“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.

In this article, I explore the compatibility of inference to the best explanation (IBE) with several influential models and accounts of scientific explanation. First, I explore the different conceptions of IBE and limit my discussion to two: the heuristic conception and the objective Bayesian conception. Next, I discuss five models of scientific explanation with regard to each model’s compatibility with IBE. I argue that Kitcher’s unificationist account supports IBE; Railton’s deductive–nomological–probabilistic model, Salmon’s statistical-relevance model, and van Fraassen’s erotetic account are (...) incompatible with IBE; and Salmon’s causal–mechanical model is merely consistent with IBE. In short, many influential models of scientific explanation do not support IBE. I end by outlining three possible conclusions to draw: (1) either philosophers of science or defenders of IBE have seriously misconstrued the concept of explanation, (2) philosophers of science and defenders of IBE do not use the term ‘explanation’ univocally, and (3) the ampliative conception of IBE, which is compatible with any model of scientific explanation, deserves a closer look. (shrink)

This paper takes a critical stance on Tallis’s separation of causation and agency. While his critique of the causal theory of action and the assumptions about causation underlying different versions of determinism, including the one based on neuroscience is right, his rejection of causation (of all sorts) has implausible consequences. Denying the link between action and causation amounts to overlooking the role action plays in causal inference and in the origin of causal concepts. I suggest that a weaker version of (...) Tallis’ claim, compatible with causation understood as agency, would work better. (shrink)

Theory of illness causation is an important issue in all biomedical sciences, and solid etiological explanations are needed in order to develop therapeutic approaches in medicine and preventive interventions in public health. Until now, the literature about the theoretical underpinnings of illness causation research has been scarce and fragmented, and lacking a convenient summary. This interdisciplinary book provides a convenient and accessible distillation of the current status of research into this developing field, and adds a personal flavor to the discussion (...) by proposing the etiological stance as a comprehensive approach to identify modifiable causes of illness. (shrink)

Definiciones de epistemología hay muchas, al igual que clases y estilos. Sin embargo, más allá de esta diversidad, es necesario contar con una definición básica que guíe nuestra comprensión del tema. Dos serán las preguntas que nos ayuden a ello en este artículo: a) ¿qué es la epistemología? y b) ¿para qué le sirve al científico?

I present Aristotle’s theory of causation in a way that privileges a comparison with contemporary discussion on causation. I do so by selecting in Aristotle’s theory points that are interesting to contemporary discussion and by translating Aristotle in the contemporary philosophical terminology. I compare Aristotle’s views with Mackie’s (1993/1965) and Sosa’s (1993/1980). Mackie is a humean regularist regarding the metaphysics of causal necessity, but his theory postulates some formal aspects of the causal relation which are similar to the Aristotelian theory. (...) By introducing the notion of causal field as a third causal relatum – a sample in which the cause must be picked out as a explanation coextensive to the effect –, Mackie holds a point very similar to Aristotle, inasmuch as both defend that the causal relation is triadic and both have the extensional desideratum. Sosa (1993/1980) defends that every cause necessitates its effect, arguing against classical Humeanism, and he also proposes a causal pluralism. Both these theses are clearly Aristotelian. Aristotle comprehends that the causal relation has three relata: a subjacent C, a property of that subjacent A and a cause B that explains why such property is attributed to that subjacent. The subjacent is similar to Mackie’s notion of causal field, for in regard to it the cause must be coextensive to the property. But Aristotle also says that for each explanandum (property attributed to a subjacent of which one aims to investigate a cause) there is only one cause, which necessitates it. Sosa and Aristotle are similar because both develop a causal pluralism from a theory of causes as having intrinsic necessitation. For Aristotle, causes/explanations [aitiai] are central for attaining scientific knowledge, and its triadic structure determines the syllogistic structure of scientific demonstrations. Aristotle’s theory of causation also involves comprehending the actualisation of capacities (dispositional properties of objects) affirming that the causal relation is resultant from intrinsic properties of the objects, and the cause B is the essence of the explanandum. (shrink)

Grounding is often glossed as metaphysical causation, yet no current theory of grounding looks remotely like a plausible treatment of causation. I propose to take the analogy between grounding and causation seriously, by providing an account of grounding in the image of causation, on the template of structural equation models for causation.

How do people attribute responsibility in situations where the contributions of multiple agents combine to produce a joint outcome? The prevalence of over-determination in such cases makes this a difficult problem for counterfactual theories of causal responsibility. In this article, we explore a general framework for assigning responsibility in multiple agent contexts. We draw on the structural model account of actual causation (e.g., Halpern & Pearl, 2005) and its extension to responsibility judgments (Chockler & Halpern, 2004). We review the main (...) theoretical and empirical issues that arise from this literature and propose a novel model of intuitive judgments of responsibility. This model is a function of both pivotality (whether an agent made a difference to the outcome) and criticality (how important the agent is perceived to be for the outcome, before any actions are taken). The model explains empirical results from previous studies and is supported by a new experiment that manipulates both pivotality and criticality. We also discuss possible extensions of this model to deal with a broader range of causal situations. Overall, our approach emphasizes the close interrelations between causality, counterfactuals, and responsibility attributions. (shrink)

I argue that, in his effort to overcome causation as an obstacle to agency or free will, Raymond Tallis’ self-described “Humean” re-working of David Hume’s analysis of causation falters on historicotextual and conceptual grounds.

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)

Concrete Causation centers about theories of causation, their interpretation, and their embedding in metaphysical-ontological questions, as well as the application of such theories in the context of science and decision theory. The dissertation is divided into four chapters, that firstly undertake the historical-systematic localization of central problems (chapter 1) to then give a rendition of the concepts and the formalisms underlying David Lewis' and Judea Pearl's theories (chapter 2). After philosophically motivated conceptual deliberations Pearl's mathematical-technical framework is drawn on for (...) an epistemic interpretation and for emphasizing the knowledge-organizing aspect of causality in an extension of the interventionist Bayes net account of causation (chapter 3). Integrating causal and non-causal knowledge in unified structures ultimately leads to an approach towards solving problems of (causal) decision theory and at the same time facilitates the representation of logical-mathematical, synonymical, as well as reductive relationships in efficiently structured, operational nets of belief propagation (chapter 4). (shrink)

Through the introduction of his ‘common cause principle’ [The Direction of Time, 1956], Hans Reichenbach was the first to formulate a precise link relating causal claims to statements of probability. Despite some criticism, the principle has been hugely influential and successful—a pillar of scientific practice, as well as guiding our reasoning in everyday life. However, Bell’s theorem, taken in conjunction with quantum theory, challenges this principle in a fundamental sense at the microscopic level. For the same reason, the celebrated causal (...) model framework pioneered by Pearl, as well as by Spirtes, Glymour and Scheines, defies satisfactory causal explanations of quantum correlations—the role of the ‘causal Markov condition’ in this framework amounts to a generalisation of Reichenbach’s principle. Much effort has been devoted to the development of quantum causal models to overcome this challenge and to study whether a principled way of causal reasoning, albeit adjusted in its terms, can be maintained when it comes to quantum physics. A clarification of what quantum causal relations are supposed to be is also a much needed step in light of the hotly debated topic of causality in foundations of quantum theory, e.g. in the study of ‘indefinite causal structures’. This paper reports and discusses a framework of quantum causal models and argues that it is promising and interesting for two main reasons. First, it can be seen as a prime example of a recent research programme that took direct and fruitful inspiration from ideas first formulated by Reichenbach—it began by asking, and giving an answer to, how the common cause principle could be generalised appropriately to quantum theoretical terms. Second, the framework did not only facilitate generalisations of the core theorems of the classical framework of causal models, but, above all, it has a theorem at its center that justifies the ‘quantum causal Markov condition’ on the basis of what arguably is a natural definition of causal relations in quantum theory. This provides a conceptually clear grounding of the framework, as well as a proposal for the needed clarification of quantum causal relations in the foundations of quantum theory more generally. (shrink)

In the present paper we propose to approach the Spinoza`s methodological project from a philosophical and historical perspective broad enough to adequately understand the reasons that led him to adopt geometric method to expose his philosophy. Even if the topic has been widely discussed by Spinoza´s commentators in the four centuries since the Ethics was published, we believe that the approaches are either inadequate or suffer from some fragmentation, in the sense that they address this or that aspect, but don`t (...) put together all pieces that make up the puzzle. Likewise, we consider that a full understanding of such application of geometric method transcends the mere question of whether it was successful or not in terms of logical rigor. So that, the fundamental task in the present work is unite various aspects that help us understand Spinoza`s methodological choice in a synoptic vision, in which both historical and systematic aspects can be included. To this end, we start from a hypothesis which allow us glimpse a certain unity behind the reasons that lead Spinoza to choose the geometric method, namely: our philosopher tries to reach an ideal of science, which combines some conceptual elements of Aristotelian tradition with others from Cartesian philosophy. (shrink)

Powers are properties defined by what they do. The focus of the large majority of the powers literature has been mainly put on explicating the (multifaceted) results of the production of a power in certain (multifaceted) initial conditions: but all this causal complexity is bound to be—and, in fact, it has proved to be—quite difficult to handle. In this paper we take a different approach by focusing on the very activity of producing those multifaceted manifestations themselves. In this paper, we (...) propose an original account of what the essence of a power consists in which stems from a radical reconceptualisation of power-causation according to which counterfactuals are to be explained away by powers, and not vice-versa. We call this approach the dynamical operator account of powers. According to this account, the causal role of powers consists in their ensuring that the ontological transition from a stimulus S to a manifestation M happens. Powers thus have a dynamical essence which consists in the fundamental activity of generating the counterfactuals typically associated with them. We show that if one conceptualises this functional activity as the metaphysical fulcrum around which counterfactual-based causation revolves, one is granted not only an improved methodology to individuate powers but also a better understanding of their knowability, modality and directedness. (shrink)

This article illustrates instrumental variable (IV) estimation by examining an unexpected finding of the research on career adaptability and job satisfaction. Theoretical and empirical arguments suggest that in the general population, people’s abilities to adapt their careers are beneficial to their job satisfaction. However, a recent meta-analysis unexpectedly found no effect when personality traits are controlled for. We argue that a reverse effect of job satisfaction on career adaptability, originating from affective tendencies tied to personality, might explain this null effect. (...) Our argument implies that the estimates obtained with traditional ordinary least squares (OLS) regressions are biased by endogeneity, a correlation between an explanatory variable and the error term in a regression model. When experimental manipulations are impossible, IV estimations, such as two-stage least squares (2SLS) regressions, are one possible solution to the endogeneity problem. Analyzing three waves of data from a sample of 836 adults, the concurrent and time-lagged effect of job satisfaction on career adaptability was revealed to be more consistent than the reverse. Our results provide an explanation, rooted in affective dispositions, as to why recent meta-analytical estimates unexpectedly found that career adaptability does not predict job satisfaction at the interindividual level. We also discuss IV estimation in terms of its limits, weight the interpretation of its estimates against the temporality criterion for causal inference, and consider its possible extension to analyses of change. (shrink)

Whether there exist causal relations between guns firing and people dying, between pedals pressed and cars accelerating, or between carbon dioxide emissions and global warming, is typically taken to be a mind-independent, objective, matter of fact. However, recent contributions to the literature on causation, in particular theories of contrastive causation and causal modelling, have undermined this central causal platitude by relativising causal facts to models or to interests. This thesis flies against the prevailing wind by arguing that we must pay (...) greater attention to which elements of our causal talk vary with context and which elements track genuine features of the world around us. I will argue that once these elements are teased apart we will be in a position to better understand some of the most persistent problems in the philosophy of causation: pre-emption cases, absence causation, failures of transitivity and overdetermination. The result is a naturalist account of causation, concordant with the contextual variability we find in our ordinary causal talk, and parsimonious with respect to the theoretical entities posited. (shrink)

Causal inference plays a central role in behavioral science. Historically, behavioral science methodologies have typically sought to infer a single causal relation. Each of the major approaches to causal inference in the behavioral sciences follows this pattern. Nonetheless, such approaches sometimes differ in the causal relation that they infer. Incremental causal inference offers an alternative to this conceptualization of causal inference that divides the inference into a series of incremental steps. Different steps infer different causal relations. Incremental causal inference is (...) consistent with both causal pluralism and anti-pluralism. However, anti-pluralism places greater constraints the possible topology of sequential inferences. Arguments against causal inference include questioning consistency with causation as an explanatory principle, charging undue complexity, and questioning the need for it. Arguments in favor of incremental inference include better explanation of diverse causal inferences in behavioral science, tailored causal inference, and more detailed and explicit description of causal inference. Incremental causal inference offers a viable and potentially fruitful alternative to approaches limited to a single causal relation. (shrink)

A simple counterfactual theory of causation fails because of problems with cases of preemption. This might lead us to expect that preemption will raise problems for counterfactual theories of other concepts that have a causal dimension. Indeed, examples are easy to find. But there is one case where we do not find this. Several versions of causal decision theory are formulated using counterfactuals. This might lead us to expect that these theories will yield the wrong recommendations in cases of preemption. (...) But they do not. The explanation, I argue, is that the ‘cause’ that has been the target of counterfactual analyses is a specific relation, ‘actual causation’, that is not needed for prospective deliberation. A simple counterfactual theory of causation seems to capture the notion of cause needed for causal decision theory. This shows, in opposition to some critics, that counterfactual theories of causation are not barking up the wrong tree. (shrink)

In his article ‘Doing, allowing, and the problem of evil’ recently published in this journal, Daniel Lim attempts to undermine the following claims with respect to God: the doing-allowing distinction exists and the doing-allowing distinction is morally significant. I argue that Lim’s attempt is unsuccessful, and that his understanding of divine providence has the unacceptable consequence of implying that God is the originator of evil.

Psychosomatic medicine, with its prevailing biopsychosocial model, aims to integrate human and exact sciences with their divergent conceptual models. Therefore, its own conceptual foundations, which often remain implicit and unknown, may be critically relevant. We defend the thesis that choosing between different metaphysical views on the ‘mind–body problem’ may have important implications for the conceptual foundations of psychosomatic medicine, and therefore potentially also for its methods, scientific status and relationship with the scientific disciplines it aims to integrate: biomedical sciences, psychology (...) and social sciences. To make this point, we introduce three key positions in the philosophical ‘mind–body’ debate and investigate their consequences for the conceptual basis of the biopsychosocial model in general and its ‘psycho-biological’ part in particular. Despite the clinical merits of the biopsychosocial model, we submit that it is conceptually underdeveloped or even flawed, which may hamper its use as a proper scientific model. (shrink)

Thinking about illness causation has a long and rich history in medicine. After a hiatus in the 1990s, the last one-and-a-half decades have seen a surge of publications on causality in the biomedical sciences. Interestingly, this surge is visible not only in the medical, epidemiological, bioinformatics, and public health literatures, but also among philosophical publications. In this essay, I review and discuss one most recent addition to the literature, "Causality: Philosophical Theory Meets Scientific Practice" written by philosophers Phyllis Illari and (...) Federica Russo about causality in the sciences, and particularly about the health sciences. (shrink)

We start this paper by arguing that causality should, in analogy with force in Newtonian physics, be understood as a theoretical concept that is not explicated by a single definition, but by the axioms of a theory. Such an understanding of causality implicitly underlies the well-known theory of causal nets and has been explicitly promoted by Glymour. In this paper we investigate the explanatory warrant and empirical content of TCN. We sketch how the assumption of directed cause–effect relations can be (...) philosophically justified by an inference to the best explanation. We then ask whether the explanations provided by TCN are merely post-facto or have independently testable empirical content. To answer this question we develop a fine-grained axiomatization of TCN, including a distinction of different kinds of faithfulness. A number of theorems show that although the core axioms of TCN are empirically empty, extended versions of TCN have successively increasing empirical content. (shrink)

Woodward’s interventionist theory of causation is beset by a problem of circularity: the analysis of causes is in terms of interventions, and the analysis of interventions is in terms of causes. This is not in itself an argument against the correctness of the analysis. But by requiring us to have causal knowledge prior to making any judgements about causation, Woodward’s theory does make it mysterious how we can ever start acquiring causal knowledge. We present a solution to this problem by (...) showing how the interventionist notion of causation can be rationally generated from a more primitive agency notion of causation. The agency notion is easily and non-circularly applicable, but fails when we attempt to capture causal relations between non-actions. We show that the interventionist notion of causation serves as an appropriate generalisation of the agency notion. Furthermore, the causal judgements based on the latter generally remain true when rephrased in terms of the former, which allows one to use the causal knowledge gained by applying the agency notion as a basis for applying Woodward’s interventionist theory. We then present an overview of relevant empirical evidence from developmental psychology which shows that our proposed rational reconstruction lines up neatly with the actual development of causal reasoning in children. This gives additional plausibility to our proposal. The article thus provides a solution to one of the main problems of interventionism while keeping Woodward’s analysis intact. (shrink)

Stemming from the realization of the importance of the role of explanation in the science classroom, the Next Generation Science Standards call for appropriately supporting students to learn science, argue from evidence, and provide explanations. Despite the ongoing emphasis on explanations in the science classroom, there seems to be no well-articulated framework that supports students in constructing adequate scientific explanations, or that helps teachers assess student explanations. Our motivation for this article is twofold: First, we think that the ways in (...) which researchers in science education have studied scientific explanation are, at best, leaves much to be desired and, at worst, simply incomplete. Second, we believe that research about the teaching and learning of explanation in science classrooms must be guided by explicit models or frameworks that specify elements involved in constructing explanations particularly applicable to science. More importantly, we think that the development of such models or guidelines should be based on theoretical and philosophical foundations. In order to develop these frameworks or guidelines, we first outline and clarify models of scientific explanation developed by philosophers of science over the last few decades. In the second section of this article, we present a more recent philosophical work on scientific explanation, the pragmatic approach to studying scientific explanations. This approach suggests a toolbox for analyzing scientists’ scientific explanations, which provides a useful instrument to science education. In Section 3, we discuss the ways by which the previous two sections are useful in developing a K-12 scientific explanation schema. Implications for future research on students’ explanations are discussed. (shrink)

Jaegwon Kim famously challenged non-reductive materialism/physicalism, a popular stance in the philosophy of mind, with the so-called exclusion argument. The argument is alleged to show that if NRM is true, then mental properties cannot be causes. In recent years, there have been many reactions to the exclusion problem based on counterfactual accounts of causation. In particular, List and Menzies gave an interesting response based on a Lewis-style counterfactual theory of causation, with some modifications made to Lewis’s semantics of counterfactuals. In (...) this thesis, I first argue that their central thesis regarding the issue of exclusion can actually be established with Lewis’s original semantics, without modifications. I then clarify the real consequence of List and Menzies’ modification by showing that List and Menzies' modified counterfactual theory, but not Lewis’s original theory, can satisfy Zhong ’s requirement of causal autonomy. My analysis reveals that, despite Zhong ’s employment of an interventionist theory of causation, it is not any peculiarity with the interventionism that is essential for establishing the possibility of causal autonomy. On the contrary, I argue that the existing semantics for interventionist counterfactuals do not seem to serve Zhong’s purpose particularly well. These considerations suggest that once one decides to use a dependence notion of causation to counter the exclusion argument, a Lewis-style theory of causation is good enough. (shrink)

We have two main aims: to construct mathematical models for analysing determinism, causality and supervenience; and then to use these to demonstrate the possibility of constructing an ontic construal of the operation of free will - one requiring both the presentation of genuine alternatives to an agent and their selecting between them in a manner that permits the attribution of responsibility. Determinism is modelled using trans-temporal ontic links between discrete juxtaposed universe states and shown to be distinct from predictability. Causality (...) is defined on a temporal sequence of δ-algebras and quantified using a measure. The measure leads to definitions of causal overdetermination and epiphenomena. Proofs are constructed to demonstrate deterministic universes must carry their properties essentially but not necessarily locally. We argue determinism and causality are separate doctrines. These models and results are marshalled to put the case that a counterfactual construal of ontic choice cannot work. In response we propose ‘immanence’ - a modified form of indeterminism whereby a universe can present choices to its denizens. We prove that beings subsumed within a universe cannot pilot their own actions. We then argue these beings can exercise free will only when selecting between choices inhering within immanent relata. A being is responsible for its selections if and only if it is constituted of a temporally evolving deterministic substructure. Our proposal is novel: it avoids injecting indeterminism into the decision process. Topological models for property supervenience are developed and used to reconstruct standard definitions from the literature. These are then used to demonstrate considerations of supervenience do not affect our arguments. We have demonstrated that a model of the exercise of free will involving both genuine choices and responsibility is possible but can only operate within a non-deterministic universe possessing specific traits. (shrink)