confusion that surround functionalism and computationalism, recruit recent philosophical work on mechanisms and computation to shed light on them, and (...) clarify how functionalism and computationalism may or may not legitimately come together. (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)

Sober and Lewontin's critique of genic selectionism is based upon the principle that a unit of selection should make a context‐independent contribution to fitness. Critics have effectively shown that this principle is flawed. In this paper I show that the context independence principle is an instance of a more general principle for characterizing causes,called the contextual unanimity principle. I argue that this latter principle, while widely accepted, is erroneous. What is needed is to replace the approach to causality characterized by (...) the contextual unanimity criterion with an approach based on the concept of causal mechanism. After sketching such an approach, I show how it can be used to shed light on the units of selection problem. (shrink)

Quantum mechanics portrays the universe as involving non-local influences that are difficult to reconcile with relativity theory. By postulating backward causation, retro-causal interpretations of quantum mechanics could circumvent these influences and accordingly reconcile quantum mechanics with relativity. The postulation of backward causation poses various challenges for the retro-causal interpretations of quantum mechanics and for the existing conceptual frameworks for analyzing counterfactual dependence, causation and causal explanation. In this chapter, we analyze the nature of time, causation and explanation in a local, (...) deterministic retro-causal interpretation of quantum mechanics that is inspired by Bohmian mechanics. This interpretation of quantum mechanics offers a deterministic, local ‘hidden-variables’ model of the Einstein-Podolsky-Rosen experiment that poses a new challenge for Reichenbach’s principle of the common cause. In this model, the common cause – the state of particles at the emission from the source – screens off the correlation between its effects – the distant measurement outcomes – but nevertheless fails to explain the correlation between the effects. (shrink)

This paper makes the case for a wider acceptance of a probabilistic approach to causation in negligence. This acceptance would help to remove much of the incoherence which has come to afflict the English law of personal injury law. This incoherence can also be found in other common law jurisdictions (notably those of the United States, Canada and Australia). Concentrating upon recent UK case law, the argument opposes the contention that ‘naked statistics’ can play no role in establishing causation. The (...) argument is controversial but it can be reduced to three unremarkable grounds: (1) With its acceptance (albeit in certain carefully prescribed circumstances) of liability for a negligently increased risk which has eventuated, the common law has already embraced a probabilistic conception of causation; (2) The English common law already employs a probabilistic (frequentist) approach to identifying coincidences; and (3) With the ‘balance of probabilities’ as the standard of proof in civil cases, the common law has long had a probabilistic (epistemic) concept at its core. Probabilistic approaches (at both the type and token level) are shown to be consistent with laypersons’ understanding of the concepts such as risk, chance, odds and likelihood. Moreover, a wider acceptance of a probabilistic perspective on causation would entail no major challenge to the fundamental aims of tort, viz. deterrence and corrective justice. (shrink)

Nancy Cartwright begins her recent book, Hunting Causes and Using Them, by noting that while a few years ago real causal claims were in dispute, nowadays “causality is back, and with a vengeance.” In the case of the social sciences, Keith Morrison writes that “Social science asks ‘why?’. Detecting causality or its corollary—prediction—is the jewel in the crown of social science research.” With respect to the health sciences, Judea Pearl writes that the “research questions that motivate most studies in the (...) health sciences are causal in nature.” However, not all data used by people interested in making causal claims come from experiments that use random assignment to control and treatment groups. Indeed, much research in the social and health science depends on non-experimental, observational data. Thus, one of the most important problems in the social and health sciences concerns making warranted causal claims using non-experimental, observational data; viz., “Can observational data be used to make etiological inferences leading to warranted causal claims?” This paper examines one method of warranting causal claims that is especially widespread in epidemiology and the health sciences generally—the use of causal criteria. It is argued that cases of complex causation generally, and redundant causation—both causal overdetermination and causal preemption—specifically, undermine the use of such criteria to warrant causal claims. (shrink)

Larry Wright and others have advanced causal accounts of functional explanation, designed to alleviate fears about the legitimacy of such explanations. These analyses take functional explanations to describe second order causal relations. These second order relations are conceptually puzzling. I present an account of second order causation from within the framework of Eells' probabilistic theory of causation; the account makes use of the population-relativity of causation that is built into this theory.

It it tempting to think that if an outcome had some probability of not occurring, then we cannot explain why that outcome in fact occurred. Despite this intuition, most philosophers of science have come to admit the possibility of indeterministic explanation. Yet some of them continue to hold that if an outcome was not determined, it cannot be explained why that outcome rather than some other occurred. I argue that this is an untenable compromise: if indeterministic explanation is possible, then (...) indeterministic contrastive explanation is possible too. In order to defend this conclusion, I develop an account of contrastive explanation. (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)

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)

The scope of this paper can be clarified by means of a well-known phenomenon that is usually called ‘industrial melanism’: the fact that the melanic form of the peppered moth became dominant in industrial areas in England in the second half of the nineteenth century. Such changes in relative phenotype frequencies are important explananda for population biologists. Apart from trying to explain such changes over time, population biologists also often try to explain differences between populations, e.g. why yellow shell colour (...) is dominant in certain colonies of land snails and almost absent in other colonies. The causal explanations that are given to address such explananda are the objects of analysis in this paper. Our primary aim is to explicate their structure: we want to capture the typical ingredients of causal explanations in population biology, and their organisation. Based on this explication, we discuss how natural selection fits into recent mechanical philosophy of science, and engage in the debate on the nature of evolutionary theory. (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)

Modern empirical macroeconomic models, known as structural autoregressions (SVARs) are dynamic models that typically claim to represent a causal order among contemporaneously valued variables and to merely represent non-structural (reduced-form) co-occurence between lagged variables and contemporaneous variables. The strategy is held to meet the minimal requirements for identifying the residual errors in particular equations in the model with independent, though otherwise not directly observable, exogenous causes (“shocks”) that ultimately account for change in the model. In nonstationary models, such shocks accumulate (...) so that variables have discernible trends. Econometricians have conceived of variables that trend in sympathy with each other (so-called “cointegrated variables”) as sharing one or more of these unobserved trends as a common cause. It is possible for estimates of the values of both the otherwise unobservable individual shocks and the otherwise unobservable common trends to be backed-out of cointegrated systems of equations. The issue addressed in this paper is whether and in what circumstances these values can be regarded as observations of real entities rather than merely artifacts of the representation of variables in the model. The issue is related, on the one hand, to practical methodological problems in the use of SVARs for policy analysis—e.g., does it make sense to estimate of shocks or trends in one model and then use them as measures of variables in a conceptually distinct model? The issue is also related to debates in the philosophical analysis of causation—particularly, whether we are entitled, as assumed by the developers of Bayes-net approaches, to rely on the causal Markov condition (a generalization of Reichenbach’s common-cause condition) or whether cointegration generates a practical example of Nancy Cartwright’s “byproducts” objection to the causal Markov condition. (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)

This article attacks “open systems” arguments that because constant conjunctions are not generally observed in the real world of open systems we should be highly skeptical that universal laws exist. This work differs from other critiques of open system arguments against laws of nature by not focusing on laws themselves, but rather on the inference from open systems. We argue that open system arguments fail for two related reasons; 1) because they cannot account for the “systems” central to their argument (...) (nor the implied systems labeled “exogenous factors” in relation to the system of interest) and 2) they are nomocentric, fixated on laws while ignoring initial and antecedent conditions that are able to account for systems and exogenous factors within a fundamentalist framework. (shrink)