Probabilistic Causation

In this note, I discuss the simplicity of rival statistical explanations of a correlation, couched in terms of Reichenbachian Common Cause Systems. Simplicity is analyzed in two components, the so-called intrinsic and contextual simplicity. I show that if one disentangles simplicity from explanatory power then the size of the system provides an adequate for simplicity in both of its dimensions.

Consider the following claims: -/- 1. The drought caused the famine. -/- 2. Drowsy driving causes crashes. -/- 3. How much I water my plant influences how tall it grows. -/- 4. How much novocaine a patient receives affects how much pain they will feel during dental surgery. -/- The metaphysics of causation asks questions about what it takes for claims like these to be true—what kind of relation the claims are about, and in virtue of what these relations obtain.

Though common sense says that causes must temporally precede their effects, the hugely influential interventionist account of causation makes no reference to temporal precedence. Does common sense lead us astray? In this paper, I evaluate the power of the commonsense assumption from within the interventionist approach to causal modeling. I first argue that if causes temporally precede their effects, then one need not consider the outcomes of interventions in order to infer causal relevance, and that one can instead use temporal (...) and probabilistic information to infer exactly when X is causally relevant to Y in each of the senses captured by Woodward’s interventionist treatment. Then, I consider the upshot of these findings for causal decision theory, and argue that the commonsense assumption is especially powerful when an agent seeks to determine whether so-called “dominance reasoning” is applicable. (shrink)

A cause may influence its effect via multiple paths. Paradigmatically (Hesslow [1974]), taking birth control pills both decreases one’s risk of thrombosis by preventing pregnancy and increases it by producing a blood chemical. Building on Pearl ([2001]), I explicate the notion of a path-specific effect. Roughly, a path-specific effect of C on E via path P is the degree to which a change in C would change E were they to be transmitted only via P. Facts about such effects may (...) be gleaned from the structural equations commonly used to represent the causal relationships among variables. I contrast my analysis of the Hesslow case with those given by theorists of probabilistic causality, who mistakenly link it to issues of causal heterogeneity, token-causation and indeterminism. The reason probabilistic theories misdiagnose this case is that they pay inadequate attention to the structural relationships among variables. (shrink)

Causal overdetermination occupies an uncomfortable place within all the major theories of causation. A natural solution to the problems it gives rise to would be to resolve overdetermination into preemption or joint causation. However, such a solution would seem to lead to individuate events in a fragile manner. The issue of such modal fragility is addressed and it is argued that events designated as effects are always fragile in a natural way and the putative problems of adopting modal fragility can (...) be resolved. It is also studied whether causal overdetermination could work in a setting where the overdetermining causes occur in different levels of reality. Typically postulated higher-level causes are shown to contradict the definitional features of overdetermination. There is thus no reasonable role for causal overdetermination and the notion should be abandoned. (shrink)

The pairing argument aims to demonstrate the impossibility of non-spatial objects (including minds) standing in causal relations. Its chief premises are (roughly) that causation requires pairing relations between causes and effects and that pairing relations require spatial relations. Critics have argued that the first claim suffers from counterexamples involving indeterministic causation. After briefly rehearsing the pairing argument and the objection from indeterministic causation, I offer two ways of revising the pairing argument to meet the objection from indeterministic causation.

The principle of common cause asserts that positive correlations between causally unrelated events ought to be explained through the action of some shared causal factors. Reichenbachian common cause systems are probabilistic structures aimed at accounting for cases where correlations of the aforesaid sort cannot be explained through the action of a single common cause. The existence of Reichenbachian common cause systems of arbitrary finite size for each pair of non-causally correlated events was allegedly demonstrated by Hofer-Szabó and Rédei in 2006. (...) This paper shows that their proof is logically deficient, and we propose an improved proof. (shrink)

Analyses of singular causation often make use of the idea that a cause increases the probability of its effect. Of particular salience in such accounts are the values of the probability function of the effect, conditional on the presence and absence of the putative cause, analysed around the times of the events in question: causes are characterized by the effect’s probability function being greater when conditionalized upon them. Put this way, it becomes clearer that the ‘behaviour’ of probability functions in (...) small intervals about the times in question ought to be of concern. In this article, I make an extended case that causal theorists employing the ‘probability raising’ idea should pay attention to the continuity question. Specifically, if the probability functions are ‘jumping about’ in ways typical of discontinuous functions, then the stability of the relevant probability increase is called into question. The rub, however, is that sweeping requirements for either continuity or discontinuity are problematic and, as I argue, this constitutes a ‘continuity bind’. Hence more subtle considerations and constraints are needed, two of which I consider: utilizing discontinuous first derivatives of continuous probability functions, and abandoning point probability for imprecise probability. _1_ Introduction _2_ Probability Trajectories and Continuity _2.1_ Probability trajectories _2.2_ Causation as discontinuous jumps _2.3_ Against systematic discontinuity _3_ Broader Discontinuity Concerns _4_ The Continuity Bind _4.1_ Retaining continuity with discontinuous first derivatives _4.2_ Imprecise probability trajectories _5_ Concluding Remarks Appendix. (shrink)

The issue of causal comparability in the social sciences underlies matters of both generalization and extrapolation. After critiquing two existing interpretations of comparability, due to Hitchcock and Hausman, I propose a distinction between ontological and epistemic comparability. While the former refers to whether two cases are actually comparable, the latter respects that in cases of incomplete information, we need to rely on whatever evidence we have of comparability. I argue, using a political science case study, that in those cases of (...) imperfect information, an epistemic homogeneity criterion can be an adequate justification for generalization. (shrink)

“Freedom” is a phenomenon in the natural world. This phenomenon—and indirectly the question of free will—is explored using a variety of systems-theoretic ideas. It is argued that freedom can emerge only in systems that are partially determined and partially random, and that freedom is a matter of degree. The paper considers types of freedom and their conditions of possibility in simple living systems and in complex living systems that have modeling subsystems. In simple living systems, types of freedom include independence (...) from fixed materiality, internal rather than external determination, activeness that is unblocked and holistic, and the capacity to choose or alter environmental constraint. In complex living systems, there is freedom in satisfaction of lower level needs that allows higher potentials to be realized. Several types of freedom also manifest in the modeling subsystems of these complex systems: in the transcending of automatism in subjective experience, in reason as instrument for passion yet also in reason ruling over passion, in independence from informational colonization by the environment, and in mobility of attention. Considering the wide range of freedoms in simple and complex living systems allows a panoramic view of this diverse and important natural phenomenon. (shrink)

Are there ‘degrees of causation’? Yes and no: causation is not a scalar relation, but different causes can contribute to a causing of an effect to different extents. In this paper, I motivate a probabilistic analysis of an event’s degree of contribution to a causing of an effect and explore some of its consequences.

Understanding probabilities as something other than point values has often been motivated by the need to find more realistic models for degree of belief, and in particular the idea that degree of belief should have an objective basis in “statistical knowledge of the world.” I offer here another motivation growing out of efforts to understand how chance evolves as a function of time. If the world is “chancy” in that there are non-trivial, objective, physical probabilities at the macro-level, then the (...) chance of an event e that happens at a given time is \ until it happens. But whether the chance of e goes to one continuously or not is left open. Discontinuities in such chance trajectories can have surprising and troubling consequences for probabilistic analyses of causation and accounts of how events occur in time. This, coupled with the compelling evidence for quantum discontinuities in chance’s evolution, gives rise to a “continuity bind” with respect to chance probability trajectories. I argue that a viable option for circumventing the continuity bind is to understand the probabilities “imprecisely,” that is, as intervals rather than point values. I then develop and motivate an alternative kind of continuity appropriate for interval-valued chance probability trajectories. (shrink)

An important distinction is that between selective abductions, which select an optimal candidate from given multitude of possible explanations, and creative abductions, which introduce new theoretical concepts and models. The article focuses on creative abductions, which are essential for scientific progress, although they are rarely discussed in the literature. Scientifically, fruitful creative abductions are demarcated from purely speculative abductions by means of three virtues which are possessed by the former but not by the latter: (i) providing unification, (ii) detecting common (...) causes and (iii) generating novel predictions by means of which they can be independently tested. Based on historical examples it is demonstrated that common cause abduction from correlated dispositions is the fundamental abductive operation by which new theoretical concepts and models are scientifically generated. Statistical factor analysis can be regarded as a statistical generalization of common cause abduction. (shrink)

Sober [2011] argues that some causal statements are a priori true and that a priori causal truths are central to explanations in the theory of natural selection. Lange and Rosenberg [2011] criticize Sober's argument. They concede that there are a priori causal truths, but maintain that those truths are only ‘minimally causal’. They also argue that explanations that are built around a priori causal truths are not causal explanations, properly speaking. Here we criticize both of Lange and Rosenberg's claims.

The paper argues that a causal explanation of the correlated outcomes of EPR-type experiments is desirable and possible. It shows how Bohmian mechanics and the GRW mass density theory offer such an explanation in terms of a non-local common cause.

Anything other than paraphrasing the well-known Heraclitean aphorism would not be more appropriate to portray the crux of the contribution of the three philosophers of the Budapest School, Gábor Hofer-Szabó, Miklós Rédei and Lázló E. Szabó, in the ongoing discussion of the principle of the common cause . Indeed, ‘common causes love to hide’ and for that reason critics and aspirant falsifiers of PCC find correlations which, at a first level of analysis, might lack a common cause explanation. But as (...) the authors argue such correlations do not amount to disconfirming evidence for the principle, since PCC does not specify where to search for a common cause of a correlation; it just states that there is one. PCC is neither falsifiable, nor verifiable; it is a metaphysical doctrine that can only be assessed for its plausibility in the light of theories of empirical science. This idea fosters the investigation of the existence of common causes of correlations in two fundamental physical t .. (shrink)

The Principle of the Common Cause is usually understood to provide causal explanations for probabilistic correlations obtaining between causally unrelated events. In this study, an extended interpretation of the principle is proposed, according to which common causes should be invoked to explain positive correlations whose values depart from the ones that one would expect to obtain in accordance to her probabilistic expectations. In addition, a probabilistic model for common causes is tailored which satisfies the generalized version of the principle, at (...) the same time including the standard conjunctive-fork model as a special case. (shrink)

We begin by considering two principles, each having the form causal completeness ergo screening-off. The first concerns a common cause of two or more effects; the second describes an intermediate link in a causal chain. They are logically independent of each other, each is independent of Reichenbach's principle of the common cause, and each is a consequence of the causal Markov condition. Simple examples show that causal incompleteness means that screening-off may fail to obtain. We derive a stronger result: in (...) a rather general setting, if the composite cause C1 & C2 & … & Cn screens-off one event from another, then each of the n component causes C1, C2, …, Cn must fail to screen-off. The idea that a cause may be ordinally invariant in its impact on different effects is defined; it plays an important role in establishing this no-go theorem. Along the way, we describe how composite and component causes can all screen-off when ordinal invariance fails. We argue that this theorem is relevant to assessing the plausibility of the two screening-off principles. The discovery of incomplete causes that screen-off is not evidence that causal completeness must engender screening-off. Formal and epistemic analogies between screening-off and determinism are discussed. (shrink)

The framework of causal Bayes nets, currently influential in several scientific disciplines, provides a rich formalism to study the connection between causality and probability from an epistemological perspective. This article compares three assumptions in the literature that seem to constrain the connection between causality and probability in the style of Occam's razor. The trio includes two minimality assumptions—one formulated by Spirtes, Glymour, and Scheines (SGS) and the other due to Pearl—and the more well-known faithfulness or stability assumption. In terms of (...) logical strength, it is fairly obvious that the three form a sequence of increasingly stronger assumptions. The focus of this article, however, is to investigate the nature of their relative strength. The comparative analysis reveals an important sense in which Pearl's minimality assumption is as strong as the faithfulness assumption and identifies a useful condition under which it is as safe as SGS's relatively secure minimality assumption. Both findings have notable implications for the theory and practice of causal inference. 1 Introduction2 Background: Inference of Causal Structure in Markovian Causal Models3 Three Assumptions of Simplicity4 A Comparison of P-minimality and Faithfulness5 A Comparison of P-minimality and SGS-minimality6 Methodological Formulations and Prior Knowledge of Causal Order7 Conclusion. (shrink)

The present paper deals with the tools that can be used to represent causation and to reason about it and, specifically, with their diversity. It focuses on so-called “causal probabilities”—that is, probabilities of effects given one of their causes—and critically surveys a recent paper in which Joyce argues that the values of these probabilities do not depend on one’s conception of causation. I first establish a stronger independence claim: I show that the very definition of causal probabilities is independent of (...) one’s conception of causation. Second, I investigate whether causal probabilities indeed take the same values under their different possible definitions. (shrink)

This article aims to analyze the scope and limits of common cause abduction which is a version of explanatory abduction based on Hans Reichenbach’s Principle of the Common Cause. First, it is argued that common cause abduction can be regarded as a rational inferential mechanism that enables us to accept hypotheses that aim to account for the surprising correlations of events. Three arguments are presented in support of common cause abduction: the argument from screening-off, the argument from likelihood, and the (...) argument from simplicity. Second, it is claimed, that common cause abduction is a defeasible reasoning, i.e., common cause abductive hypotheses are not always more plausible than separate cause abductive hypotheses. Finally, it is outlined what factors should be taken into account in order to use common cause abduction in a reasonable way. (shrink)

The aim of this article is to analyze the main contributions of Wesley C. Salmon to the philosophy of science, that is, his concepts of causation, common cause, and theoretical explanation, and to provide a critique of them. This critique will be based on a comparison of Salmon's concepts with categories developed by Hegel in his Science of Logic, and which can be applied to the issues treated by Salmon by means of the above given three concepts. It is the (...) author's contention that by means of Hegelian categories it becomes possible to provide a critique of Salmon's philosophy of science and at the same time to enlarge the concept framework of philosophy of science. (shrink)

In cognitive neuroscience and in philosophy of mind, causation is a notion that is immensely important but usually not defined precisely enough to afford careful application. A widespread basic flaw is the confusion of causation with correlation. All empirical knowledge in the sciences is based on observing correlations; assigning causal relations to them or interpreting them causally always requires a theoretical background that is implicitly or (better) explicitly stated. This entails that differing theoretical approaches might lead to different interpretations of (...) correlations. In this special volume we attempt to contribute to an improved understanding of causation, in general, and its relationship to consciousness studies, specifically. (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)

Accomplice liability makes people guilty of crimes they knowingly helped or encouraged others to commit, even if they did not commit the crime themselves. But this method of criminalizing aiders and abettors is fraught with problems. In this chapter, I argue that accomplice liability in the criminal law should be replaced with a system in which agents are criminalized on the basis of their individual contributions to causings of harm—the larger the contribution, the more severe the crime—regardless of whether those (...) contributions were made “through” the actions of another person. Not only would this avoid the issues associated with making the guilt of accomplices parasitic on the guilt of the principal, it would also fill gaps in the law concerning other cases to which accomplice liability does not apply. (shrink)

The book tackles these questions as well as others concerning the use of causality in the sciences.

Suppose that two geysers, about one mile apart, erupt at irregular intervals, but usually erupt almost exactly at the same time. One would suspect that they come from a common source, or at least that there is a common cause of their eruptions. And this common cause surely acts before both eruptions take place. This idea, that simultaneous correlated events must have prior common causes, was first made precise by Hans Reichenbach (Reichenbach 1956). It can be used to infer the (...) existence of unobserved and unobservable events, and to infer causal relations from statistical relations. Unfortunately it does not appear to be universally valid, nor is there agreement as to the circumstances in which it is valid. (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.

The aim of this talk unpublished until now, and that constitutes the last contribution of the author to this topic, is to show how Hans Reichenbach’s work “Die Kausalstruktur der Welt und der Unterschied zwischen Vergangenheit und Zukunft” , published in 1925, and significantly expanded and revised in the posthumously published book in 1956, The Direction of Time, inspires substantially part of the work that is carried out in the domain of causality at the beginning of the twenty first century.

In this paper we give a positive answer to a problem posed by Hofer-Szabó and Rédei (Int. J. Theor. Phys. 43:1819–1826, 2004) regarding the existence of infinite Reichenbachian common cause systems (RCCSs). An example of a countably infinite RCCS is presented. It is also determined that no RCCSs of greater cardinality exist.

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)

We offer a review of some of the most influential views on the status of Reichenbach’s Principle of the Common Cause (RPCC) for genuinely indeterministic systems. We first argue that the RPCC is properly a conjunction of two distinct claims, one metaphysical and another methodological. Both claims can and have been contested in the literature, but here we simply assume that the metaphysical claim is correct, in order to focus our analysis on the status of the methodological claim. We briefly (...) review the most entrenched or classical positions, including Salmon’s ‘interactive forks’, van Fraassen’s scepticism, and Cartwright’s generalisation of the fork criterion. We then go on to review the results of the ‘Budapest school’ on the existence of formally defined screening­ off events for any correlation —by means of the ideas of probability space extensibility and (Reichenbachian common cause) completability. We distinguish the Budapest doctrine clearly from any of the classical conceptions, and thus present an overall framework for discussions of causal inference in quantum mechanics. We argue that this review is preliminary essential work for a thorough assessment of the conditions under which RCCP may be a reliable tool for causal inference in a genuinely probabilistic (indeterministic) context. (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)

It is often argued that no local common cause models of EPR correlation exist. However, Szabó and Rédei pointed out that such arguments have the tacit assumption that plural correlations have the same common causes. Furthermore, Szabó showed that for EPR correlation a local common cause model in his sense exists. One of his requirements is that common cause events are statistically independent of apparatus settings on each side. However, as Szabó knows, to meet this requirement does not entail that (...) different combinations of common cause events (e.g. meet and join in lattice-theoretic terminology) are statistically independent of measurement settings. This further condition is formulated in two ways. First, the apparatus settings are completely independent of such combinations. Second, the apparatus settings on each side are independent of such combinations. Does a common cause model which meets the former and the latter respectively exist? This problem is considered. In particular, the latter version is Szabó’s and Rédei’s open problem. Negative answers are given to both versions. (shrink)

“Probabilistic Causation” designates a group of theories that aim to characterize the relationship between cause and effect using the tools of probability theory. The central idea behind these theories is that causes change the probabilities of their effects. This article traces developments in probabilistic causation, including recent developments in causal modeling. A variety of issues within, and objections to, probabilistic theories of causation will also be discussed.

Standard derivations of the Bell inequalities assume a common common cause system that is a common screener-off for all correlations and some additional assumptions concerning locality and no-conspiracy. In a recent paper (Grasshoff et al., 2005) Bell inequalities have been derived via separate common causes assuming perfect correlations between the events. In the paper it will be shown that the assumptions of this separate-common-cause-type derivation of the Bell inequalities in the case of perfect correlations can be reduced to the assumptions (...) of common-common-cause-system-type derivation. However, in the case of non-perfect correlations a non-reducible separate-common-cause-type derivation of some Bell-like inequalities can be given. The violation of these Bell-like inequalities proves Szabó's (2000) conjecture concerning the non-existence of a local, non-conspiratorial, separate-common-cause-model for a delta δ-neighborhood of perfect EPR correlations. (shrink)

Nancy Cartwright believes that we live in a Dappled World– a world in which theories, principles, and methods applicable in one domain may be inapplicable in others; in which there are no universal principles. One of the targets of Cartwright’s arguments for this conclusion is the Causal Markov condition, a condition which has been proposed as a universal condition on causal structures.1 The Causal Markov condition, Cartwright argues, is applicable only in a limited domain of special cases, and thus cannot (...) be used as a universal principle in causal discovery. I have no dispute with any of these claims here. Rather, I wish to argue for a very limited thesis: that the Causal Markov condition is applicable in the specific domain of microscopic quantum mechanical systems; further, that the condition can fruitfully be applied to the much discussed EPR setup. This is perhaps a surprising conclusion, for it is precisely in this domain that Cartwright’s arguments against the Causal Markov condition have been considered to be the most successful. (shrink)

Schaffer proposes a new account of probabilistic causation that synthesizes the probability-raising and process-linkage views on causation. The driving idea of Schaffer's account is that, although an effect does not invariably depend on its cause, a process linked to the effect does. In this paper, however, I will advance counterexamples to Schaffer's account and then demonstrate that Schaffer's possible responses to them do not work. Finally, I will argue that my counterexamples suggest that the driving idea of Schaffer's account is (...) misdirected. (shrink)

A partition $\{C_i\}_{i\in I}$ of a Boolean algebra Ω in a probability measure space (Ω, p) is called a Reichenbachian common cause system for the correlation between a pair A,B of events in Ω if any two elements in the partition behave like a Reichenbachian common cause and its complement; the cardinality of the index set I is called the size of the common cause system. It is shown that given any non-strict correlation in (Ω, p), and given any finite (...) natural number n > 2, the probability space (Ω,p) can be embedded into a larger probability space in such a manner that the larger space contains a Reichenbachian common cause system of size n for the correlation. (shrink)

Woodward present an argument for the Causal Markov Condition (CMC) on the basis of a principle they dub ‘modularity’ ([1999, 2004]). I show that the conclusion of their argument is not in fact the CMC but a substantially weaker proposition. In addition, I show that their argument is invalid and trace this invalidity to two features of modularity, namely, that it is stated in terms of pairwise independence and ‘arrow-breaking’ interventions. Hausman & Woodward's argument can be rendered valid through a (...) reformulation of modularity, but it is doubtful that the argument so revised provides any substantially new insight regarding the basis of the CMC. Introduction The CMC versus Hausman & Woodward's conclusion Hausman & Woodward's argument Modularity and independent error terms Conclusion Appendix: D-separation. (shrink)

We propose a new definition of actual causes, using structural equations to model counterfactuals. We show that the definition yields a plausible and elegant account of causation that handles well examples which have caused problems for other definitions and resolves major difficulties in the traditional account.

We provide a formally rigorous framework for integrating singular causation, as understood by Nuel Belnap's theory of causae causantes, and objective single case probabilities. The central notion is that of a causal probability space whose sample space consists of causal alternatives. Such a probability space is generally not isomorphic to a product space. We give a causally motivated statement of the Markov condition and an analysis of the concept of screening-off. 1. Causal dependencies and probabilities1.1Background: causation in branching space-times1.2What are (...) probabilities defined for?2. Basic transitions2.1Basics of basic transitions2.2Sets of basic transitions3. Causal probability theory3.1Some simple cases3.2General causal probabilities3.3Application: probability of suprema of a chain. (shrink)

Orthodox physicalism has a problem with mental causation. If physics is complete and mental events are not identical to physical events (as multiple-realisation arguments imply) it seems as though there is no causal work for the mental to do. This paper examines some recent attempts to overcome this problem by analysing causation in terms of counterfactuals or conditional probabilities. It is argued that these solutions cannot simultaneously capture the force of the completeness of physics and make room for mental causation.

Thirty years after Lewis's paper, this book brings together some of the most important recent work connecting—or, in some cases, disputing the connection ...

"Goodness of Fit": Clinical Applications from Infancy through Adult Life. By Stella Chess & Alexander Thomas. Brunner/Mazel, Philadelphia, PA, 1999. pp. 229. pound24.95 (hb). Chess and Thomas's pioneering longitudinal studies of temperamental individuality started over 40 years ago (Thomas et al., 1963). Their publications soon became and remain classics. Their concept of "goodness of fit" emerges out of this monumental work but has had a long gestation period. In their new book, the authors distinguish between behaviour disorders that are reactive (...) to the child's life circumstances, including life events, and which are self-correcting or responsive to the relevant changes in their environment, and more serious disorders. (shrink)