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  1. Perspectival objectivity.Peter W. Evans - 2020 - European Journal for Philosophy of Science 10 (2):1-21.
    Building on self-professed perspectival approaches to both scientific knowledge and causation, I explore the potentially radical suggestion that perspectivalism can be extended to account for a type of objectivity in science. Motivated by recent claims from quantum foundations that quantum mechanics must admit the possibility of observer-dependent facts, I develop the notion of ‘perspectival objectivity’, and suggest that an easier pill to swallow, philosophically speaking, than observer-dependency is perspective-dependency, allowing for a notion of observer-independence indexed to an agent perspective. Working (...)
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  • What’s so special about initial conditions? Understanding the past hypothesis in directionless time.Matt Farr - forthcoming - In Yemima Ben-Menahem (ed.), Rethinking Laws of Nature. Springer.
    It is often said that the world is explained by laws of nature together with initial conditions. But does that mean initial conditions don’t require further explanation? And does the explanatory role played by initial conditions entail or require that time has a preferred direction? This chapter looks at the use of the ‘initialness defence’ in physics, the idea that initial conditions are intrinsically special in that they don’t require further explanation, unlike the state of the world at other times. (...)
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  • Robustness and Modularity.Trey Boone - forthcoming - British Journal for the Philosophy of Science.
    Functional robustness refers to a system’s ability to maintain a function in the face of perturbations to the causal structures that support performance of that function. Modularity, a crucial element of standard methods of causal inference and difference-making accounts of causation, refers to the independent manipulability of causal relationships within a system. Functional robustness appears to be at odds with modularity. If a function is maintained despite manipulation of some causal structure that supports that function, then the relationship between that (...)
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  • Why adoption of causal modeling methods requires some metaphysics.Holly Andersen - 2023 - In Federica Russo (ed.), Routledge Handbook of Causality and Causal Methods,. Routledge.
    I highlight a metaphysical concern that stands in the way of more widespread adoption of causal modeling techniques such as causal Bayes nets. Researchers in some fields may resist adoption due to concerns that they don't 'really' understand what they are saying about a system when they apply such techniques. Students in these fields are repeated exhorted to be cautious about application of statistical techniques to their data without a clear understanding of the conditions required for those techniques to yield (...)
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  • Causal Markov, robustness and the quantum correlations.Mauricio Suárez & Iñaki San Pedro - 2010 - In Probabilities, Causes and Propensities in Physics. New York: Springer. pp. 173–193.
    It is still a matter of controversy whether the Principle of the Common Cause (PCC) can be used as a basis for sound causal inference. It is thus to be expected that its application to quantum mechanics should be a correspondingly controversial issue. Indeed the early 90’s saw a flurry of papers addressing just this issue in connection with the EPR correlations. Yet, that debate does not seem to have caught up with the most recent literature on causal inference generally, (...)
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  • Interdefining causation and intervention.Michael Baumgartner - 2009 - Dialectica 63 (2):175-194.
    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 (...)
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  • Interdefining Causation and Intervention.Michael Baumgartner - 2009 - Dialectica 63 (2):175-194.
    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 (...)
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  • The three faces of faithfulness.Jiji Zhang & Peter Spirtes - 2016 - Synthese 193 (4):1011-1027.
    In the causal inference framework of Spirtes, Glymour, and Scheines, inferences about causal relationships are made from samples from probability distributions and a number of assumptions relating causal relations to probability distributions. The most controversial of these assumptions is the Causal Faithfulness Assumption, which roughly states that if a conditional independence statement is true of a probability distribution generated by a causal structure, it is entailed by the causal structure and not just for particular parameter values. In this paper we (...)
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  • On the completeness of orientation rules for causal discovery in the presence of latent confounders and selection bias.Jiji Zhang - 2008 - Artificial Intelligence 172 (16-17):1873-1896.
    Causal discovery becomes especially challenging when the possibility of latent confounding and/or selection bias is not assumed away. For this task, ancestral graph models are particularly useful in that they can represent the presence of latent confounding and selection effect, without explicitly invoking unobserved variables. Based on the machinery of ancestral graphs, there is a provably sound causal discovery algorithm, known as the FCI algorithm, that allows the possibility of latent confounders and selection bias. However, the orientation rules used in (...)
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  • Error probabilities for inference of causal directions.Jiji Zhang - 2008 - Synthese 163 (3):409 - 418.
    A main message from the causal modelling literature in the last several decades is that under some plausible assumptions, there can be statistically consistent procedures for inferring (features of) the causal structure of a set of random variables from observational data. But whether we can control the error probabilities with a finite sample size depends on the kind of consistency the procedures can achieve. It has been shown that in general, under the standard causal Markov and Faithfulness assumptions, the procedures (...)
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  • Detection of unfaithfulness and robust causal inference.Jiji Zhang & Peter Spirtes - 2008 - Minds and Machines 18 (2):239-271.
    Much of the recent work on the epistemology of causation has centered on two assumptions, known as the Causal Markov Condition and the Causal Faithfulness Condition. Philosophical discussions of the latter condition have exhibited situations in which it is likely to fail. This paper studies the Causal Faithfulness Condition as a conjunction of weaker conditions. We show that some of the weaker conjuncts can be empirically tested, and hence do not have to be assumed a priori. Our results lead to (...)
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  • The Underdeterministic Framework.Tomasz Wysocki - forthcoming - British Journal for the Philosophy of Science.
    Philosophy and statistics have studied two causal species, deterministic and probabilistic. There's a third species, however, hitherto unanalysed: underdeterministic causal phenomena, which are non-deterministic yet non-probabilistic. Here, I formulate a framework for modelling them. -/- Consider a simple case. If I go out, I may stumble into you but also may miss you. If I don’t go out, we won't meet. I go out. We meet. My going out is a cause of our encounter even if there was no determinate (...)
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  • Explanatory generalizations, part I: A counterfactual account.James Woodward & Christopher Hitchcock - 2003 - Noûs 37 (1):1–24.
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  • Explanation and invariance in the special sciences.James Woodward - 2000 - British Journal for the Philosophy of Science 51 (2):197-254.
    This paper describes an alternative to the common view that explanation in the special sciences involves subsumption under laws. According to this alternative, whether or not a generalization can be used to explain has to do with whether it is invariant rather than with whether it is lawful. A generalization is invariant if it is stable or robust in the sense that it would continue to hold under a relevant if it is stable or robust in the sense that it (...)
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  • Critical notice: Causality by Judea Pearl.James Woodward - 2003 - Economics and Philosophy 19 (2):321-340.
    This is a wonderful book; indeed, it is easily one of the most important and creative books I have ever read on the subject of causation and causal inference. Causality is impressive on many levels and should be of great interest to many different audiences. Philosophers will find of particular interest Pearl's defense of what might be described as a broadly manipulationist or interventionist treatment of causation: Causal claims have to do with what would happen under ideal, suitably surgical experimental (...)
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  • Causation in biology: Stability, specificity, and the choice of levels of explanation.James Woodward - 2010 - Biology and Philosophy 25 (3):287-318.
    This paper attempts to elucidate three characteristics of causal relationships that are important in biological contexts. Stability has to do with whether a causal relationship continues to hold under changes in background conditions. Proportionality has to do with whether changes in the state of the cause “line up” in the right way with changes in the state of the effect and with whether the cause and effect are characterized in a way that contains irrelevant detail. Specificity is connected both to (...)
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  • Counterfactuals and causal explanation.James Woodward - 2002 - International Studies in the Philosophy of Science 18 (1):41 – 72.
    This article defends the use of interventionist counterfactuals to elucidate causal and explanatory claims against criticisms advanced by James Bogen and Peter Machamer. Against Bogen, I argue that counterfactual claims concerning what would happen under interventions are meaningful and have determinate truth values, even in a deterministic world. I also argue, against both Machamer and Bogen, that we need to appeal to counterfactuals to capture the notions like causal relevance and causal mechanism. Contrary to what both authors suppose, counterfactuals are (...)
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  • The fate of causal structure under time reversal.Porter Williams - 2022 - Theoria. An International Journal for Theory, History and Foundations of Science 37 (1):87-102.
    What happens to the causal structure of a world when time is reversed? At first glance it seems there are two possible answers: the causal relations are reversed, or they are not. I argue that neither of these answers is correct: we should either deny that time-reversed worlds have causal relations at all, or deny that causal concepts developed in the actual world are reliable guides to the causal structure of time-reversed worlds. The first option is motivated by the instability (...)
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  • Common causes and the direction of causation.Brad Weslake - 2005 - Minds and Machines 16 (3):239-257.
    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 (...)
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  • Intervening and Letting Go: On the Adequacy of Equilibrium Causal Models.Naftali Weinberger - 2021 - Erkenntnis 88 (6):1-25.
    Causal representations are distinguished from non-causal ones by their ability to predict the results of interventions. This widely-accepted view suggests the following adequacy condition for causal models: a causal model is adequate only if it does not contain variables regarding which it makes systematically false predictions about the results of interventions. Here I argue that this condition should be rejected. For a class of equilibrium systems, there will be two incompatible causal models depending on whether one intervenes upon a certain (...)
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  • Intervening and Letting Go: On the Adequacy of Equilibrium Causal Models.Naftali Weinberger - 2021 - Erkenntnis 88 (6):2467-2491.
    Causal representations are distinguished from non-causal ones by their ability to predict the results of interventions. This widely-accepted view suggests the following adequacy condition for causal models: a causal model is adequate only if it does not contain variables regarding which it makes systematically false predictions about the results of interventions. Here I argue that this condition should be rejected. For a class of equilibrium systems, there will be two incompatible causal models depending on whether one intervenes upon a certain (...)
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  • The social epidemiologic concept of fundamental cause.Andrew Ward - 2007 - Theoretical Medicine and Bioethics 28 (6):465-485.
    The goal of research in social epidemiology is not simply conceptual clarification or theoretical understanding, but more importantly it is to contribute to, and enhance the health of populations (and so, too, the people who constitute those populations). Undoubtedly, understanding how various individual risk factors such as smoking and obesity affect the health of people does contribute to this goal. However, what is distinctive of much on-going work in social epidemiology is the view that analyses making use of individual-level variables (...)
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  • Reduction Without Elimination: Mental Disorders as Causally Efficacious Properties.Gottfried Vosgerau & Patrice Soom - 2018 - Minds and Machines 28 (2):311-330.
    We argue that any account of mental disorders that meets the desideratum of assigning causal efficacy to mental disorders faces the so-called “causal exclusion problem”. We argue that fully reductive accounts solve this problem but run into the problem of multiple realizability. Recently advocated symptom-network approaches avoid the problem of multiple realizability, but they also run into the causal exclusion problem. Based on a critical analysis of these accounts, we will present our own account according to which mental disorders are (...)
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  • Great apes and children infer causal relations from patterns of variation and covariation.Christoph J. Völter, Inés Sentís & Josep Call - 2016 - Cognition 155 (C):30-43.
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  • Preface.Raphael van Riel & Albert Newen - 2011 - Philosophia Naturalis 48 (1):5-8.
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  • Interventions and Causality in Quantum Mechanics.Mauricio Suárez - 2013 - Erkenntnis 78 (2):199-213.
    I argue that the Causal Markov Condition (CMC) is in principle applicable to the Einstein–Podolsky–Rosen (EPR) correlations. This is in line with my defence in the past of the applicability of the Principle of Common Cause to quantum mechanics. I first review a contrary claim by Dan Hausman and Jim Woodward, who endeavour to preserve the CMC against a possible counterexample by asserting that the conditions for the application of the CMC are not met in the EPR experiment. In their (...)
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  • Review of Hunting Causes and Using Them: Approaches in Philosophy and Economics. [REVIEW]Daniel Steel - 2010 - Economics and Philosophy 26 (1):77-86.
  • Methodological individualism, explanation, and invariance.Daniel Steel - 2006 - Philosophy of the Social Sciences 36 (4):440-463.
    This article examines methodological individualism in terms of the theory that invariance under intervention is the signal feature of generalizations that serve as a basis for causal explanation. This theory supports the holist contention that macro-level generalizations can explain, but it also suggests a defense of methodological individualism on the grounds that greater range of invariance under intervention entails deeper explanation. Although this individualist position is not threatened by multiple-realizability, an argument for it based on rational choice theory is called (...)
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  • Interventionist decision theory.Reuben Stern - 2017 - Synthese 194 (10):4133-4153.
    Jim Joyce has argued that David Lewis’s formulation of causal decision theory is inadequate because it fails to apply to the “small world” decisions that people face in real life. Meanwhile, several authors have argued that causal decision theory should be developed such that it integrates the interventionist approach to causal modeling because of the expressive power afforded by the language of causal models, but, as of now, there has been little work towards this end. In this paper, I propose (...)
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  • Indeterminism and the causal Markov condition.Daniel Steel - 2005 - British Journal for the Philosophy of Science 56 (1):3-26.
    The causal Markov condition (CMC) plays an important role in much recent work on the problem of causal inference from statistical data. It is commonly thought that the CMC is a more problematic assumption for genuinely indeterministic systems than for deterministic ones. In this essay, I critically examine this proposition. I show how the usual motivation for the CMC—that it is true of any acyclic, deterministic causal system in which the exogenous variables are independent—can be extended to the indeterministic case. (...)
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  • Decision and Intervention.Reuben Stern - 2019 - Erkenntnis 84 (4):783-804.
    Meek and Glymour use the graphical approach to causal modeling to argue that one and the same norm of rational choice can be used to deliver both causal-decision-theoretic verdicts and evidential-decision-theoretic verdicts. Specifically, they argue that if an agent maximizes conditional expected utility, then the agent will follow the causal decision theorist’s advice when she represents herself as intervening, and will follow the evidential decision theorist’s advice when she represents herself as not intervening. Since Meek and Glymour take no stand (...)
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  • Comment on Hausman & Woodward on the causal Markov condition.Daniel Steel - 2006 - British Journal for the Philosophy of Science 57 (1):219-231.
    Woodward present an argument for the Causal Markov Condition (CMC) on the basis of a principle they dub ‘modularity’ ([1999, 2004]). I show that the conclusion of their argument is not in fact the CMC but a substantially weaker proposition. In addition, I show that their argument is invalid and trace this invalidity to two features of modularity, namely, that it is stated in terms of pairwise independence and ‘arrow-breaking’ interventions. Hausman & Woodward's argument can be rendered valid through a (...)
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  • Causal concepts and temporal ordering.Reuben Stern - 2019 - Synthese 198 (Suppl 27):6505-6527.
    Though common sense says that causes must temporally precede their effects, the hugely influential interventionist account of causation makes no reference to temporal precedence. Does common sense lead us astray? In this paper, I evaluate the power of the commonsense assumption from within the interventionist approach to causal modeling. I first argue that if causes temporally precede their effects, then one need not consider the outcomes of interventions in order to infer causal relevance, and that one can instead use temporal (...)
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  • Intervention, determinism, and the causal minimality condition.Peter Spirtes - 2011 - Synthese 182 (3):335-347.
    We clarify the status of the so-called causal minimality condition in the theory of causal Bayesian networks, which has received much attention in the recent literature on the epistemology of causation. In doing so, we argue that the condition is well motivated in the interventionist (or manipulability) account of causation, assuming the causal Markov condition which is essential to the semantics of causal Bayesian networks. Our argument has two parts. First, we show that the causal minimality condition, rather than an (...)
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  • Mechanisms, determination and the metaphysics of neuroscience.Patrice Soom - 2012 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 43 (3):655-664.
  • Mechanisms, determination and the metaphysics of neuroscience.Patrice Soom - 2012 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 43 (3):655-664.
    In this paper, I evaluate recently defended mechanistic accounts of the unity of neuroscience from a metaphysical point of view. Considering the mechanistic framework in general , I argue that explanations of this kind are essentially reductive . The reductive character of mechanistic explanations provides a sufficiency criterion, according to which the mechanism underlying a certain phenomenon is sufficient for the latter. Thus, the concept of supervenience can be used in order to describe the relation between mechanisms and phenomena . (...)
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  • A Priori Causal Models of Natural Selection.Elliott Sober - 2011 - Australasian Journal of Philosophy 89 (4):571 - 589.
    To evaluate Hume's thesis that causal claims are always empirical, I consider three kinds of causal statement: ?e1 caused e2 ?, ?e1 promoted e2 ?, and ?e1 would promote e2 ?. Restricting my attention to cases in which ?e1 occurred? and ?e2 occurred? are both empirical, I argue that Hume was right about the first two, but wrong about the third. Standard causal models of natural selection that have this third form are a priori mathematical truths. Some are obvious, others (...)
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  • Quantum causal explanation: or, why birds fly south.Sally Shrapnel - 2014 - European Journal for Philosophy of Science 4 (3):409-423.
    It is widely held that it is difficult, if not impossible, to apply causal theory to the domain of quantum mechanics. However, there are several recent scientific explanations that appeal crucially to quantum processes, and which are most naturally construed as causal explanations. They come from two relatively new fields: quantum biology and quantum technology. We focus on two examples, the explanation for the optical interferometer LIGO and the explanation for the avian magneto-compass. We analyse the explanation for the avian (...)
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  • Interactive Causes: Revising the Markov Condition.Gerhard Schurz - 2017 - Philosophy of Science 84 (3):456-479.
    This article suggests a revision of the theory of causal nets. In section 1 we introduce an axiomatization of TCN based on a realistic understanding. It is shown that the causal Markov condition entails three independent principles. In section 2 we analyze indeterministic decay as the major counterexample to one of these principles: screening off by common causes. We call SCC-violating common causes interactive causes. In section 3 we develop a revised version of TCN, called TCN*, which accounts for interactive (...)
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  • Bi-directionality and time in causal relationships.Fernanda Samaniego - 2022 - Theoria. An International Journal for Theory, History and Foundations of Science 37 (1).
    This paper aims to provide an answer to James Woodward’s article “Flagpoles anyone? Causal and explanatory asymmetries”. It will be conjectured that, when causal directionality depends on the experimental design, it is because the variables involved are capable of producing changes in each other. This will be exemplified using the case of ideal gases as opposed to the flagpole-shadow scenario.
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  • A new proposal how to handle counterexamples to Markov causation à la Cartwright, or: fixing the chemical factory.Nina Retzlaff & Alexander Gebharter - 2020 - Synthese 197 (4):1467-1486.
    Cartwright (Synthese 121(1/2):3–27, 1999a; The dappled world, Cambridge University Press, Cambridge, 1999b) attacked the view that causal relations conform to the Markov condition by providing a counterexample in which a common cause does not screen off its effects: the prominent chemical factory. In this paper we suggest a new way to handle counterexamples to Markov causation such as the chemical factory. We argue that Cartwright’s as well as similar scenarios feature a certain kind of non-causal dependence that kicks in once (...)
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  • Causal and Mechanistic Explanations in Ecology.Jani Raerinne - 2010 - Acta Biotheoretica 59 (3):251-271.
    How are scientific explanations possible in ecology, given that there do not appear to be many—if any—ecological laws? To answer this question, I present and defend an account of scientific causal explanation in which ecological generalizations are explanatory if they are invariant rather than lawlike. An invariant generalization continues to hold or be valid under a special change—called an intervention—that changes the value of its variables. According to this account, causes are difference-makers that can be intervened upon to manipulate or (...)
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  • Explanation and Manipulation.Alexander Prescott-Couch - 2017 - Noûs 51 (3):484-520.
    I argue that manipulationist theories of causation fail as accounts of causal structure, and thereby as theories of “actual causation” and causal explanation. I focus on two kinds of problem cases, which I call “Perceived Abnormality Cases” and “Ontological Dependence Cases.” The cases illustrate that basic facts about social systems—that individuals are sensitive to perceived abnormal conditions and that certain actions metaphysically depend on institutional rules—pose a challenge for manipulationist theories and for counterfactual theories more generally. I then show how (...)
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  • Does the Interventionist Notion of Causation Deliver Us from the Fear of Epiphenomenalism?Tuomas K. Pernu - 2013 - International Studies in the Philosophy of Science 27 (2):157-172.
    This article reviews the causal exclusion argument and confronts it with some recently proposed refutations based on the interventionist account of causation. I first show that there are several technical and interpretative difficulties in applying the interventionist account to the exclusion issue. Different ways of accommodating the two to one another are considered and all are shown to leave the issue without a fully satisfactory resolution. Lastly, I argue that, on the most consistent construal, the interventionist approach can provide grounds (...)
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  • Experiment, Downward Causation, and Interventionist Levels of Explanation.Veli-Pekka Parkkinen - 2016 - International Studies in the Philosophy of Science 30 (3):245-261.
    This article considers interventionist arguments for downward causation and non-fundamental level causal explanation from the point of view of inferring causation from experiments. Several authors have utilised the interventionist theory of causal explanation to argue that the causal exclusion argument is moot and that higher-level as well as downward causation is real. I show that this argument can be made when levels are understood as levels of grain, leaving us with a choice between causal explanations pitched at different levels. Causal (...)
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  • The Statistical Nature of Causation.David Papineau - 2022 - The Monist 105 (2):247-275.
    Causation is a macroscopic phenomenon. The temporal asymmetry displayed by causation must somehow emerge along with other asymmetric macroscopic phenomena like entropy increase and the arrow of radiation. I shall approach this issue by considering ‘causal inference’ techniques that allow causal relations to be inferred from sets of observed correlations. I shall show that these techniques are best explained by a reduction of causation to structures of equations with probabilistically independent exogenous terms. This exogenous probabilistic independence imposes a recursive order (...)
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  • Evidence for interactive common causes. Resuming the Cartwright-Hausman-Woodward debate.Paul M. Näger - 2021 - European Journal for Philosophy of Science 12 (1):Article number: 2 (pages: 1-33).
    The most serious candidates for common causes that fail to screen off and thus violate the causal Markov condition refer to quantum phenomena. In her seminal debate with Hausman and Woodward, Cartwright early on focussed on unfortunate non-quantum examples. Especially, Hausman and Woodward’s redescriptions of quantum cases saving the CMC remain unchallenged. This paper takes up this lose end of the discussion and aims to resolve the debate in favour of Cartwright’s position. It systematically considers redescriptions of ICC structures, including (...)
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  • Econometric methods and Reichenbach’s principle.Seán Mfundza Muller - 2022 - Synthese 200 (3):1-21.
    Reichenbach’s ‘principle of the common cause’ is a foundational assumption of some important recent contributions to quantitative social science methodology but no similar principle appears in econometrics. Angrist et al. has argued that the principle is necessary for instrumental variables methods in econometrics, and Angrist Krueger builds a framework using it that he proposes as a means of resolving an important methodological dispute among econometricians. Through analysis of instrumental variables methods and the issue of multicollinearity, we aim to show that (...)
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  • Some Criticism of the Contextual Approach, and a Few Proposals.Brian McLoone - 2015 - Biological Theory 10 (2):116-124.
    The contextual approach is a prominent framework for thinking about group selection. Here, I highlight ambiguity about what the contextual approach is. Then, I discuss problematic entailments the contextual approach has for what processes count as group selection—entailments more troublesome than typically noted. However, Sober and Wilson’s version of the Price approach, which is the main alternative to the contextual approach, is problematic too: it leads to an underappreciated paradox called the vanishing selection problem and thereby generates the wrong qualitative (...)
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  • Agents and Causes: Dispositional Intuitions As a Guide to Causal Structure.Ralf Mayrhofer & Michael R. Waldmann - 2015 - Cognitive Science 39 (1):65-95.
    Currently, two frameworks of causal reasoning compete: Whereas dependency theories focus on dependencies between causes and effects, dispositional theories model causation as an interaction between agents and patients endowed with intrinsic dispositions. One important finding providing a bridge between these two frameworks is that failures of causes to generate their effects tend to be differentially attributed to agents and patients regardless of their location on either the cause or the effect side. To model different types of error attribution, we augmented (...)
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