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  1. Philosophy inside out.Philip Kitcher - 2011 - Metaphilosophy 42 (3):248-260.
    Abstract: Philosophy is often conceived in the Anglophone world today as a subject that focuses on questions in particular “core areas,” pre-eminently epistemology and metaphysics. This article argues that the contemporary conception is a new version of the scholastic “self-indulgence for the few” of which Dewey complained nearly a century ago. Philosophical questions evolve, and a first task for philosophers is to address issues that arise for their own times. The article suggests that a renewal of philosophy today should turn (...)
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  • Lewis Causation is a Special Case of Spohn Causation.Franz Huber - 2011 - British Journal for the Philosophy of Science 62 (1):207-210.
    This paper shows that causation in the sense of Lewis is a special case of causation in the sense of Spohn.
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  • A Probabilistic Analysis of Causation.Luke Glynn - 2011 - British Journal for the Philosophy of Science 62 (2):343-392.
    The starting point in the development of probabilistic analyses of token causation has usually been the naïve intuition that, in some relevant sense, a cause raises the probability of its effect. But there are well-known examples both of non-probability-raising causation and of probability-raising non-causation. Sophisticated extant probabilistic analyses treat many such cases correctly, but only at the cost of excluding the possibilities of direct non-probability-raising causation, failures of causal transitivity, action-at-a-distance, prevention, and causation by absence and omission. I show that (...)
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  • (1 other version)Probabilistic models of cognition: Conceptual foundations.Nick Chater & Alan Yuille - 2006 - Trends in Cognitive Sciences 10 (7):287-291.
    Remarkable progress in the mathematics and computer science of probability has led to a revolution in the scope of probabilistic models. In particular, ‘sophisticated’ probabilistic methods apply to structured relational systems such as graphs and grammars, of immediate relevance to the cognitive sciences. This Special Issue outlines progress in this rapidly developing field, which provides a potentially unifying perspective across a wide range of domains and levels of explanation. Here, we introduce the historical and conceptual foundations of the approach, explore (...)
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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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  • Walsh on causes and evolution.Robert Northcott - 2010 - Philosophy of Science 77 (3):457-467.
    Denis Walsh has written a striking new defense in this journal of the statisticalist (i.e., noncausalist) position regarding the forces of evolution. I defend the causalist view against his new objections. I argue that the heart of the issue lies in the nature of nonadditive causation. Detailed consideration of that turns out to defuse Walsh’s ‘description‐dependence’ critique of causalism. Nevertheless, the critique does suggest a basis for reconciliation between the two competing views. *Received December 2009; revised December 2009. †To contact (...)
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  • Contrastive causation in the law.Jonathan Schaffer - 2010 - Legal Theory 16 (4):259-297.
    What conception of causation is at work in the law? I argue that the law implicitly relies on a contrastive conception. In a liability case where the defendant's breach of duty must be shown to have caused the plaintiff's damages, it is not enough to consider what would have happened if the cause had not occurredthe law requires us to look to a specific replacement for the effect, which in this case is the hypothetical outcome in which the plaintiff came (...)
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  • Neutral Monism Reconsidered.Erik C. Banks - 2010 - Philosophical Psychology 23 (2):173-187.
    Neutral monism is a position in metaphysics defended by Mach, James, and Russell in the early twentieth century. It holds that minds and physical objects are essentially two different orderings of the same underlying neutral elements of nature. This paper sets out some of the central concepts, theses and the historical background of ideas that inform this doctrine of elements. The discussion begins with the classic neutral monism of Mach, James, and Russell in the first part of the paper, then (...)
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  • Causation and the Agent’s Point of View.Sebastián Álvarez - 2014 - Theoria 29 (1):133-147.
    There are philosophers who deny that causal relations actually exist in nature, arguing that they are merely a product of our perspective as beings capable of intentional actions. In this paper I briefly explain this thesis and consider that it needs to be complemented with a basic non-causal ontological perspective which can account for phenomena taken as causal; I then describe what seems to be a good candidate for such an ontology and finally conclude, however, that it cannot dispense with (...)
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  • (1 other version)Contemporary debates in philosophy of science.Christopher Hitchcock (ed.) - 2004 - Malden, MA: Blackwell.
    Showcasing original arguments for well-defined positions, as well as clear and concise statements of sophisticated philosophical views, this volume is an ...
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  • Weighted explanations in history.Robert Northcott - 2008 - Philosophy of the Social Sciences 38 (1):76-96.
    , whereby some causes are deemed more important than others, are ubiquitous in historical studies. Drawing from influential recent work on causation, I develop a definition of causal-explanatory strength. This makes clear exactly which aspects of explanatory weighting are subjective and which objective. It also sheds new light on several traditional issues, showing for instance that: underlying causes need not be more important than proximate ones; several different causes can each be responsible for most of an effect; small causes need (...)
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  • (1 other version)The Causal Autonomy of the Special Sciences.Peter Menzies & Christian List - 2010 - In Graham Macdonald & Cynthia Macdonald (eds.), Emergence in mind. New York: Oxford University Press. pp. 108-129.
    The systems studied in the special sciences are often said to be causally autonomous, in the sense that their higher-level properties have causal powers that are independent of the causal powers of their more basic physical properties. This view was espoused by the British emergentists, who claimed that systems achieving a certain level of organizational complexity have distinctive causal powers that emerge from their constituent elements but do not derive from them. More recently, non-reductive physicalists have espoused a similar view (...)
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  • Scientific explanation.Michael Strevens - 2006 - In D. M. Borchert (ed.), Encyclopedia of Philosophy, second edition.
    The three cardinal aims of science are prediction, control, and explanation; but the greatest of these is explanation. Also the most inscrutable: prediction aims at truth, and control at happiness, and insofar as we have some independent grasp of these notions, we can evaluate science’s strategies of prediction and control from the outside. Explanation, by contrast, aims at scientific understanding, a good intrinsic to science and therefore something that it seems we can only look to science itself to explicate.
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  • Graphical models, causal inference, and econometric models.Peter Spirtes - 2005 - Journal of Economic Methodology 12 (1):3-34.
    A graphical model is a graph that represents a set of conditional independence relations among the vertices (random variables). The graph is often given a causal interpretation as well. I describe how graphical causal models can be used in an algorithm for constructing partial information about causal graphs from observational data that is reliable in the large sample limit, even when some of the variables in the causal graph are unmeasured. I also describe an algorithm for estimating from observational data (...)
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  • What is a macrostate? Subjective observations and objective dynamics.Cosma Rohilla Shalizi & Cristopher Moore - unknown
    We consider the question of whether thermodynamic macrostates are objective consequences of dynamics, or subjective reflections of our ignorance of a physical system. We argue that they are both; more specifically, that the set of macrostates forms the unique maximal partition of phase space which 1) is consistent with our observations (a subjective fact about our ability to observe the system) and 2) obeys a Markov process (an objective fact about the system's dynamics). We review the ideas of computational mechanics, (...)
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  • Causation, exclusion, and the special sciences.Panu Raatikainen - 2010 - Erkenntnis 73 (3):349-363.
    The issue of downward causation (and mental causation in particular), and the exclusion problem is discussed by taking into account some recent advances in the philosophy of science. The problem is viewed from the perspective of the new interventionist theory of causation developed by Woodward. It is argued that from this viewpoint, a higher-level (e.g., mental) state can sometimes truly be causally relevant, and moreover, that the underlying physical state which realizes it may fail to be such.
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  • A new solution to the puzzle of simplicity.Kevin T. Kelly - 2007 - Philosophy of Science 74 (5):561-573.
    Explaining the connection, if any, between simplicity and truth is among the deepest problems facing the philosophy of science, statistics, and machine learning. Say that an efficient truth finding method minimizes worst case costs en route to converging to the true answer to a theory choice problem. Let the costs considered include the number of times a false answer is selected, the number of times opinion is reversed, and the times at which the reversals occur. It is demonstrated that (1) (...)
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  • Interventions and causal inference.Frederick Eberhardt & Richard Scheines - 2007 - Philosophy of Science 74 (5):981-995.
    The literature on causal discovery has focused on interventions that involve randomly assigning values to a single variable. But such a randomized intervention is not the only possibility, nor is it always optimal. In some cases it is impossible or it would be unethical to perform such an intervention. We provide an account of ‘hard' and ‘soft' interventions and discuss what they can contribute to causal discovery. We also describe how the choice of the optimal intervention(s) depends heavily on the (...)
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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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  • (1 other version)Pragmatic causation.Antony Eagle - 2007 - In Huw Price & Richard Corry (eds.), Causation, Physics and the Constitution of Reality: Russell’s Republic Revisited. New York: Oxford University Press.
    Russell famously argued that causation should be dispensed with. He gave two explicit arguments for this conclusion, both of which can be defused if we loosen the ties between causation and determinism. I show that we can define a concept of causation which meets Russell’s conditions but does not reduce to triviality. Unfortunately, a further serious problem is implicit beneath the details of Russell’s arguments, which I call the causal exclusion problem. Meeting this problem involves deploying a minimalist pragmatic account (...)
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  • Independence, invariance and the causal Markov condition.Daniel M. Hausman & James Woodward - 1999 - British Journal for the Philosophy of Science 50 (4):521-583.
    This essay explains what the Causal Markov Condition says and defends the condition from the many criticisms that have been launched against it. Although we are skeptical about some of the applications of the Causal Markov Condition, we argue that it is implicit in the view that causes can be used to manipulate their effects and that it cannot be surrendered without surrendering this view of causation.
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  • (2 other versions)Causes and explanations: A structural-model approach. Part I: Causes.Joseph Y. Halpern & Judea Pearl - 2005 - British Journal for the Philosophy of Science 56 (4):843-887.
    We propose a new definition of actual causes, using structural equations to model counterfactuals. We show that the definition yields a plausible and elegant account of causation that handles well examples which have caused problems for other definitions and resolves major difficulties in the traditional account.
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  • Dispositional versus epistemic causality.Jon Williamson - 2006 - Minds and Machines 16 (3):259-276.
    I put forward several desiderata that a philosophical theory of causality should satisfy: it should account for the objectivity of causality, it should underpin formalisms for causal reasoning, it should admit a viable epistemology, it should be able to cope with the great variety of causal claims that are made, and it should be ontologically parsimonious. I argue that Nancy Cartwright’s dispositional account of causality goes part way towards meeting these criteria but is lacking in important respects. I go on (...)
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  • Causal inference of ambiguous manipulations.Peter Spirtes & Richard Scheines - 2004 - Philosophy of Science 71 (5):833-845.
    Over the last two decades, a fundamental outline of a theory of causal inference has emerged. However, this theory does not consider the following problem. Sometimes two or more measured variables are deterministic functions of one another, not deliberately, but because of redundant measurements. In these cases, manipulation of an observed defined variable may actually be an ambiguous description of a manipulation of some underlying variables, although the manipulator does not know that this is the case. In this article we (...)
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  • Causation and contrast classes.Robert Northcott - 2008 - Philosophical Studies 139 (1):111 - 123.
    I argue that causation is a contrastive relation: c-rather-than-C* causes e-rather-than-E*, where C* and E* are contrast classes associated respectively with actual events c and e. I explain why this is an improvement on the traditional binary view, and develop a detailed definition. It turns out that causation is only well defined in ‘uniform’ cases, where either all or none of the members of C* are related appropriately to members of E*.
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  • Bayesian Epistemology.Stephan Hartmann & Jan Sprenger - 2010 - In Sven Bernecker & Duncan Pritchard (eds.), The Routledge Companion to Epistemology. New York: Routledge. pp. 609-620.
    Bayesian epistemology addresses epistemological problems with the help of the mathematical theory of probability. It turns out that the probability calculus is especially suited to represent degrees of belief (credences) and to deal with questions of belief change, confirmation, evidence, justification, and coherence. Compared to the informal discussions in traditional epistemology, Bayesian epis- temology allows for a more precise and fine-grained analysis which takes the gradual aspects of these central epistemological notions into account. Bayesian epistemology therefore complements traditional epistemology; it (...)
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  • Analysing causality: The opposite of counterfactual is factual.Jim Bogen - 2002 - International Studies in the Philosophy of Science 18 (1):3 – 26.
    Using Jim Woodward's Counterfactual Dependency account as an example, I argue that causal claims about indeterministic systems cannot be satisfactorily analysed as including counterfactual conditionals among their truth conditions because the counterfactuals such accounts must appeal to need not have truth values. Where this happens, counterfactual analyses transform true causal claims into expressions which are not true.
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  • Grounding, metaphysical laws, and structure.Martin Grajner - 2021 - Analytic Philosophy 62 (4):376-395.
    According to the deductive-nomological account of ground, a fact A grounds another fact B in case the laws of metaphysics determine the existence of B on the basis of the existence of A. Accounts of grounding of this particular variety have already been developed in the literature. My aim in this paper is to sketch a new version of this account. My preferred account offers two main improvements over existing accounts. First, the present account is able to deal with necessitarian (...)
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  • What can bouncing oil droplets tell us about quantum mechanics?Peter W. Evans & Karim P. Y. Thébault - 2020 - European Journal for Philosophy of Science 10 (3):1-32.
    A recent series of experiments have demonstrated that a classical fluid mechanical system, constituted by an oil droplet bouncing on a vibrating fluid surface, can be induced to display a number of behaviours previously considered to be distinctly quantum. To explain this correspondence it has been suggested that the fluid mechanical system provides a single-particle classical model of de Broglie’s idiosyncratic ‘double solution’ pilot wave theory of quantum mechanics. In this paper we assess the epistemic function of the bouncing oil (...)
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  • Causal inference in biomedical research.Tudor M. Baetu - 2020 - Biology and Philosophy 35 (4):1-19.
    Current debates surrounding the virtues and shortcomings of randomization are symptomatic of a lack of appreciation of the fact that causation can be inferred by two distinct inference methods, each requiring its own, specific experimental design. There is a non-statistical type of inference associated with controlled experiments in basic biomedical research; and a statistical variety associated with randomized controlled trials in clinical research. I argue that the main difference between the two hinges on the satisfaction of the comparability requirement, which (...)
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  • The Modal Future: A Theory of Future-Directed Thought and Talk.Fabrizio Cariani - 2021 - Cambridge, UK: Cambridge University Press.
    Provisional draft, pre-production copy of my book “The Modal Future” (forthcoming with Cambridge University Press).
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  • Toward Mechanism 2.1: A Dynamic Causal Approach.Wei Fang - 2021 - Philosophy of Science 88 (5):796-809.
    I propose a dynamic causal approach to characterizing the notion of a mechanism. Levy and Bechtel, among others, have pointed out several critical limitations of the new mechanical philosophy, and pointed in a new direction to extend this philosophy. Nevertheless, they have not fully fleshed out what that extended philosophy would look like. Based on a closer look at neuroscientific practice, I propose that a mechanism is a dynamic causal system that involves various components interacting, typically nonlinearly, with one another (...)
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  • Why Attention is Not Explanation: Surgical Intervention and Causal Reasoning about Neural Models.Christopher Grimsley, Elijah Mayfield & Julia Bursten - 2020 - Proceedings of the 12th Conference on Language Resources and Evaluation.
    As the demand for explainable deep learning grows in the evaluation of language technologies, the value of a principled grounding for those explanations grows as well. Here we study the state-of-the-art in explanation for neural models for natural-language processing (NLP) tasks from the viewpoint of philosophy of science. We focus on recent evaluation work that finds brittleness in explanations obtained through attention mechanisms.We harness philosophical accounts of explanation to suggest broader conclusions from these studies. From this analysis, we assert the (...)
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  • Belief, Credence and Statistical Evidence.Davide Fassio & Jie Gao - 2020 - Theoria 86 (4):500-527.
    According to the Rational Threshold View, a rational agent believes p if and only if her credence in p is equal to or greater than a certain threshold. One of the most serious challenges for this view is the problem of statistical evidence: statistical evidence is often not sufficient to make an outright belief rational, no matter how probable the target proposition is given such evidence. This indicates that rational belief is not as sensitive to statistical evidence as rational credence. (...)
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  • (1 other version)Rethinking Causation for Data‐intensive Biology: Constraints, Cancellations, and Quantized Organisms.Douglas E. Brash - 2020 - Bioessays 42 (7):1900135.
    Complex organisms thwart the simple rectilinear causality paradigm of “necessary and sufficient,” with its experimental strategy of “knock down and overexpress.” This Essay organizes the eccentricities of biology into four categories that call for new mathematical approaches; recaps for the biologist the philosopher's recent refinements to the causation concept and the mathematician's computational tools that handle some but not all of the biological eccentricities; and describes overlooked insights that make causal properties of physical hierarchies such as emergence and downward causation (...)
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  • Modeling in Biology: looking backward and looking forward.Steven Hecht Orzack & Brian McLoone - 2019 - Studia Metodologiczne 39.
    Understanding modeling in biology requires understanding how biology is organized as a discipline and how this organization influences the research practices of biologists. Biology includes a wide range of sub-disciplines, such as cell biology, population biology, evolutionary biology, molecular biology, and systems biology among others. Biologists in sub-disciplines such as cell, molecular, and systems biology believe that the use of a few experimental models allows them to discover biological universals, whereas biologists in sub-disciplines such as ecology and evolutionary biology believe (...)
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  • Causation and Time Reversal.Matt Farr - 2020 - British Journal for the Philosophy of Science 71 (1):177-204.
    What would it be for a process to happen backwards in time? Would such a process involve different causal relations? It is common to understand the time-reversal invariance of a physical theory in causal terms, such that whatever can happen forwards in time can also happen backwards in time. This has led many to hold that time-reversal symmetry is incompatible with the asymmetry of cause and effect. This article critiques the causal reading of time reversal. First, I argue that the (...)
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  • Taking Control : The role of manipulation in theories of causation.Henning Strandin - 2019 - Dissertation, Stockholm University
    Causation has always been a philosophically controversial subject matter. While David Hume’s empiricist account of causation has been the dominant influence in analytic philosophy and science during modern times, a minority view has instead connected causation essentially to agency and manipulation. A related approach has for the first time gained widespread popularity in recent years, due to new powerful theories of causal inference in science that are based in a technical notion of intervention, and James Woodward’s closely connected interventionist theory (...)
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  • The problem of granularity for scientific explanation.David Kinney - 2019 - Dissertation, London School of Economics and Political Science (Lse)
    This dissertation aims to determine the optimal level of granularity for the variables used in probabilistic causal models. These causal models are useful for generating explanations in a number of scientific contexts. In Chapter 1, I argue that there is rarely a unique level of granularity at which a given phenomenon can be causally explained, thereby rejecting various causal exclusion arguments. In Chapter 2, I consider several recent proposals for measuring the explanatory power of causal explanations, and show that these (...)
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  • Causal Inference from Noise.Nevin Climenhaga, Lane DesAutels & Grant Ramsey - 2021 - Noûs 55 (1):152-170.
    "Correlation is not causation" is one of the mantras of the sciences—a cautionary warning especially to fields like epidemiology and pharmacology where the seduction of compelling correlations naturally leads to causal hypotheses. The standard view from the epistemology of causation is that to tell whether one correlated variable is causing the other, one needs to intervene on the system—the best sort of intervention being a trial that is both randomized and controlled. In this paper, we argue that some purely correlational (...)
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  • Conditional Probabilities.Kenny Easwaran - 2019 - In Richard Pettigrew & Jonathan Weisberg (eds.), The Open Handbook of Formal Epistemology. PhilPapers Foundation. pp. 131-198.
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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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  • Representing credal imprecision: from sets of measures to hierarchical Bayesian models.Daniel Lassiter - 2020 - Philosophical Studies 177 (6):1463-1485.
    The basic Bayesian model of credence states, where each individual’s belief state is represented by a single probability measure, has been criticized as psychologically implausible, unable to represent the intuitive distinction between precise and imprecise probabilities, and normatively unjustifiable due to a need to adopt arbitrary, unmotivated priors. These arguments are often used to motivate a model on which imprecise credal states are represented by sets of probability measures. I connect this debate with recent work in Bayesian cognitive science, where (...)
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  • Explanatory autonomy: the role of proportionality, stability, and conditional irrelevance.James Woodward - 2018 - Synthese 198 (1):1-29.
    This paper responds to recent criticisms of the idea that true causal claims, satisfying a minimal “interventionist” criterion for causation, can differ in the extent to which they satisfy other conditions—called stability and proportionality—that are relevant to their use in explanatory theorizing. It reformulates the notion of proportionality so as to avoid problems with previous formulations. It also introduces the notion of conditional independence or irrelevance, which I claim is central to understanding the respects and the extent to which upper (...)
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  • Defining Metabolic Syndrome: Which Kind of Causality, if any, is Required?Margherita Benzi - 2017 - Disputatio 9 (47):553-580.
    The definition of metabolic syndrome has been, and still is, extremely controversial. My purpose is not to give a solution to the associated debate but to argue that the controversy is at least partially due to the different ‘causal content’ of the various definitions: their theoretical validity and practical utility can be evaluated by reconstructing or making explicit the underlying causal structure. I will therefore propose to distinguish the alternative definitions according to the kinds of causal content they carry: definitions (...)
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  • Computer Simulations in Science and Engineering. Concept, Practices, Perspectives.Juan Manuel Durán - 2018 - Springer.
    This book addresses key conceptual issues relating to the modern scientific and engineering use of computer simulations. It analyses a broad set of questions, from the nature of computer simulations to their epistemological power, including the many scientific, social and ethics implications of using computer simulations. The book is written in an easily accessible narrative, one that weaves together philosophical questions and scientific technicalities. It will thus appeal equally to all academic scientists, engineers, and researchers in industry interested in questions (...)
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  • Causal Learning with Occam’s Razor.Oliver Schulte - 2019 - Studia Logica 107 (5):991-1023.
    Occam’s razor directs us to adopt the simplest hypothesis consistent with the evidence. Learning theory provides a precise definition of the inductive simplicity of a hypothesis for a given learning problem. This definition specifies a learning method that implements an inductive version of Occam’s razor. As a case study, we apply Occam’s inductive razor to causal learning. We consider two causal learning problems: learning a causal graph structure that presents global causal connections among a set of domain variables, and learning (...)
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  • Intervening into mechanisms: Prospects and challenges.Lena Kästner & Lise Marie Andersen - 2018 - Philosophy Compass 13 (11):e12546.
    In contemporary philosophy of science, the consensus view seems to be that scientific explanations describe mechanisms responsible for the phenomena to be explained. Two kinds of explanatory relevance figure in mechanistic accounts of explanation: causal and constitutive. Following prominent accounts, it seems natural to analyze both these relations in terms of systematic interventions into some factor X with respect to another factor Y. However, such interventions are tailored to uncover causal relations only. Construing the constitutive relationship between parts and wholes (...)
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  • (1 other version)Horizontal Surgicality and Mechanistic Constitution.Michael Baumgartner, Lorenzo Casini & Beate Krickel - 2020 - Erkenntnis 85:417-430.
    While ideal interventions are acknowledged by many as valuable tools for the analysis of causation, recent discussions have shown that, since there are no ideal interventions on upper-level phenomena that non-reductively supervene on their underlying mechanisms, interventions cannot—contrary to a popular opinion—ground an informative analysis of constitution. This has led some to abandon the project of analyzing constitution in interventionist terms. By contrast, this paper defines the notion of a horizontally surgical intervention, and argues that, when combined with some innocuous (...)
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  • First principles in the life sciences: the free-energy principle, organicism, and mechanism.Matteo Colombo & Cory Wright - 2021 - Synthese 198 (14):3463–3488.
    The free-energy principle states that all systems that minimize their free energy resist a tendency to physical disintegration. Originally proposed to account for perception, learning, and action, the free-energy principle has been applied to the evolution, development, morphology, anatomy and function of the brain, and has been called a postulate, an unfalsifiable principle, a natural law, and an imperative. While it might afford a theoretical foundation for understanding the relationship between environment, life, and mind, its epistemic status is unclear. Also (...)
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