Philosophical analyses of causation have been centred on the question of what causation is. More precisely speaking, philosophers tend to address four different issues: metaphysical (what is causation out there?), epistemological (how can a causal claim be established and assessed?), conceptual (what does the word ‘cause’ mean?), and methodological (what methods ought one to use in order to establish and assess causal claims?). This chapter argues that the practical issue of causation (what is a causal claim for in practice?) is (...) highly relevant to the metaphysical, epistemological, conceptual, and methodological issues of causation. Any philosophical enquiry into causation without an examination of this practical issue is incomplete. In other words, a promising approach to causation ought to take all of the metaphysical, epistemological, conceptual, methodological, and practical issues into account. (shrink)

In my thesis, I develop two distinct themes. The first part of my thesis is devoted to indicative conditionals and approaching them from an empirically informed perspective. In the second part, I am developing classical topics of philosophy of science, specifically, scientific objectivity and the role of values in science, in connection to recent methodological developments, revolving around the Replication Crisis.

In her ‘Causality and Determination’, Anscombe argues for the strong thesis that despite centuries of philosophical assumption to the contrary, the supposition that causality and necessity have something essential to do with one another is baseless. In this paper, I assess Anscombe’s arguments and endorse her conclusion. I then attempt to argue that her arguments remain highly relevant today, despite the fact that most popular general views of causation today are firmly probabilistic in orientation and thus show no trace of (...) the assumptions Anscombe hoped to undermine. My suggestion is that Anscombe's interests in causality are distinct from those which mostly animate the modern debate about the general nature of causality and that in those specialized areas of philosophy in which those concerns still dominate, one can still see the effects of the fallacies and confusions to which she alerts us. I conclude by offering two possible complementary explanations of the tendency to suppose that causation is a variety of necessitation. (shrink)

According to the theory developed here, we may trace out the processes emanating from a cause in such a way that any consequence lying along one of these processes counts as an effect of the cause. This theory gives intuitive verdicts in a diverse range of problem cases from the literature. Its claims about causation will never be retracted when we include additional variables in our model. And it validates some plausible principles about causation, including Sartorio's ‘Causes as Difference Makers’ (...) principle and Hitchcock's ‘Principle of Sufficient Reason’. (shrink)

In this dissertation I develop a pluralist theory of actual causation. I argue that we need to distinguish between total, path-changing, and contributing actual causation. The pluralist theory accounts for a set of example cases that have raised problems for extant unified theories and it is supported by considerations about the various functions of causal concepts. The dissertation also analyses the context-sensitivity of actual causation. I show that principled accounts of causal reasoning in legal inquiry face limitations and I argue (...) that the context-sensitivity of actual causation is best represented by a distinction between default and deviant states in causal models. (shrink)

How do multiple reasons combine to support a conclusion about what to do or believe? This question raises two challenges: How can we represent the strength of a reason? How do the strengths of multiple reasons combine? Analogous challenges about confirmation have been answered using probabilistic tools. Can reductive and nonreductive theories of reasons use these tools to answer their challenges? Yes, or more exactly: reductive theories can answer both challenges. Nonreductive theories, with the help of a result in confirmation (...) theory, can answer one, and there are grounds for optimism that they can answer the other. (shrink)

The causal and simulation theories are often presented as very distinct views about declarative memory, their major difference lying on the causal condition. The causal theory states that remembering involves an accurate representation causally connected to an earlier experience. In the simulation theory, remembering involves an accurate representation generated by a reliable memory process. I investigate how to construe detailed versions of these theories that correctly classify memory errors as misremembering or confabulation. Neither causalists nor simulationists have paid attention to (...) memory-conjunction errors, which is unfortunate because both theories have problems with these cases. The source of the difficulty is the background assumption that an act of remembering has one target. I fix these theories for those cases. The resulting versions are closely related when implemented using tools of information theory, differing only on how memory transmits information about the past. The implementation provides us with insights about the distinction between confabulatory and non-confabulatory memory, where memory-conjunction errors have a privileged position. (shrink)

According to the deliberative view of democracy, the legitimacy of democratic politics is closely tied to whether the use of political power is accompanied by a process of rational deliberation among the citizenry and their representatives. Critics have questioned whether this level of deliberative capacity is even possible among modern citizenries--due to limitations of time, energy, and differential backgrounds--which therefore calls into question the very possibility of this type of democracy. In my dissertation, I counter this line of criticism, arguing (...) that deliberative democrats and their critics have both idealized the wrong kind of citizen deliberation. Citizen deliberation should not be concerned with the indeterminate project of "translating" abstract democratic principles and values into everyday cases of political problem-solving. Instead, deliberation should take the form of analogy, just as we already find it in everyday politics and affairs. When ordinary citizens use analogies, they do not derive decisions from general principles or values, but they still reason nonetheless. Seen from this analogical perspective, deliberative democracy is already a practical reality to a large degree. When an election is on the horizon, a campaign season arises in which debates, forums, and "barstool" dialogues exponentially increase the amount of citizen deliberation. In these settings, citizens can readily be seen to be mapping analogous past candidates, elections, issues, and problems onto those currently on the ballot so as to reason about them. Consequently, analogical reasoning allows citizens to treat the majority rule mechanisms that proliferate in real politics as "deliberative outlets," which is to say, as catalysts of deliberation akin to the "creative outlets" that catalyze self-expression in the arts. While citizens may recognize majority rule mechanisms as catalysts of deliberation, many democratic theorists will hesitate to embrace this vision of the practical reality of deliberative politics. Isn't analogical reasoning too low in rigor to be placed at the heart of the deliberative ideal? I develop two arguments to explain the foundational role analogy plays in deliberation and to counter such critics. First, I draw on the explosion of research on analogical reasoning over the past two decades to show that it is far more rigorous and systematic than many suppose. Second, I argue that to the extent that citizen deliberation is concerned with rational planning, rather than just reasoning in general, analogical reasoning is logically superior. When we reason about what to do, we make plans that incorporate predictions about what is likely to ensue when a given course of action is selected. However, as soon as predictions enter into deliberation, its underlying logic changes as well. The reason for this change in logic is that as our probabilistic reasoning expands, the probability of its conclusions degenerates. Therefore, when assessing probabilities, we no longer should seek decisions derived from long, elegant chains of reasoning that connect our various options to generalities like values and principles. Instead, what we need is "short and sweet," or terse, humble lines of reasoning, which are more congruent with this form of deliberation. Thus, to the extent that democratic deliberation is involved in rational planning, it calls not for the elegant, deductive kind of reasoning idealized by proponents and critics of deliberative democracy alike. Instead, democratic deliberation calls for the "short and sweet," analogical kind of decision-making we associate with ordinary citizens already. After all, as research has shown, analogies are a much preferred and rigorous way by which even experts engage in probabilistic reasoning. By focusing on analogical reasoning, I therefore conclude that the practical reality of deliberative democracy should be recognized in ways that might ordinarily be dismissed. (shrink)

"L'énigme majeure est la cause efficace" insiste Jean Largeault (1985). En effet, la physique contemporaine géométrise les phénomènes de la nature en transformant les causes efficientes en causalité formelle. Cependant elle nous invite aussi à accorder le structurel etle physique, le formel et le dynamique. Il convient donc de s'interroger sur le fondement du pouvoir créateur des mathématiques ou de leur caractère générateur en physique. Selon Charles de Koninck, la fécondité des mathématiques parait comme une intériorisation de la figure philosophique (...) de l'ange dans le cadre du projet d'une métamathématique comme angélologie thomiste. La raison poursuit un moyen de connaitre qui serait universel in repraesentando, par opposition à l'universel in praedicando. Cette tendance est essentielle à ce que l'on appelle le "mode platonicien". L'une des idées centrales de cet article consiste à établir une connexion profonde entre la notion de causalité en physique et cette manière platonicienne de connaitre. Plus précisément, l'idéalisation de la causalité efficace en physique mathématique est-il autre chose que ce mode dialectique de connaître abusivement porté à sa limite ? (shrink)

The mental realm seems different to the physical realm; the mental is thought to be dependent on, yet distinct from the physical. But how, exactly, are the two realms supposed to be different, and what, exactly, creates the seemingly insurmountable juxtaposition between the mental and the physical? This review identifies and discusses five marks of the mental, features that set characteristically mental phenomena apart from the characteristically physical phenomena. These five marks (intentionality, consciousness, free will, teleology, and normativity) are not (...) presented as a set of features that define mentality. Rather, each of them is something we seem to associate with phenomena we consider mental, and each of them seems to be in tension with the physical view of reality in its own particular way. It is thus suggested how there is no single mind-body problem, but a set of distinct but interconnected problems. Each of these separate problems is analyzed, and their differences, similarities and connections are identified. This provides a useful basis for future theoretical work on psychology and philosophy of mind, that until now has too often suffered from unclarities, inadequacies, and conflations. (shrink)

This dissertation shows how initial conditions play a special role in the explanation of contingent and irregular outcomes, including, in the form of geographic context, the special case of uneven development in the social sciences. The dissertation develops a general theory of this role, recognizes its empirical limitations in the social sciences, and considers how it might be applied to the question of uneven development. The primary purpose of the dissertation is to identify and correct theoretical problems in the study (...) of uneven development; it is not intended to be an empirical study. Chapter 1 introduces the basic problem, and discusses why it has become especially salient in debates concerning uneven development. Chapter 2 develops an argument for the importance of initial conditions in the philosophy of science, developed specifically in the context of the Bhaskar/Cartwright ‘open systems’ (and by extension, ‘exogenous factor’) emphasis on the ubiquity of contingency in the universe and rejection of explanation based on laws of nature (regularity accounts) of causation. Chapter 3 makes three claims concerning the concept of contingency, especially as related to the study of society: 1) that there are eight distinct uses of the word contingency, and its many meanings are detrimental to clarity of discussion and thought in history and the social sciences; 2) that it is possible to impose some order on these different uses through developing a classification of contingency into three types based on assumptions concerning possible worlds and determinism; 3) that one of the classes is a special use of the word without relevance to the social sciences, while the two remaining classes are nothing more than a variety of the ‘no hidden factors’ argument in the debate on indeterminism and determinism (and thus related to the concept of spacetime trajectories caused by initial conditions and the interference of these in the form of ‘exogenous factors’ with ‘open systems’). Chapter 4 The concept of explanation based on initial conditions together with laws of nature is widely associated with determinism. In the social sciences determinism has frequently been rejected due to the moral dilemmas it is perceived as presenting. Chapter 4 considers problems with this view. Chapter 5 considers attitudes among geographers, economists, and historians towards using geographic factors as initial conditions in explanation and how they might acceptably be used, in particular their role in ‘anchoring’ aspatial theories of social processes to real-world distributions. Chapter 6 considers the relationship of the statistical methods common in development studies with the trend towards integrating geographical factors into econometric development studies. It introduces the statistical argument on ‘apparent populations’ that arrives at conclusions concerning determinism consistent with Chapters 2 and 3 of the dissertation. The need for the visual interpretation of data with descriptive statistics and maps and their utility in the study of uneven development is discussed with a number of examples. Chapter 7 applies these concepts to the ‘institutions versus geography’ debate in development studies, using Acemoglu, Johnson and Robinson’s 2002 ‘reversal of fortune’ argument as a primary example. Chapter 8 considers possible directions for future work, both theoretical and empirical. Chapter 9 concludes with a discussion of additional possible objections to the use of initial conditions as exogenous factors in explanation. (shrink)

Abstract In Section 1 I examine the use of probabilistic data to establish causal conclusions in non?experimental research. In Section 2 I show that the probabilities involved in such research are inhomogeneous ?mixed? probabilities. Section 3 then argues that such mixed probabilities are responsible for the way common causes screen off correlations between their joint effects. Section 4 concludes that mixed probabilities are therefore crucial for the nature of the causal relation itself.

Questions about the metaphysics of causation may be usefully divided as follows. First, there are questions about the nature of the causal relata, including (1.1) whether they are in spacetime immanence), (1.2) how fine grained they are individuation), and (1.3) how many there are adicity). Second, there are questions about the metaphysics of the causal relation, including (2.1) what is the difference between causally related and causally unrelated sequences connection), (2.2) what is the difference between sequences related as cause to (...) effect, and those related as effect to cause or as joint effects of a common cause direction), and (2.3) what is the difference between sequences involving the cause, and those involving mere conditions selection). (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.

Hans Reichenbach is well known for his limiting frequency view of probability, with his most thorough account given in The Theory of Probability in 1935/1949. Perhaps less known are Reichenbach's early views on probability and its epistemology. In his doctoral thesis from 1915, Reichenbach espouses a Kantian view of probability, where the convergence limit of an empirical frequency distribution is guaranteed to exist thanks to the synthetic a priori principle of lawful distribution. Reichenbach claims to have given a purely objective (...) account of probability, while integrating the concept into a more general philosophical and epistemological framework. A brief synopsis of Reichenbach's thesis and a critical analysis of the problematic steps of his argument will show that the roots of many of his most influential insights on probability and causality can be found in this early work. (shrink)

This paper addresses a problem that arises when it comes to inferring deterministic causal chains from pertinent empirical data. It will be shown that to every deterministic chain there exists an empirically equivalent common cause structure. Thus, our overall conviction that deterministic chains are one of the most ubiquitous (macroscopic) causal structures is underdetermined by empirical data. It will be argued that even though the chain and its associated common cause model are empirically equivalent there exists an important asymmetry between (...) the two models with respect to model expansions. This asymmetry might constitute a basis on which to disambiguate corresponding causal inferences on non-empirical grounds. (shrink)

Several philosophers have embraced the view that high-level events—events like Zimbabwe's monetary policy and its hyper-inflation—are causally related if their corresponding low-level, fundamental physical events are causally related. I dub the view which denies this without denying that high-level events are ever causally related causal emergentism. Several extant philosophical theories of causality entail causal emergentism, while others are inconsistent with the thesis. I illustrate this with David Lewis's two theories of causation, one of which entails causal emergentism, the other of (...) which entails its negation. I then argue for causal emergentism on the grounds that it provides the only adequate means of squaring the apparent plenitude of causal relations between low-level events with the apparent scarcity of causal relations between high-level events. This tension between the apparent abundance of low-level causation and the apparent scarcity of high-level causation has been noted before. However, it has been thought that various theses about the semantics or the pragmatics of causal claims could be used to ameliorate the tension without going in for causal emergentism. I argue that none of the suggested semantic or pragmatic strategies meet with success, and recommend emergentist theories of causality in their stead. As Lewis's 1973 account illustrates, causal emergentism is consistent with the thesis that all facts reduce to microphysical facts. (shrink)

The foundations of probability are viewed through the lens of the subjectivist interpretation. This article surveys conditional probability, arguments for probabilism, probability dynamics, and the evidential and subjective interpretations of probability.

Many contemporary philosophers of physics (and philosophers of science more generally) follow Bertrand Russell in arguing that there is no room for causal notions in physics. Causation, as James Woodward has put it, has a ‘human face’, which makes causal notions sit ill with fundamental theories of physics. In this paper I examine a range of anti-causal arguments and show that the human face of causation is the face of scientific representations much more generally. Physics, like other sciences, is deeply (...) permeated with causal reasoning. (shrink)

This chapter provides an introduction to the study of the philosophical notions of mechanisms and causality in biology and economics. This chapter sets the stage for this volume, Mechanism and Causality in Biology and Economics, in three ways. First, it gives a broad review of the recent changes and current state of the study of mechanisms and causality in the philosophy of science. Second, consistent with a recent trend in the philosophy of science to focus on scientific practices, it in (...) turn implies the importance of studying the scientific methods employed by researchers. Finally, by way of providing an overview of each chapter in the volume, this chapter demonstrates that biology and economics are two fertile fields for the philosophy of science and shows how biological and economic mechanisms and causality can be synthesized. (shrink)

The development of causal modelling since the 1950s has been accompanied by a number of controversies, the most striking of which concerns the Markov condition. Reichenbach's conjunctive forks did satisfy the Markov condition, while Salmon's interactive forks did not. Subsequently some experts in the field have argued that adequate causal models should always satisfy the Markov condition, while others have claimed that non-Markovian causal models are needed in some cases. This paper argues for the second position by considering the multi-causal (...) forks, which are widespread in contemporary medicine (Section 2). A non-Markovian causal model for such forks is introduced and shown to be mathematically tractable (Sections 6, 7, and 8). The paper also gives a general discussion of the controversy about the Markov condition (Section 1), and of the related controversy about probabilistic causality (Sections 3, 4, and 5). (shrink)

In the following we will apply the manipulability theory of causation of Woodward 2003 to physical systems, and show that, in the latter context, the theory can be simplified. Elaborating on an argument by Cartwright, we will argue that the notions of ‘modularity’ and ‘intervention’ of the cited work should be adapted for typical physical systems, in order to take coupling of system equations into account. We will show that this allows to reduce all cause types discussed in Woodward 2003 (...) to only one, namely that of ‘total cause’. (shrink)

This paper attempts to set up a probabilistic framework for understanding the notion of causal necessity. What results is a relaxed and relativized probabilistic theory of epsilon-Causal necessity and an explicit attempt to avoid deterministic assumptions. The theory developed emphasizes the notions of partial cause, Causal contribution, And the degree of contribution. Implications for causal overdetermination, Causal preemption, And causal discourse are discussed.

Critics of functional explanations in social science maintain that such explanations are illegitimate unless a mechanism is specified. Others argue that mechanisms are not necessary for causal inference and that functional explanations are a type of causal claim that raise no special difficulties for testing. I show that there is indeed a special problem that confronts testing functional explanations resulting from their connection to second-order causal claims. I explain how mechanisms can resolve this difficulty, but argue that this does not (...) provide support for methodological individualism since it is not necessary that the mechanisms be described in terms of individual interactions. (shrink)

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

Non-reductive interventionist theories of causation and methodologies of causal reasoning embedded in that theoretical framework have become increasingly popular in recent years. This paper argues that one variant of an interventionist account of causation, viz. the one presented, for example, in Woodward (2003 ), is unsuited as a theoretical fundament of interventionist methodologies of causal reasoning, because it renders corresponding methodologies incapable of uncovering a causal structure in a finite number of steps. This finding runs counter to Woodward's own assessment (...) and to other recent studies which presume that Woodward's version of interventionism is effectively applicable to uncover causal structures, e.g. Campbell (2007 ) or Shapiro and Sober (2007 ). (shrink)

Russell famously argued that causation should be dispensed with. He gave two explicit arguments for this conclusion, both of which can be defused if we loosen the ties between causation and determinism. I show that we can define a concept of causation which meets Russell’s conditions but does not reduce to triviality. Unfortunately, a further serious problem is implicit beneath the details of Russell’s arguments, which I call the causal exclusion problem. Meeting this problem involves deploying a minimalist pragmatic account (...) of the nature and function of modal language. Russell’s scruples about causation can be accommodated, even as we partially legitimise the pervasive causal explanations in folk and scientific practice. (shrink)

In this paper an attempt is made at developing the notion of a real and complete empirical explanation as excluding all forms of potential or incomplete explanations. This explanation is, however, no longer conceived as the proper aim of empirical science, for it can certainly be gleaned from recent epistemological publications that no comprehensive notion of a real and complete scientific explanation is likely to be constructed from within empirical science. Contrary to common understanding the empirical explanation, deductive-nomological as well (...) as statistical explanation, is considered here only as motive of scientific activities, i.e., as common aim of a transcending cooperation of scientific and non-scientific social practice. Following from this the proper aim of empirical science now consists in the development of practically relevant explanatory theories.This redetermination of the aim of scientific activities of empirical science also means criticism of the unification of deductive-nomological and statistical explanations, as it has been proposed by Wolfgang Stegmüller in his pragmatisch-epistemische Wende. For both forms of empirical explanation must be referred to fundamentally different kinds of practical relevance, the former playing a more important role in the advancement of social practice. Stegmüller's development of a comprehensive probabilistic notion of empirical explanation, as tied up to pragmatic knowledge-situations, in a way already transcends a scientifically immanent determination of it, but he seems to have stopped halfway on the road to practically relevant empirical explanations. Several insufficiencies with his probabilistic notion of empirical explanation are shown up in this paper as a consequence of his abiding by pragmatic, and not penetrating to practical, knowledge-situations. The final result of it, however, consists in a clarification and a modification of the concept of deductive-nomological explanation, originally developed by Hempel and Oppenheim. (shrink)

Kolmogorov''s axiomatization of probability includes the familiarratio formula for conditional probability: 0).$$ " align="middle" border="0">.

Two kinds of causal inference rules which are widely used by social scientists are investigated. Two conceptions of causation also widely used are explicated — the INUS and probabilistic conceptions of causation. It is shown that the causal inference rules which link correlation, a kind of partial correlation, and a conception of causation areinvalid. It is concluded anew methodology is required for causal inference.

Is the common cause principle merely one of a set of useful heuristics for discovering causal relations, or is it rather a piece of heavy duty metaphysics, capable of grounding the direction of causation itself? Since the principle was introduced in Reichenbach’s groundbreaking work The Direction of Time (1956), there have been a series of attempts to pursue the latter program—to take the probabilistic relationships constitutive of the principle of the common cause and use them to ground the direction of (...) causation. These attempts have not all explicitly appealed to the principle as originally formulated; it has also appeared in the guise of independence conditions, counterfactual overdetermination, and, in the causal modelling literature, as the causal markov condition. In this paper, I identify a set of difficulties for grounding the asymmetry of causation on the principle and its descendents. The first difficulty, concerning what I call the vertical placement of causation, consists of a tension between considerations that drive towards the macroscopic scale, and considerations that drive towards the microscopic scale—the worry is that these considerations cannot both be comfortably accommodated. The second difficulty consists of a novel potential counterexample to the principle based on the familiar Einstein Podolsky Rosen (EPR) correlations in quantum mechanics. (shrink)

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

We argue against some of Reichenbach's claims about causal forks are incorrect. We do not see why the Second Law of Thermodynamics rules out the existence of conjunctive forks open to the past. In addition, we argue that a common effect rarely forms a conjunctive fork with its joint causes, but it sometimes does. Nevertheless, we think there is something to be said for Reichenbach's idea that forks of various kinds are relevant to explaining why we know more about the (...) past than about the future. And entropy turns out to play a role in the explanation, though not the determining role that Reichenbach envisions. (shrink)

We argue that the health sciences make causal claims on the basis of evidence both of physical mechanisms, and of probabilistic dependencies. Consequently, an analysis of causality solely in terms of physical mechanisms or solely in terms of probabilistic relationships, does not do justice to the causal claims of these sciences. Yet there seems to be a single relation of cause in these sciences - pluralism about causality will not do either. Instead, we maintain, the health sciences require a theory (...) of causality that unifies its mechanistic and probabilistic aspects. We argue that the epistemic theory of causality provides the required unification. (shrink)

Can Contemporary Science Inspire Philosophical and Theological Reflection on Causality? The cooperation between natural science, philosophy, and theology in an analysis of the causal structure and co-dependency of entities in the universe seems to be both legitimate and expected. It turns out, however, that in practice it oftentimes raises some tensions, questions and difficulties, leading to the development of alternative and in a sense competitive models of causality and of God’s action in the world. What is more, the attitude of (...) natural sciences since modernity, concentrated on gaining knowledge about natural phenomena to predict and control them, without trying to determine the nature of their ultimate causes, Humean criticism and rejection of the concept of causality as such, and concentration of analytic philosophers on the description of what accompanies phenomena classified as causal, leaving aside the question of the metaphysical status of causes and effects – they all seem to make impossible an interaction and mutual reference of contemporary science, philosophy, and theology in their reflection on the topic of causation. The main goal of this article is to defend the thesis about the possible and actual influence of scientific analysis of cause and effect relationships on the philosophical and theological reflection on causation, not only in the Middle Ages and Modernity, but also in contemporary thought. The presentation of the latest positions in the debate on divine action in the natural world will be followed by an argument in favor of the relevance of the model developed by philosophers and theologians representing the Thomistic school. (shrink)

Causal reasoning is one of our most central cognitive competencies, enabling us to adapt to our world. Causal knowledge allows us to predict future events, or diagnose the causes of observed facts. We plan actions and solve problems using knowledge about cause-effect relations. Without our ability to discover and empirically test causal theories, we would not have made progress in various empirical sciences. In the past decades, the important role of causal knowledge has been discovered in many areas of cognitive (...) psychology. Despite the ubiquity of causal reasoning, textbooks of cognitive psychology have neglected this growing field. The goal of The Oxford Handbook of Causal Reasoning is to fill this gap. The handbook brings together the leading researchers in the field of causal reasoning and offers state-of-the-art presentations of theories and research. It provides introductions of competing theories of causal reasoning, and discusses its role in various cognitive functions and domains. The final section presents research from neighboring fields. 1. Causal Reasoning: An Introduction Michael R. Waldmann Part I: Theories of Causal Cognition 2. Associative Accounts of Causal Cognition Mike E. Le Pelley, Oren Griffiths, and Tom Beesley 3. Rules of Causal Judgment: Mapping Statistical Information Onto Causal Beliefs José C. Perales, Andrés Catena, Antonio Cándido, and Antonio Maldonado 4. The Inferential Reasoning Theory of Causal Learning: Toward a Multi- Process Propositional Account Yannick Boddez, Jan De Houwer, and Tom Beckers 5. Causal Invariance as an Essential Constraint for Creating a Causal Representation of the World: Generalizing the Invariance of Causal Power Patricia W. Cheng and Hongjing Lu 6. The Acquisition and Use of Causal Structure Knowledge Benjamin Margolin Rottman 7. Formalizing Prior Knowledge in Causal Induction Thomas L. Griffiths 8. Causal Mechanisms Samuel G. B. Johnson and Woo-kyoung Ahn 9. Force Dynamics and Causation Phillip Wolff and Robert Thorstad 10. Mental Models and Causation P. N. Johnson- Laird and Sangeet S. Khemlani 11. Pseudocontingencies Klaus Fiedler and Florian Kutzner 12. Singular Causation David Danks 13. Cognitive Neuroscience of Causal Reasoning Joachim T. Operskalski and Aron K. Barbey Part II: Basic Cognitive Functions 14. Visual Impressions of Causality Peter White 15. Goal-Directed Actions Bernhard Hommel 16. Planning and Control Magda Osman 17. Reinforcement Learning and Causal Models Samuel J. Gershman 18. Causation and the Probability of Causal Conditionals David E. Over 19. Causal Models and Conditional Reasoning Mike Oaksford and Nick Chater 20. Concepts as Causal Models: Categorization Bob Rehder 21. Concepts as Causal Models: Induction Bob Rehder 22. Causal Explanation Tania Lombrozo and Nadya Vasilyeva 23. Diagnostic Reasoning Björn Meder and Ralf Mayrhofer 24. Inferring Causal Relations by Analogy Keith J. Holyoak and Hee-Seung Lee 25. Causal Argument Ulrike Hahn, Roland Bluhm, and Frank Zenker 26. Causality in Decision- Making York Hagmayer and Philip M. Fernbach Part III: Domains of Causal Reasoning 27. Intuitive Theories Tobias Gerstenberg and Joshua B. Tenenbaum 28. Space, Time, and Causality Marc J. Buehner 29. Causation in Legal and Moral Reasoning David A. Lagnado and Tobias Gerstenberg 30. The Role of Causal Knowledge in Reasoning About Mental Disorders Woo-kyoung Ahn, Nancy S. Kim, and Matthew S. Lebowitz 31. Causality and Causal Reasoning in Natural Language Torgrim Solstad and Oliver Bott 32. Social Attribution and Explanation Denis Hilton Part IV: Development, Phylogeny, and Culture 33. The Development of Causal Reasoning Paul Muentener and Elizabeth Bonawitz 34. Causal Reasoning in Non-Human Animals Christian Schloegl and Julia Fischer 35. Causal Cognition and Culture Andrea Bender, Sieghard Beller, and Douglas L. Medin. (shrink)

We propose an account of dynamic predicates which draws on the notion of force, eliminating reference to events in the linguistic semantics. We treat dynamic predicates as predicates of forces, represented as functions from an initial situation to a final situation that occurs ceteris paribus, that is, if nothing external intervenes. The possibility that opposing forces might intervene to prevent the transition to a given final situation leads us to a novel analysis of non-culminating accomplishment predicates in a variety of (...) languages, including the English progressive. We then apply the force-theoretic framework to the composition of basic Vendlerian eventuality types within a lexical-decomposition syntax. The difference between predicates of forces and predicates of situations is argued to underlie the dynamic/stative contrast, and also to allow for a formal treatment of the difference between be and stay. Consequences for the relationship between language and cognition are discussed. (shrink)

Social research, from economics to demography and epidemiology, makes extensive use of statistical models in order to establish causal relations. The question arises as to what guarantees the causal interpretation of such models. In this paper we focus on econometrics and advance the view that causal models are ‘augmented’ statistical models that incorporate important causal information which contributes to their causal interpretation. The primary objective of this paper is to argue that causal claims are established on the basis of a (...) plurality of evidence. We discuss the consequences of ‘evidential pluralism’ in the context of econometric modelling. (shrink)

We clarify the notions scientific process and social process with structuralist means. Three questions are formulated, and answered in the structuralistic, set-theoretic framework. What is a scientific process, and a process in science? What can be meant by a non-social process? In which sense a non-social process can be a part of a scientific process in social science? We are specifically interested in social processes. Our answers use the notion of the generalized subset relation applied to set-theoretical structures, and the (...) set of structuralistically reconstructed empirical theories. (shrink)

This paper outlines a theory and computer implementation of causal meanings and reasoning. The meanings depend on possibilities, and there are four weak causal relations: A causes B, A prevents B, A allows B, and A allows not‐B, and two stronger relations of cause and prevention. Thus, A causes B corresponds to three possibilities: A and B, not‐A and B, and not‐A and not‐B, with the temporal constraint that B does not precede A; and the stronger relation conveys only the (...) first and last of these possibilities. Individuals represent these relations in mental models of what is true in the various possibilities. The theory predicts a number of phenomena, and, contrary to many accounts, it implies that the meaning of causation is not probabilistic, differs from the meaning of enabling conditions, and does not depend on causal powers or mechanisms. The theory also implies that causal deductions do not depend on schemas or rules. (shrink)

Information about the structure of a causal system can come in the form of observational data—random samples of the system's autonomous behavior—or interventional data—samples conditioned on the particular values of one or more variables that have been experimentally manipulated. Here we study people's ability to infer causal structure from both observation and intervention, and to choose informative interventions on the basis of observational data. In three causal inference tasks, participants were to some degree capable of distinguishing between competing causal hypotheses (...) on the basis of purely observational data. Performance improved substantially when participants were allowed to observe the effects of interventions that they performed on the systems. We develop computational models of how people infer causal structure from data and how they plan intervention experiments, based on the representational framework of causal graphical models and the inferential principles of optimal Bayesian decision‐making and maximizing expected information gain. These analyses suggest that people can make rational causal inferences, subject to psychologically reasonable representational assumptions and computationally reasonable processing constraints. (shrink)

Causation is in trouble—at least as it is pictured in current theories in philosophy and in economics as well, where causation is also once again in fashion. In both disciplines the accounts of causality on offer are either modelled too closely on one or another favoured method for hunting causes or on assumptions about the uses to which causal knowledge can be put—generally for predicting the results of our efforts to change the world. The first kind of account supplies no (...) reason to think that causal knowledge, as it is pictured, is of any use; the second supplies no reason to think our best methods will be reliable for establishing causal knowledge. So, if these accounts are all there is to be had, how do we get from method to use? Of what use is knowledge of causal laws that we work so hard to obtain? (shrink)

Backtracking influence is influence that zigzags in time. For example, backtracking influence exists when an event E_1 makes an event E_2 more likely by way of a nomic connection that goes from E_1 back in time to an event C and then forward in time to E_2. I contend that in our local region of spacetime, at least, backtracking influence is redundant in the sense that any existing backtracking influence exerted by E_1 on E_2 is equivalent to E_1's temporally direct (...) influence on E_2. I prove the redundancy of backtracking influence using several plausible physical principles without assuming any fundamental temporal or causal asymmetry. This explanation can play a prominent role in an account of why causation appears to be objectively asymmetric regardless of whether the fundamental laws are symmetric. (shrink)