One primary goal for metaphysical theories of natural kinds is to account for their epistemic fruitfulness. According to cluster theories of natural kinds, this epistemic fruitfulness is grounded in the regular and stable co- occurrence of a broad set of properties. In this paper, I defend the view that such a cluster theory is insufficient to adequately account for the epistemic fruitfulness of kinds. I argue that cluster theories can indeed account for the projectibility of natural kinds, but not for (...) several other epistemic operations that natural kinds support. Natural kinds also play a role in scientific explanations and categorizations. A theory of natural kinds can only account for these additional kind-based epistemic practices if it also analyzes their causal structure. (shrink)

Recently, a strong hylomorphic reading of Aristotelian emotions has been put forward, one that allegedly eliminates the problem of causal interaction between soul and body. Taking the presentation of emotions in de An. I 1 as a starting point and basic thread, but relying also on the discussion of Rh. II, I will argue that this reading only takes into account two of the four causes of emotions, and that, if all four of them are included into the picture, (...) then a causal interaction of mind and body remains within Aristotelian emotions, independent of how strongly their hylomorphism is understood. Beyond the discussion with this recent reading, the analysis proposed of the fourfold causal structure of emotions is also intended as a hermeneutical starting point for a comprehensive analysis of particular emotions in Aristotle. Through the different causes Aristotle seems to account for many aspects of the complex phenomenon of emotion, including its physiological causes, its mental causes, and its intentional object. (shrink)

This paper examines the idea that there might be natural kinds of causal processes, with characteristic diachronic structure, in much the same way that various chemical elements form natural kinds, with characteristic synchronic structure. This claim -- if compatible with empirical science -- has the potential to shed light on a metaphysics of essentially dispositional properties, championed by writers such as Bird and Ellis.

The results from a number of recent studies suggest that ascriptions of intentionality are based on evaluative considerations: specifically, that the likelihood of viewing a person’s actions as intentional is greater when the outcome is bad than good (see Knobe, 2006, 2010). In this research we provide an alternative explanation for these findings, one based on the idea that ascriptions of intentionality depend on causal structure. As predicted by the causal structure view, we observed that actions (...) leading to bad outcomes are associated with negative social pressures (Experiment 1), that these negative pressures give rise to a specific kind of causal structure (Experiment 2), and that when these causal structures are pitted against the badness of the outcome, intentionality judgments track with causal structure and not badness (Experiment 3). While the badness of an outcome may have an indirect effect on judgments of intentionality, our results suggest that the factors that affect judgments of intentionality most directly are non-evaluative and objective. (shrink)

According to mainstream philosophical views causal explanation in biology and neuroscience is mechanistic. As the term ‘mechanism’ gets regular use in these fields it is unsurprising that philosophers consider it important to scientific explanation. What is surprising is that they consider it the only causal term of importance. This paper provides an analysis of a new causal concept—it examines the cascade concept in science and the causal structure it refers to. I argue that this concept (...) is importantly different from the notion of mechanism and that this difference matters for our understanding of causation and explanation in science. (shrink)

1Department of Philosophy, University of Nottingham, University Park, Nottingham NG7 2RD, UK. [email protected] of Philosophy, University of Nottingham, University Park, Nottingham NG7 2RD, UK. [email protected].

This paper critically reviews and characterizes the student's causal-explanatory understanding; this is done as a step toward explicating the problematic of evolution education as it concerns the cognitive difficulties in understanding Darwin's theory of natural selection. The review concludes that the student's understanding is fundamentally different from Darwin's, for the student understands evolutionary change as necessary individual transformation caused by the transformative action of various physical and behavioral factors. This is in complete contrast to Darwin's (and even the Darwinian's, (...) for that matter) understanding of evolutionary change as a change caused by accumulative selection. Hence, to understand natural selection, the student has to learn to “see” how the accumulative selection causes evolutionary change. (shrink)

This paper introduces and defends a new principle for when a structural equation model is apt for analyzing actual causation. Any such analysis in terms of these models has two components: a recipe for reading claims of actual causation off an apt model, and an articulation of what makes a model apt. The primary focus in the literature has been on the first component. But the problem of structural isomorphs has made the second especially pressing (Hall 2007; Hitchcock 2007a). Those (...) with realist sympathies have reason to resist the standard response to this problem, which introduces a normative parameter into the metaphysics (Hall 2007; Halpern and Hitchcock 2010, 2015; Halpern 2016a; Menzies 2017; Gallow 2021). However, the only alternative solution in the literature leaves central questions unanswered (Blanchard and Schaffer 2017). I propose an independently motivated aptness requirement, Evident Mediation, that provides the missing details and resolves the structural isomorph problem without need for a normative parameter. (shrink)

Although Newton carefully eschews questions about gravity’s causal basis in the published Principia, the original version of his masterwork’s third book contains some intriguing causal language. “These forces,” he writes, “arise from the universal nature of matter.” Such remarks seem to assert knowledge of gravity’s cause, even that matter is capable of robust and distant action. Some commentators defend that interpretation of the text—a text whose proper interpretation is important since Newton’s reasons for suppressing it strongly suggest that (...) he continued to endorse its ideas. This article argues that the surface appearance of Newton’s causal language is deceptive. What does New- ton intend with his causal language if not a full causal hypothesis? His remarks actually indicate a way of considering the force mathematically, something he contrasts to the structure of the force as it really is in nature. In explaining that, he identifies a significant disjunction between the physical force itself and mathematical ways of considering it, and the text’s significance lies in its view of the force’s structure and in the questions raised about the relationship between mathematical representations and the physical world. (shrink)

There is traditionally a division of labor between economics and economic history, the task of economic history being that of studying the evolving constraints of economic mechanisms. Recent theorizing on endogenous structural change challenges this view: if structural change is endogenous to economic mechanisms, any strict division of labor between causal analysis and structural analysis breaks down. Rather such views call for an integration of causal and structural analysis. This paper looks for such a methodology, noting especially the (...) contributions made by two Swedish economists, Johan Åkerman (1896-1982) and Erik Dahmén (1916-2005). With evolutionary, Marxian, Hayekian and critical realist contributions, the paper examines notions of endogenous structural change with the aim of expounding how the notion can be thought in terms of underlying mechanisms to aid such structural analysis. The findings of endogenous mechanisms underlying structural change are crystallized into a mathematical model and a simple methodological framework. (shrink)

Social scientists appeal to various “structures” in their explanations including public policies, economic systems, and social hierarchies. Significant debate surrounds the explanatory relevance of these factors for various outcomes such as health, behavioral, and economic patterns. This paper provides a causal account of social structural explanation that is motivated by Haslanger (2016). This account suggests that social structure can be explanatory in virtue of operating as a causal constraint, which is a causal factor with unique characteristics. (...) A novel causal framework is provided for understanding these explanations–this framework addresses puzzles regarding the mysterious causal influence of social structure, how to understand its relation to individual choice, and what makes it the main explanatory (and causally responsible) factor for various outcomes. (shrink)

This paper examines the adequacy of causal graph theory as a tool for modeling biological phenomena and formalizing biological explanations. I point out that the causal graph approach reaches it limits when it comes to modeling biological phenomena that involve complex spatial and structural relations. Using a case study from molecular biology, DNA-binding and -recognition of proteins, I argue that causal graph models fail to adequately represent and explain causal phenomena in this field. The inadequacy of (...) these models is due to their failure to include relevant spatial and structural information in a way that does not render the model non-explanatory, unmanageable, or inconsistent with basic assumptions of causal graph theory. (shrink)

Different methodological approaches to empirical macroeconomics will be described and it will be explained that they represent different answers to the question from the title. Structural approaches require that macroeconometrical research should be explicitly founded on the (micro)economic theory in order to be able to measure the causal structure of the macroeconomic phenomena. Unstructural VAR approach suggest using econometric models to try to find out as much as possible about causal structure from the data, without prior (...) restrictions from the theory. Problems with both are described. (shrink)

I present three reasons why philosophers of science should be more concerned about violations of causal faithfulness (CF). In complex evolved systems, mechanisms for maintaining various equilibrium states are highly likely to violate CF. Even when such systems do not precisely violate CF, they may nevertheless generate precisely the same problems for inferring causal structure from probabilistic relationships in data as do genuine CF-violations. Thus, potential CF-violations are particularly germane to experimental science when we rely on probabilistic (...) information to uncover the DAG, rather than already knowing the DAG from which we could predict the right experiments to ‘catch out’ the hidden causal relationships. (shrink)

This paper brings together Thompson's naive action explanation with interventionist modeling of causal structure to show how they work together to produce causal models that go beyond current modeling capabilities, when applied to specifically selected systems. By deploying well-justified assumptions about rationalization, we can strengthen existing causal modeling techniques' inferential power in cases where we take ourselves to be modeling causal systems that also involve actions. The internal connection between means and end exhibited in naive (...) action explanation has a modal strength like that of distinctively mathematical explanation, rather than that of causal explanation. Because it is stronger than causation, it can be treated as if it were merely causal in a causal model without thereby overextending the justification it can provide for inferences. This chapter introduces and demonstrate the usage of the Rationalization condition in causal modeling, where it is apt for the system(s) being modeled, and to provide the basics for incorporating R variables into systems of variables and R arrows into DAGs. Use of the Rationalization condition supplements causal analysis with action analysis where it is apt. (shrink)

There is widespread belief in a tension between quantum theory and special relativity, motivated by the idea that quantum theory violates J. S. Bell’s criterion of local causality, which is meant to implement the causal structure of relativistic space-time. This paper argues that if one takes the essential intuitive idea behind local causality to be that probabilities in a locally causal theory depend only on what occurs in the backward light cone and if one regards objective probability (...) as what imposes constraints on rational credence along the lines of David Lewis’ Principal Principle, then one arrives at the view that whether or not Bell’s criterion holds is irrelevant for whether or not local causality holds. The assumptions on which this argument rests are highlighted, and those that may seem controversial are motivated. (shrink)

Causal models show promise as a foundation for the semantics of counterfactual sentences. However, current approaches face limitations compared to the alternative similarity theory: they only apply to a limited subset of counterfactuals and the connection to counterfactual logic is not straightforward. This paper addresses these difficulties using exogenous interventions, where causal interventions change the values of exogenous variables rather than structural equations. This model accommodates judgments about backtracking counterfactuals, extends to logically complex counterfactuals, and validates familiar principles (...) of counterfactual logic. This combines the interventionist intuitions of the causal approach with the logical advantages of the similarity approach. (shrink)

When agents violate norms, they are typically judged to be more of a cause of resulting outcomes. In this paper, we suggest that norm violations also affect the causality attributed to other agents, a phenomenon we refer to as "causal superseding." We propose and test a counterfactual reasoning model of this phenomenon in four experiments. Experiments 1 and 2 provide an initial demonstration of the causal superseding effect and distinguish it from previously studied effects. Experiment 3 shows that (...) this causal superseding effect is dependent on a particular event structure, following a prediction of our counterfactual model. Experiment 4 demonstrates that causal superseding can occur with violations of non-moral norms. We propose a model of the superseding effect based on the idea of counterfactual sufficiency. (shrink)

Analyses of factual causation face perennial problems, including preemption, overdetermination, and omissions. Arguably, the thorniest, are cases of omissive overdetermination, involving two independent omissions, each sufficient for the harm, and neither, independently, making a difference. A famous example is Saunders, where pedestrian was hit by a driver of a rental car who never pressed on the (unbeknownst to the driver) defective (and, negligently, never inspected) brakes. Causal intuitions in such cases are messy, reflected in disagreement about which omission mattered. (...) What these analyses mistakenly take for granted, is that at issue is the 'efficacy' of each omission. I argue, on the contrary, the puzzle of omissive overdetermination favors taking the act/omission distinction seriously. Factual causation, properly understood precludes omissions (i.e. omissions are not causal). Of course, the law also attaches liability to omissions, but this works differently from liability for real causes (e.g. omissions have a duty requirement, they also respond differentially to difference-making considerations). The manner in which liability attaches for omissions differs from that of straightforward causal liability, and is entirely dependent on the underlying causal structure. Attention to that structure (e.g. that the driver's hitting the pedestrian with his car is what actually caused the injury) sheds light on which omissions matter (e.g. driver's failure to press on the brakes) and why (because that failure removes a defense the driver would have to liability for the accident he caused). Other cases, where the parties' connection is entirely omissive (e.g. two physicians fail to detect independently lethal conditions), come out differently (tracking moralized elements). The analysis offered makes better sense of both why omissive determination cases are puzzling and how to resolve them. (shrink)

Causal selection is the cognitive process through which one or more elements in a complex causal structure are singled out as actual causes of a certain effect. In this paper, we report on an experiment in which we investigated the role of moral and temporal factors in causal selection. Our results are as follows. First, when presented with a temporal chain in which two human agents perform the same action one after the other, subjects tend to (...) judge the later agent to be the actual cause. Second, the impact of temporal location on causal selection is almost canceled out if the later agent did not violate a norm while the former did. We argue that this is due to the impact that judgments of norm violation have on causal selection—even if the violated norm has nothing to do with the obtaining effect. Third, moral judgments about the effect influence causal selection even in the case in which agents could not have foreseen the effect and did not intend to bring it about. We discuss our findings in connection to recent theories of the role of moral judgment in causal reasoning, on the one hand, and to probabilistic models of temporal location, on the other. (shrink)

Structural representations are increasingly popular in philosophy of cognitive science. A key virtue they seemingly boast is that of meeting Ramsey's job description challenge. For this reason, structural representations appear tailored to play a clear representational role within cognitive architectures. Here, however, I claim that structural representations do not meet the job description challenge. This is because even our most demanding account of their functional profile is satisfied by at least some receptors, which paradigmatically fail the job description challenge. Hence, (...) the functional profile typically associated with structural representations does not identify representational posits. After a brief introduction, I present, in the second section of the paper, the job description challenge. I clarify why receptors fail to meet it and highlight why, as a result, they should not be considered representations. In the third section I introduce what I take to be the most demanding account of structural representations at our disposal, namely Gładziejewski's account. Provided the necessary background, I turn from exposition to criticism. In the first half of the fourth section, I equate the functional profile of structural representations and receptors. To do so, I show that some receptors boast, as a matter of fact, all the functional features associated with structural representations. Since receptors function merely as causal mediators, I conclude structural representations are mere causal mediators too. In the second half of the fourth section I make this conclusion intuitive with a toy example. I then conclude the paper, anticipating some objections my argument invites. (shrink)

This paper provides a general introduction to the use of causal models in the metaphysics of causation, specifically structural equation models and directed acyclic graphs. It reviews the formal framework, lays out a method of interpretation capable of representing different underlying metaphysical relations, and describes the use of these models in analyzing causation.

In this paper I argue that Theodor W. Adorno 's philosophy of freedom needs an ontological picture of the world. Adorno does not make his view of natural order explicit, but I suggest it could be neither the chaotic nor the strictly determined ontological images common to idealism and positivism, and that it would have to make intelligible the possibility both of human freedom and of critical social science. I consider two possible candidates, Nancy Cartwright 's ‘patchwork of laws’, and (...) Roy Bhaskar 's critical realism. Arguing that Cartwright 's position conflicts with the spirit of Adorno 's philosophy, I suggest that Bhaskar 's realism is compatible with and to a significant extent implicit in Adorno 's position. Whilst Adorno is clearly not a critical realist, Bhaskar 's position does provide the best overall account of the ontological commitments of Adorno 's critical theory. It becomes possible in turn to locate Bhaskar 's arguments in a broader critical tradition and give fuller expression to the concerns that structure his work, in particular by locating the epistemic fallacy in the narrative account of the natural history of subjective reason and its tendency towards ‘identity thinking ’. The discussion goes on to consider the interdependence of reason, nature and freedom in the idea of emancipatory critique, confirming the deeper affinities between critical realism and critical theory. (shrink)

Causal reasoning and game-theoretic reasoning are fundamental topics in artificial intelligence, among many other disciplines: this paper is concerned with their intersection. Despite their importance, a formal framework that supports both these forms of reasoning has, until now, been lacking. We offer a solution in the form of (structural) causal games, which can be seen as extending Pearl's causal hierarchy to the game-theoretic domain, or as extending Koller and Milch's multi-agent influence diagrams to the causal domain. (...) We then consider three key questions: i) How can the (causal) dependencies in games - either between variables, or between strategies - be modelled in a uniform, principled manner? ii) How may causal queries be computed in causal games, and what assumptions does this require? iii) How do causal games compare to existing formalisms? To address question i), we introduce mechanised games, which encode dependencies between agents' decision rules and the distributions governing the game. In response to question ii), we present definitions of predictions, interventions, and counterfactuals, and discuss the assumptions required for each. Regarding question iii), we describe correspondences between causal games and other formalisms, and explain how causal games can be used to answer queries that other causal or game-theoretic models do not support. Finally, we highlight possible applications of causal games, aided by an extensive open-source Python library. (shrink)

It is widely held that whether a person is morally responsible for an outcome partly depends on whether certain causal relations obtain between that person and the outcome. This paper argues that, regardless of whether the preceding claim about moral responsibility is true, moral blameworthiness is independent of such causal considerations. This conclusion is motivated by considering cases from Carolina Sartorio and Sara Bernstein. The causal structures of these cases are complex. Sartorio and Bernstein believe that reaching (...) conclusions about moral responsibility and blameworthiness requires wading through this complexity. But it is argued here that getting clear on these causal structures does not help us assess blameworthiness (regardless of the relevance of such considerations for drawing conclusions about moral responsibility). Moral blameworthiness simply does not turn on the considerations relevant to figuring out whether an agent causally contributed to an outcome. (shrink)

In the last couple of years, a few seemingly independent debates on scientific explanation have emerged, with several key questions that take different forms in different areas. For example, the questions what makes an explanation distinctly mathematical and are there any non-causal explanations in sciences (i.e., explanations that don’t cite causes in the explanans) sometimes take a form of the question of what makes mathematical models explanatory, especially whether highly idealized models in science can be explanatory and in virtue (...) of what they are explanatory. These questions raise further issues about counterfactuals, modality, and explanatory asymmetries: i.e., do mathematical and non-causal explanations support counterfactuals, and how ought we to understand explanatory asymmetries in non-causal explanations? Even though these are very common issues in the philosophy of physics and mathematics, they can be found in different guises in the philosophy of biology where there is the statistical interpretation of the Modern Synthesis theory of evolution, according to which the post-Darwinian theory of natural selection explains evolutionary change by citing statistical properties of populations and not the causes of changes. These questions also arise in philosophy of ecology or neuroscience in regard to the nature of topological explanations. The question here is can the mathematical (or more precisely topological) properties in network models in biology, ecology, neuroscience, and computer science be explanatory of physical phenomena, or are they just different ways to represent causal structures. The aim of this special issue is to unify all these debates around several overlapping questions. These questions are: are there genuinely or distinctively mathematical and non-causal explanations?; are all distinctively mathematical explanations also non-causal; in virtue of what they are explanatory; does the instantiation, implementation, or in general, applicability of mathematical structures to a variety of phenomena and systems play any explanatory role? This special issue provides a platform for unifying the debates around several key issues and thus opens up avenues for better understanding of mathematical and non-causal explanations in general, but also, it will enable even better understanding of key issues within each of the debates. (shrink)

Aristotelian causal theories incorporate some philosophically important features of the concept of cause, including necessity and essential character. The proposed formalization is restricted to one-place predicates and a finite domain of attributes (without individuals). Semantics is based on a labeled tree structure, with truth defined by means of tree paths. A relatively simple causal prefixing mechanism is defined, by means of which causes of propositions and reasoning with causes are made explicit. The distinction of causal and (...) factual explanation are elaborated, and examples of cyclic and convergent causation are given. Soundness and completeness proofs are sketched. (shrink)

This paper derives from a broader project dealing with the notion of causal order. I use this term to signify two kinds of parts-whole dependence: Orderly systems have rich, decomposable, internal structure; specifically, parts play differential roles, and interactions are primarily local. Disorderly systems, in contrast, have a homogeneous internal structure, such that differences among parts and organizational features are less important. Orderliness, I suggest, marks one key difference between individuals and collectives. My focus here will be (...) the connection between order and robustness, i.e. functional resilience in the face of internal or environmental perturbations. I distinguish three varieties of robustness. Ordered robustness is grounded in the system’s specific organizational pattern. In contrast, disorderly robustness stems from the aggregate outcome of many similar parts. In between, we find semi-ordered robustness, wherein a messy ensemble of elements is subjected to a selection or stabilization mechanism. I give brief characterizations of each category, discuss examples and remark on the connection between the order/disorder axis and the notions of individual versus collective. (shrink)

There is good reason to believe that scientific realism requires a commitment to the objective modal structure of the physical world. Causality, equilibrium, laws of nature, and probability all feature prominently in scientific theory and explanation, and each one is a modal notion. If we are committed to the content of our best scientific theories, we must accept the modal nature of the physical world. But what does the scientific realist’s commitment to physical modality require? We consider whether scientific (...) realism is compatible with Humeanism about the laws of nature, and we conclude that it is not. We specifically identify three major problems for the best-systems account of lawhood: its central concept of strength cannot be formulated non-circularly, it cannot offer a satisfactory account of the laws of the special sciences, and it can offer no explanation of the success of inductive inference. In addition, Humeanism fails to be naturalistically motivated. For these reasons, we conclude that the scientific realist must embrace natural necessity. (shrink)

This article examines how specific realist and projectivist versions of manipulability theories of causation deal with the problem of objectivity. Does an agent-dependent concept of manipulability imply that conflicting causal claims made by agents with different capacities can come out as true? In defence of the projectivist stance taken by the agency view, I argue that if the agent’s perspective is shown to be uniform across different agents, then the truth-values of causal claims do not vary arbitrarily and, (...) thus, reach a satisfactory level of objectivity. My argument connects Price’s considerations on the situation of deliberation, whose structure, common to all agents, is the same with respect to both decision making and causal claims on a concept inspired by Douglas’s classification of objectivity of thought processes: the perspective of the detached agent. I further argue that, despite his agent-independent concept of intervention, Woodward’s claim of a stronger objectivity standard cannot be achieved, as the relativity of causal concepts to a variable set brings about the issue of the agent’s choice of variables. Consequently, a more permissive objectivity standard applies to both views. (shrink)

Although they are continually compositionally reconstituted and reconfigured, organisms nonetheless persist as ontologically unified beings over time – but in virtue of what? A common answer is: in virtue of their continued possession of the capacity for morphological invariance which persists through, and in spite of, their mereological alteration. While we acknowledge that organisms‟ capacity for the “stability of form” – homeostasis - is an important aspect of their diachronic unity, we argue that this capacity is derived from, and grounded (...) in a more primitive one – namely, the homeodynamic capacity for the “specified variation of form”. In introducing a novel type of causal power – a „structural power‟ – we claim that it is the persistence of their dynamic potential to produce a specified series of structurally adaptive morphologies which grounds organisms‟ privileged status as metaphysically “one over many” over time. (shrink)

While structural equations modeling is increasingly used in philosophical theorizing about causation, it remains unclear what it takes for a particular structural equations model to be correct. To the extent that this issue has been addressed, the consensus appears to be that it takes a certain family of causal counterfactuals being true. I argue that this account faces difficulties in securing the independent manipulability of the structural determination relations represented in a correct structural equations model. I then offer an (...) alternate understanding of structural determination, and I demonstrate that this theory guarantees that structural determination relations are independently manipulable. The account provides a straightforward way of understanding hypothetical interventions, as well as a criterion for distinguishing hypothetical changes in the values of variables which constitute interventions from those which do not. It additionally affords a semantics for causal counterfactual conditionals which is able to yield a clean solution to a problem case for the standard ‘closest possible world’ semantics. (shrink)

This article provides a conceptual account of causal understanding by connecting current psychological research on time and causality with philosophical debates on the causal asymmetry. I argue that causal relations are viewed as asymmetric because they are understood in temporal terms. I investigate evidence from causal learning and reasoning in both children and adults: causal perception, the temporal priority principle, and the use of temporal cues for causal inference. While this account does not suffice (...) for correct inferences of causal structure, I show it to serve as a preliminary understanding of causal concepts as asymmetric, that later incorporates other types of evidence. This approach supplies causal models with an asymmetric concept of causation that underlies hypotheses about causal structure, as I will illustrate from the framework of the knowledge-based causal induction model. I further argue for an integrating perspective, showing how the understanding of causes as preceding their effects underlies both psychological models and philosophical debates over time and the causal asymmetry, particularly regarding problem cases such as simultaneous causation or backwards causation, and the conceptual connection between causation and action. (shrink)

Recently, there has been an increased interest in employing model-based definitions of actual causation in legal inquiry. The formal precision of such approaches promises to be an improvement over more traditional approaches. Yet model-based approaches are viable only if suitable models of legal cases can be provided, and providing such models is sometimes difficult. I argue that causal-model-based definitions benefit legal inquiry in an indirect way. They make explicit the causal assumptions that need to be made plausible to (...) defend a particular claim of actual causation. My argument concerns the analysis of legal cases involving a combination of double prevention and causal redundancy. I show that discussions among legal theorists about such cases sometimes suffer from ambiguous assumptions about the causal structure. My account illustrates that causal models can act as a heuristic tool for clarifying such assumptions, and that causal models provide a framework for more accurate analyses of legal cases involving complex causal structure. (shrink)

Transcranial magnetic stimulation is used to make inferences about relationships between brain areas and their functions because, in contrast to neuroimaging tools, it modulates neuronal activity. The central aim of this article is to critically evaluate to what extent it is possible to draw causal inferences from repetitive TMS data. To that end, we describe the logical limitations of inferences based on rTMS experiments. The presented analysis suggests that rTMS alone does not provide the sort of premises that are (...) sufficient to warrant strong inferences about the direct causal properties of targeted brain structures. Overcoming these limitations demands a close look at the designs of rTMS studies, especially the methodological and theoretical conditions which are necessary for the functional decomposition of the relations between brain areas and cognitive functions. The main points of this article are that TMS-based inferences are limited in that stimulation-related causal effects are not equivalent to structure-related causal effects due to TMS side effects, the electric field distribution, and the sensitivity of neuroimaging and behavioral methods in detecting structure-related effects and disentangling them from confounds. Moreover, the postulated causal effects can be based on indirect effects. A few suggestions on how to manage some of these limitations are presented. We discuss the benefits of combining rTMS with neuroimaging in experimental reasoning and we address the restrictions and requirements of rTMS control conditions. The use of neuroimaging and control conditions allows stronger inferences to be gained, but the strength of the inferences that can be drawn depends on the individual experiment’s designs. Moreover, in some cases, TMS might not be an appropriate method of answering causality-related questions or the hypotheses have to account for the limitations of this technique. We hope this summary and formalization of the reasoning behind rTMS research can be of use not only for scientists and clinicians who intend to interpret rTMS results causally but also for philosophers interested in causal inferences based on brain stimulation research. (shrink)

Recent accounts of actual causation are stated in terms of extended causal models. These extended causal models contain two elements representing two seemingly distinct modalities. The first element are structural equations which represent the or mechanisms of the model, just as ordinary causal models do. The second element are ranking functions which represent normality or typicality. The aim of this paper is to show that these two modalities can be unified. I do so by formulating two constraints (...) under which extended causal models with their two modalities can be subsumed under so called which contain just one modality. These two constraints will be formally precise versions of Lewissystem of weights or priorities” governing overall similarity between possible worlds. (shrink)

Theorising the interplay of structure and agency is the quintessential focus of sociological endeavour. This paper aims to be part of that continuing endeavour, arguing for a stratified social ontology, where structure and agency are held to be irreducible to each other and causally efficacious, yet necessarily interdependent. It thus aims not to be part of that on-going journey in search of the 'ontological holy grail'. Instead, it offers a way of linking structure and agency which enables (...) the practical education researcher concretely to examine their relative interplay over time. The methodological key to teasing out their relative interplay is held to be analytical dualism. It will be argued that such a methodological device is precluded by Giddens' structuration theory. (shrink)

Feminist epistemology aims to propose epistemic reasons for increasing the representation of women or socially subordinated people in science. This is typically done—albeit often only implicitly—by positing a causal mechanism through which the representation of sociodemographic minorities exerts a positive effect on scientific advancement. Two types of causal theories can be identified. The “epistemic diversity thesis” presents a causal path from sociodemographic diversity to scientific progress mediated by epistemic diversity. The “thesis of epistemic advantage” proposes a (...) class='Hi'>causal path from social subjugation to capacity for inquiry. The latter theory is defined with substantial ambiguity in the existing literature, and I present an explicit causal reformulation that disambiguates it. The epistemic diversity thesis focuses on the effect of group composition on collective epistemic performance and is largely silent about what kind of characteristics lead to individual epistemic excellence. On the other hand, the thesis of epistemic advantage seeks to identify sociodemographic background conditions that make certain epistemic agents strictly better knowers or inquirers than others and pays little attention to the synergistic effects of diverse group composition. Such a difference in the causal structure reflects the diverging political characteristics of the two theories. (shrink)

In this article, after presenting the basic idea of causal accounts of implementation and the problems they are supposed to solve, I sketch the model of computation preferred by Chalmers and argue that it is too limited to do full justice to computational theories in cognitive science. I also argue that it does not suffice to replace Chalmers’ favorite model with a better abstract model of computation; it is necessary to acknowledge the causal structure of physical computers (...) that is not accommodated by the models used in computability theory. Additionally, an alternative mechanistic proposal is outlined. (shrink)

This paper is an introduction on the Causal Theory of Memory, one of the most discussed theories in philosophy of memory in the present days. We begin with Martin & Deutscher’s formulation of the theory, in which the authors present three criteria in order for a given mental state to be considered an instance of memory, amongst them, the famous causal criterion, which stipulates that a memory must be causally connected to the past experience. Subsequently, we discuss if (...) these criteria are necessary and sufficient for memory and we present two theories that complement these criteria with an epistemic and a phenomenological criterion, i.e., the Causal Epistemic Theory and the Causal Autonoetic Theory. We then introduce the concept of memory traces, which are, according to Martin & Deutscher, the causal link between the memory and the past experience which created this memory; we present the model of traces as structural analogues and the model of distributed traces and discuss the problems which arise for each of these models of traces. Afterwards we focus on the concept of causality and present the Causal Procedural Theory, which offers a different conception of causality that does not focus on the memory traces, but on causal process itself. Lastly, we present the theory called Discontinuism, a theory about the relation between memory and imagination, which follows directly from the Causal Theory of Memory. (shrink)

Contemporary action theory is generally concerned with giving theories of action ontology. In this paper, we make the novel proposal that the standard view in action theory—the Causal Theory of Action—should be recast as a “model”, akin to the models constructed and investigated by scientists. Such models often consist in fictional, hypothetical, or idealized structures, which are used to represent a target system indirectly via some resemblance relation. We argue that recasting the Causal Theory as a model can (...) not only accomplish the goals of causal theorists, but also give the theory greater flexibility in responding to common objections. (shrink)

Among the many causes of an event, how do we distinguish the important ones? Are there ways to distinguish among causes on principled grounds that integrate both practical aims and objective knowledge? Psychologist Tania Lombrozo has suggested that causal explanations “identify factors that are ‘exportable’ in the sense that they are likely to subserve future prediction and intervention” (Lombrozo 2010, 327). Hence portable causes are more important precisely because they provide objective information to prediction and intervention as practical aims. (...) However, I argue that this is only part of the epistemology of causal selection. Recent work on portable causes has implicitly assumed them to be portable within the same causal system at a later time. As a result, it has appeared that the objective content of causal selection includes only facts about the causal structure of that single system. In contrast, I present a case study from systems biology in which scientists are searching for causal factors that are portable across rather than within causal systems. By paying careful attention to how these biologists find portable causes, I show that the objective content of causal selection can extend beyond the immediate systems of interest. In particular, knowledge of the evolutionary history of gene networks is necessary for correctly identifying causal patterns in these networks that explain cellular behavior in a portable way. (shrink)

Diagnoses in medicine are often taken to serve as explanations of patients’ symptoms and signs. This article examines how they do so. I begin by arguing that although some instances of diagnostic explanation can be formulated as covering law arguments, they are explanatory neither in virtue of their argumentative structures nor in virtue of general regularities between diagnoses and clinical presentations. I then consider the theory that medical diagnoses explain symptoms and signs by identifying their actual causes in particular cases. (...) While I take this to be largely correct, I argue that for a diagnosis to function as a satisfactory causal explanation of a patient’s symptoms and signs, it also needs to be supplemented by understanding the mechanisms by which the identified cause produces the symptoms and signs. This mechanistic understanding comes not from the diagnosis itself, but rather from the theoretical framework within which the physician operates. (shrink)

The focus in the literature on scientific explanation has shifted in recent years towards model-based approaches. In recent work, Alisa Bokulich has argued that idealization has a central role to play in explanation. Bokulich claims that certain highly-idealized, structural models can be explanatory, even though they are not considered explanatory by causal, mechanistic, or covering law accounts of explanation. This paper focuses on Bokulich’s account in order to make the more general claim that there are problems with maintaining that (...) a structural criterion can capture the way that highly-idealized models explain. This paper examines Bokulich’s claim that the structural model explanation of quantum wavefunction scarring, featuring semiclassical mechanics, is deeper than the explanation provided by the local quantum model. The challenge for Bokulich is to show that the semiclassical model answers a wider range of w-questions, as this is her method of assessing structural information. I look at two reasonable approaches employing w-questions, and I argue that neither approach is ultimately satisfactory. Because structural similarity has preferences for more fundamental models, I argue that the local quantum model provides explanations that at least as deep as the semiclassical ones. The criterion either wrongly identifies all models as explanatory, or prefers models from fundamental theory. Either way, it cannot capture the way that highly-idealized models explain. (shrink)

Ontologies are some of the most central constructs in today's large plethora of knowledge technologies, namely in the context of the semantic web. As their coinage indicates, they are direct heirs to the ontological investigations in the long Western philosophical tradition, but it is not easy to make bridges between them. Contemporary ontological commitments often take causality as a central aspect for the ur-segregation of entities, especially in scientific upper ontologies; theories of causality and philosophical ontological investigations often go hand-in-hand, (...) and were essentially inseparable in medieval thought. This constitutes the foundation for a bridge, and this article analyzes the causality-based ontology of the late medieval philosopher Dietrich of Freiberg from the viewpoint of today's upper-ontology engineering. In this bridging attempt, it offers a translation into English of the first part of Dietrich's De origine (abbreviated title) that is a compromise between traditional scholarly translations of medieval Latin philosophical texts and contemporary ontology. (shrink)

Philippe Huneman has recently questioned the widespread application of mechanistic models of scientific explanation based on the existence of structural explanations, i.e. explanations that account for the phenomenon to be explained in virtue of the mathematical properties of the system where the phenomenon obtains, rather than in terms of the mechanisms that causally produce the phenomenon. Structural explanations are very diverse, including cases like explanations in terms of bowtie structures, in terms of the topological properties of the system, or in (...) terms of equilibrium. The role of mathematics in bowtie structured systems and in topologically constrained systems has recently been examined in different papers. However, the specific role that mathematical properties play in equilibrium explanations requires further examination, as different authors defend different interpretations, some of them closer to the new-mechanistic approach than to the structural model advocated by Huneman. In this paper, we cover this gap by investigating the explanatory role that mathematics play in Blaser and Kirschner’s nested equilibrium model of the stability of persistent long-term human-microbe associations. We argue that their model is explanatory because: i) it provides a mathematical structure in the form of a set of differential equations that together satisfy an ESS; ii) that the nested nature of the ESSs makes the explanation of host-microbe persistent associations robust to any perturbation; iii) that this is so because the properties of the ESS directly mirror the properties of the biological system in a non-causal way. The combination of these three theses make equilibrium explanations look more similar to structural explanations than to causal-mechanistic explanation. (shrink)

Several authors have used the notion of causal specificity in order to defend non-parity about genetic causes (Waters 2007, Woodward 2010, Weber 2017, forthcoming). Non-parity in this context is the idea that DNA and some other biomolecules that are often described as information-bearers by biologists play a unique role in life processes, an idea that has been challenged by Developmental Systems Theory (e.g., Oyama 2000). Indeed, it has proven to be quite difficult to state clearly what the alleged special (...) role of genetic causes consists in. In this paper, I show that the set of biomolecules that are normally considered to be information-bearers (DNA, mRNA) can be shown to be the most specific causes of protein primary structure, provided that causal specificity is measured over a relevant space of biological possibilities, disregarding physical as well as logically possible states of the causal variables. (shrink)

Whitehead’s cosmology centers on the self-creation of actual occasions that perish as they come to be, but somehow do combine to constitute societies that are persistent agents and/or patients. “Instance Ontology” developed by D.W. Mertz concerns unification of relata into facts of relatedness by specific intensions. These two conceptual systems are similar in that they both avoid the substance-property distinction: they differ in their understanding of how basic units combine to constitute complex unities. “Process Structural Realism” (PSR) draws from both (...) of these approaches in developing an account of how combinations of processes may produce ontologically significant coherences. When a group of processes achieves such closure that a set of states recurs continually, the effects of that coherence differ from what would occur in the absence of that closure. Such altered effectiveness is an attribute of the system as a whole, and would have consequences. This indicates that the network of processes, as a unit, has ontological significance. The closed network of processes, together with the conditions that prevail, constitute the form of definiteness of the coherence. That form continues to obtain as long as the coherence persists. Constituents contribute to, rather than share, that characteristic. Aspects of some recent research in systems biology, microeconomics, and social psychology illustrate the application of PSR. (shrink)