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  1. Eliciting the plurality of causal reasoning in social-ecological systems research.Tilman Hertz, T. Homas Banitz, Rodrigo Martínez-Peña, Sonja Radosavljevic, Emilie Lindkvist, Lars-Göran Johansson, Petri Ylikoski & Maja Schlüter - unknown
    Understanding causation in social-ecological systems (SES) is indispensable for promoting sustainable outcomes. However, the study of such causal relations is challenging because they are often complex and intertwined, and their analysis involves diverse disciplines. Although there is agreement that no single research approach (RA) can comprehensively explain SES phenomena, there is a lack of ability to deal with this diversity. Underlying this diversity and the challenge of dealing with it are different causal reasonings that are rarely explicit. Awareness of hidden (...)
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  2. Bodies of evidence: The ‘Excited Delirium Syndrome’ and the epistemology of cause-of-death inquiry.Enno Fischer & Saana Jukola - 2024 - Studies in History and Philosophy of Science 104 (C):38-47.
    “Excited Delirium Syndrome” (ExDS) is a controversial diagnosis. The supposed syndrome is sometimes considered to be a potential cause of death. However, it has been argued that its sole purpose is to cover up excessive police violence because it is mainly used to explain deaths of individuals in custody. In this paper, we examine the epistemic conditions giving rise to the controversial diagnosis by discussing the relation between causal hypotheses, evidence, and data in forensic medicine. We argue that the practitioners’ (...)
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  3. Causal reasoning from almost first principles.Alexander Bochman - 2024 - Synthese 203 (1):1-34.
    A formal theory of causal reasoning is presented that encompasses both Pearl’s approach to causality and several key formalisms of nonmonotonic reasoning in Artificial Intelligence. This theory will be derived from a single rationality principle of causal acceptance for propositions. However, this principle will also set the theory of causal reasoning apart from common representational approaches to reasoning formalisms.
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  4. James Woodward: Causation with a Human Face: Normative Theory and Descriptive Psychology. [REVIEW]Enno Fischer - 2023 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 54 (4):625-629.
  5. Counterfactual Causal Reasoning in Smithian Sympathy.Eric Schliesser - 2014 - Revue Internationale de Philosophie 269 (3):307-316.
    This paper argues that according to Adam Smith the workings of (anything but extremely simple) sympathetic judgment (s) presuppose and crucially depend on counterfactual causal reasoning in the sympathetic process. In particular it argues for four related claims: (i) that according to Smith that the sympathetic process depends on a type of causal reasoning that goes well beyond the kind of simulationist theory standardly attributed to him; (ii) that the Smithian imagination in the sympathetic process works by way of counterfactual (...)
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  6. Rethinking Human and Machine Intelligence through Kant, Wittgenstein, Gödel, and Cantor.Lee Jae Jeong - manuscript
    This paper proposes a new metaphysical framework for distinguishing between human and machine intelligence by drawing on Kant’s incongruent counterparts as an analogy. Specifically, the paper posits two deterministic worlds that are superficially identical but ultimately different. Using ideas from Wittgenstein, Gödel, and Cantor, the paper defines “deterministic knowledge” and investigates how this knowledge is processed differently in those two worlds. The paper considers computationalism and causal determinism for the new framework. Then, the paper introduces new concepts to illustrate why (...)
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  7. Some Reflections on Causation.Yafeng Shan - 2024 - In Alternative Philosophical Approaches to Causation: Beyond Difference-making and Mechanism. Oxford: Oxford University Press. pp. 1-12.
    Philosophical analyses of causation have been centred on the question of what causation is. More precisely speaking, philosophers tend to address four different issues: metaphysical (what is causation out there?), epistemological (how can a causal claim be established and assessed?), conceptual (what does the word ‘cause’ mean?), and methodological (what methods ought one to use in order to establish and assess causal claims?). This chapter argues that the practical issue of causation (what is a causal claim for in practice?) is (...)
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  8. Native Ontological Framework Guides Causal Reasoning: Evidence from Wichi People.Matías Fernández Ruiz & Andrea Taverna - 2023 - Journal of Cognition and Culture 23 (3-4):397-419.
    Causal cognition – how we perceive, represent and reason about causal events – are fundamental to the human mind, but it has rarely been approached in its cultural specificity. Here, we investigate this core concept among Wichi people, an indigenous group living in Chaco Forest. We focus on the Wichi, because their epistemological orientations and explanatory frameworks about ecosystem differ importantly from those documented among most Western majority-culture populations. We asked participants to reason about causes of events that involve the (...)
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  9. Constructing science: connecting causal reasoning to scientific thinking in young children.Deena Skolnick Weisberg - 2022 - Cambridge, Massachusetts: The MIT Press. Edited by David M. Sobel.
    A novel attempt to explain why teens and adults often struggle with scientific explanation even thought young children clearly possess impressive causal reasoning skills.
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  10. On Pearl's Hierarchy and the Foundations of Causal Inference.Elias Bareinboim, Juan Correa, Duligur Ibeling & Thomas Icard - 2022 - In Hector Geffner, Rita Dechter & Joseph Halpern (eds.), Probabilistic and Causal Inference: the Works of Judea Pearl. ACM Books. pp. 507-556.
    Cause and effect relationships play a central role in how we perceive and make sense of the world around us, how we act upon it, and ultimately, how we understand ourselves. Almost two decades ago, computer scientist Judea Pearl made a breakthrough in understanding causality by discovering and systematically studying the “Ladder of Causation” [Pearl and Mackenzie 2018], a framework that highlights the distinct roles of seeing, doing, and imagining. In honor of this landmark discovery, we name this the Pearl (...)
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  11. Review of Causation with a Human Face, James Woodward. [REVIEW]Holly Andersen - forthcoming - Philosophy of Science:1-6.
    I provide an overview and critical discussion of Causation with a Human Face, by James Woodward.
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  12. A Dialogue among Recent Views of Entity Realism.Mahdi Khalili - 2023 - Philosophy of Science:1-35.
    This paper concerns the recent revival of entity realism. Having been started with the work of Ian Hacking, Nancy Cartwright and Ronald Giere, the project of entity realism has recently been developed by Matthias Egg, Markus Eronen, and Bence Nanay. The paper opens a dialogue among these recent views on entity realism and integrates them into a more advanced view. The result is an epistemological criterion for reality: the property-tokens of a certain type may be taken as real insofar as (...)
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  13. Reasoning Studies. From Single Norms to Individual Differences.Niels Skovgaard-Olsen - 2022 - Dissertation, University of Freiburg
    Habilitation thesis in psychology. The book consists of a collection of reasoning studies. The experimental investigations will take us from people’s reasoning about probabilities, entailments, pragmatic factors, argumentation, and causality to morality. An overarching theme of the book is norm pluralism and individual differences in rationality research.
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  14. Computing with causal theories.Erkan Tin & Varol Akman - 1992 - International Journal of Pattern Recognition and Artificial Intelligence 6 (4):699-730.
    Formalizing commonsense knowledge for reasoning about time has long been a central issue in AI. It has been recognized that the existing formalisms do not provide satisfactory solutions to some fundamental problems, viz. the frame problem. Moreover, it has turned out that the inferences drawn do not always coincide with those one had intended when one wrote the axioms. These issues call for a well-defined formalism and useful computational utilities for reasoning about time and change. Yoav Shoham of Stanford University (...)
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  15. The logic of counteraction.Erkan Tin & Varol Akman - 1993 - Elektrik 1 (3):167-181.
    We extend causal theories and study actions in domains involving multiple agents. Causal theories, invented by Yoav Shoham, are based on a temporal nonmonotonic logic and have computationally tractable aspects. Since Shoham's formalism does not provide an adequate mechanism for representing simultaneous actions and specifying their consequences, we introduce the notion of counteractions while preserving the efficiency and model-theoretic properties of causal theories.
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  16. Risk, Precaution, and Causation.Masaki Ichinose - 2022 - Tetsugaku: International Journal of the Philosophical Association of Japan 6:22-53.
    This paper aims to scrutinize how the notion of risk should be understood and applied to possibly catastrophic cases. I begin with clarifying the standard usage of the notion of risk, particularly emphasizing the conceptual relation between risk and probability. Then, I investigate how to make decisions in the case of seemingly catastrophic disasters by contrasting the precautionary principle with the preventive (prevention) principle. Finally, I examine what kind of causal thinking tends to be actually adopted when we make decisions (...)
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  17. Domain-Specific Perceptual Causality in Children Depends on the SpatioTemporal Configuration, Not Motion Onset.Anne Schlottmann, Katy Cole, Rhianna Watts & Marina White - 2014 - In Marc J. Buehner (ed.), Time and causality. [Lausanne, Switzerland]: Frontiers Media SA.
  18. Time and Causality: Editorial.Marc J. Buehner - 2014 - In Time and causality. [Lausanne, Switzerland]: Frontiers Media SA.
  19. Time and causality.Marc J. Buehner (ed.) - 2014 - [Lausanne, Switzerland]: Frontiers Media SA.
    This research topic will review and further explore the nature of the mutual influence between time and causality, how causal knowledge is constructed in the context of time, and how it in turn shapes and alters our perception of time. We aim to draw together literatures from the perception and cognitive science, and welcome experimental as well as theoretical papers. Contributions investigating the neural bases of binding and causal learning/perception, methodological advances, as well as articles addressing functional implications of causal (...)
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  20. Part I: Causal Reasoning in the Context of Normative and Descriptive Psychology: Configuration of Causality and Philosophy of Psychology: An Analysis of Causality as Intervention and Its Repercussion for Psychology / Wenceslao J. Gonzalez. Normative Theory and Descriptive Psychology in Understanding Causal Reasoning: The Role of Interventions and Invariance.James Woodward - 2018 - In Wenceslao J. González (ed.), Philosophy of Psychology: Causality and Psychological Subject: New Reflections on James Woodward’s Contribution. Boston: De Gruyter.
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  21. Inferential Pluralism in Causal Reasoning from Randomized Experiments.Tudor M. Baetu - 2022 - Acta Biotheoretica 70 (4):1-20.
    Causal pluralism can be defended not only in respect to causal concepts and methodological guidelines, but also at the finer-grained level of causal inference from a particular source of evidence for causation. An argument for this last variety of pluralism is made based on an analysis of causal inference from randomized experiments (RCTs). Here, the causal interpretation of a statistically significant association can be established via multiple paths of reasoning, each relying on different assumptions and providing distinct elements of information (...)
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  22. Philosophy of Psychology: Causality and Psychological Subject: New Reflections on James Woodward’s Contribution.Wenceslao J. González (ed.) - 2018 - Boston: De Gruyter.
    Contemporary philosophy of science analyzes psychology as a science with special features, because this discipline includes some specific philosophical problems – descriptive and normative, structural and dynamic. Some of these are particularly relevant both theoretically and practically. Two central aspects in this book are the role of causality, especially conceived as intervention or manipulation, and the characterization of the psychological subject. This requires a clarification of scientific explanations in terms of causality in psychology, because characterizations of causality are quite different (...)
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  23. New Contributions to Psychology as a Special Science: Causality and Psychological Subject.Wenceslao J. Gonzalez - 2018 - In Wenceslao J. González (ed.), Philosophy of Psychology: Causality and Psychological Subject: New Reflections on James Woodward’s Contribution. Boston: De Gruyter. pp. 1-18.
  24. Causality and attribution in an Aristotelian Theory.Srećko Kovač - 2015 - In Arnold Koslow & Arthur Buchsbaum (eds.), The Road to Universal Logic: Festschrift for 50th Birthday of Jean-Yves Béziau, vol. 1. Cham, Heidelberg, etc.: Springer-Birkhäuser. pp. 327-340.
    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, (...)
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Causal Modeling
  1. Causal modeling semantics for counterfactuals with disjunctive antecedents.Giuliano Rosella & Jan Sprenger - 2024 - Annals of Pure and Applied Logic 175 (9):103336.
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  2. Engineering Social Concepts: Feasibility and Causal Models.Eleonore Neufeld - forthcoming - Philosophy and Phenomenological Research.
    How feasible are conceptual engineering projects of social concepts that aim for the engineered concept to be widely adopted in ordinary everyday life? Predominant frameworks on the psychology of concepts that shape work on stereotyping, bias, and machine learning have grim implications for the prospects of conceptual engineers: conceptual engineering efforts are ineffective in promoting certain social-conceptual changes. Specifically, since conceptual components that give rise to problematic social stereotypes are sensitive to statistical structures of the environment, purely conceptual change won’t (...)
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  3. The Chances of Choices.Reuben Stern - forthcoming - British Journal for the Philosophy of Science.
  4. Causal modeling in multilevel settings: A new proposal.Thomas Blanchard & Andreas Hüttemann - forthcoming - Philosophy and Phenomenological Research.
    An important question for the causal modeling approach is how to integrate non‐causal dependence relations such as asymmetric supervenience into the approach. The most prominent proposal to that effect (due to Gebharter) is to treat those dependence relationships as formally analogous to causal relationships. We argue that this proposal neglects some crucial differences between causal and non‐causal dependencies, and that in the context of causal modeling non‐causal dependence relationships should be represented as mutual dependence relationships. We develop a new kind (...)
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  5. Broken brakes and dreaming drivers: the heuristic value of causal models in the law.Enno Fischer - 2024 - European Journal for Philosophy of Science 14 (1):1-20.
    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 (...)
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  6. An Inferential Theory of Causal Reasoning.Alexander Bochman - 2023 - In Natasha Alechina, Andreas Herzig & Fei Liang (eds.), Logic, Rationality, and Interaction: 9th International Workshop, LORI 2023, Jinan, China, October 26–29, 2023, Proceedings. Springer Nature Switzerland. pp. 1-16.
    We present a general formalism of causal reasoning that encompasses both Pearl’s approach to causality and a number of key systems of nonmonotonic reasoning in artificial intelligence.
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  7. Causal counterfactuals without miracles or backtracking.J. Dmitri Gallow - 2022 - Philosophy and Phenomenological Research 107 (2):439-469.
    If the laws are deterministic, then standard theories of counterfactuals are forced to reject at least one of the following conditionals: 1) had you chosen differently, there would not have been a violation of the laws of nature; and 2) had you chosen differently, the initial conditions of the universe would not have been different. On the relevant readings—where we hold fixed factors causally independent of your choice—both of these conditionals appear true. And rejecting either one leads to trouble for (...)
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  8. Just Probabilities.Chad Lee-Stronach - forthcoming - Noûs.
    I defend the thesis that legal standards of proof are reducible to thresholds of probability. Many have rejected this thesis because it seems to entail that defendants can be found liable solely on the basis of statistical evidence. I argue that this inference is invalid. I do so by developing a view, called Legal Causalism, that combines Thomson's (1986) causal analysis of evidence with recent work in formal theories of causal inference. On this view, legal standards of proof can be (...)
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  9. Why adoption of causal modeling methods requires some metaphysics.Holly Andersen - 2023 - In Federica Russo & Phyllis Illari (eds.), 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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  10. Causal Variable Choice, Interventions, and Pragmatism.Zili Dong - 2023 - Dissertation, University of Western Ontario
    The past century has witnessed numerous methodological innovations in probabilistic and statistical methods of causal inference (e.g., the graphical modelling and the potential outcomes frameworks, as introduced in Chapter 1). These innovations have not only enhanced the methodologies by which scientists across diverse domains make causal inference, but they have also made a profound impact on the way philosophers think about causation. The philosophical issues discussed in this thesis are stimulated and inspired by these methodological innovations. Chapter 2 addresses the (...)
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  11. Actual Causation: Apt Causal Models and Causal Relativism.Jennifer McDonald - 2022 - Dissertation, The Graduate Center, Cuny
    This dissertation begins by addressing the question of when a causal model is apt for deciding questions of actual causation with respect to some target situation. I first provide relevant background about causal models, explain what makes them promising as a tool for analyzing actual causation, and motivate the need for a theory of aptness as part of such an analysis (Chapter 1). I then define what it is for a model on a given interpretation to be accurate of, that (...)
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  12. Essential Structure for Causal Models.Jennifer McDonald - forthcoming - Australasian Journal of Philosophy.
    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 (...)
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  13. Causal Search, Causal Modeling, and the Folk.David Danks - 2016 - In Wesley Buckwalter & Justin Sytsma (eds.), Blackwell Companion to Experimental Philosophy. Malden, MA: Blackwell. pp. 463–471.
    Causal models provide a framework for precisely representing complex causal structures, where specific models can be used to efficiently predict, infer, and explain the world. At the same time, we often do not know the full causal structure a priori and so must learn it from data using a causal model search algorithm. This chapter provides a general overview of causal models and their uses, with a particular focus on causal graphical models (the most commonly used causal modeling framework) and (...)
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  14. Anti-reductionist Interventionism.Reuben Stern & Benjamin Eva - 2023 - British Journal for the Philosophy of Science 74 (1):241-267.
    Kim’s causal exclusion argument purports to demonstrate that the non-reductive physicalist must treat mental properties (and macro-level properties in general) as causally inert. A number of authors have attempted to resist Kim’s conclusion by utilizing the conceptual resources of Woodward’s interventionist conception of causation. The viability of these responses has been challenged by Gebharter, who argues that the causal exclusion argument is vindicated by the theory of causal Bayesian networks (CBNs). Since the interventionist conception of causation relies crucially on CBNs (...)
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  15. Conjoined cases.Tomasz Wysocki - 2023 - Synthese 201 (6):1-19.
    Incorporating normality ascriptions into counterfactual theories of causation was supposed to handle isomorphs. It doesn’t—conjoining isomorphs can produce cases that such ascriptions cannot resolve.
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  16. How to Trace a Causal Process.J. Dmitri Gallow - 2022 - Philosophical Perspectives 36 (1):95-117.
    According to the theory developed here, we may trace out the processes emanating from a cause in such a way that any consequence lying along one of these processes counts as an effect of the cause. This theory gives intuitive verdicts in a diverse range of problem cases from the literature. Its claims about causation will never be retracted when we include additional variables in our model. And it validates some plausible principles about causation, including Sartorio's ‘Causes as Difference Makers’ (...)
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  17. Minimal Turing Test and Children's Education.Duan Zhang, Xiaoan Wu & Jijun He - 2022 - Journal of Human Cognition 6 (1):47-58.
    Considerable evidence proves that causal learning and causal understanding greatly enhance our ability to manipulate the physical world and are major factors that distinguish humans from other primates. How do we enable unintelligent robots to think causally, answer the questions raised with "why" and even understand the meaning of such questions? The solution is one of the keys to realizing artificial intelligence. Judea Pearl believes that to achieve human-like intelligence, researchers must start by imitating the intelligence of children, so he (...)
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  18. Causal Bayes nets and token-causation: Closing the gap between token-level and type-level.Alexander Gebharter & Andreas Hüttemann - forthcoming - Erkenntnis:1-23.
    Causal Bayes nets (CBNs) provide one of the most powerful tools for modelling coarse-grained type-level causal structure. As in other fields (e.g., thermodynamics) the question arises how such coarse-grained characterisations are related to the characterisation of their underlying structure (in this case: token-level causal relations). Answering this question meets what is called a “coherence-requirement” in the reduction debate: How are different accounts of one and the same system (or kind of system) related to each other. We argue that CBNs as (...)
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  19. Actual Causation and the Challenge of Purpose.Enno Fischer - forthcoming - Erkenntnis:1-21.
    This paper explores the prospects of employing a functional approach in order to improve our concept of actual causation. Claims of actual causation play an important role for a variety of purposes. In particular, they are relevant for identifying suitable targets for intervention, and they are relevant for our practices of ascribing responsibility. I argue that this gives rise to the challenge of purpose. The challenge of purpose arises when different goals demand adjustments of the concept that pull in opposing (...)
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  20. A Causal Safety Criterion for Knowledge.Jonathan Vandenburgh - forthcoming - Erkenntnis:1-21.
    Safety purports to explain why cases of accidentally true belief are not knowledge, addressing Gettier cases and cases of belief based on statistical evidence. However, problems arise for using safety as a condition on knowledge: safety is not necessary for knowledge and cannot always explain the Gettier cases and cases of statistical evidence it is meant to address. In this paper, I argue for a new modal condition designed to capture the non-accidental relationship between facts and evidence required for knowledge: (...)
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  21. Unification and explanation from a causal perspective.Alexander Gebharter & Christian J. Feldbacher-Escamilla - 2023 - Studies in History and Philosophy of Science Part A 99 (C):28-36.
    We discuss two influential views of unification: mutual information unification (MIU) and common origin unification (COU). We propose a simple probabilistic measure for COU and compare it with Myrvold’s (2003, 2017) probabilistic measure for MIU. We then explore how well these two measures perform in simple causal settings. After highlighting several deficiencies, we propose causal constraints for both measures. A comparison with explanatory power shows that the causal version of COU is one step ahead in simple causal settings. However, slightly (...)
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  22. Well-Defined Interventions and Causal Variable Choice.Zili Dong - 2023 - Philosophy of Science 90 (2):395-412.
    There has been much debate among scientists and philosophers about what it means for interventions invoked in causal inference to be “well-defined” and how considerations of this sort should constrain the choice of causal variables. In this paper, I propose that an intervention is well-defined just in case the effect of interest is well-defined, and that the intervention can serve as a suitable means to identify that effect. Based on this proposal, I identify several types of ambiguous intervention. Implications for (...)
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  23. Causal bias in measures of inequality of opportunity.Lennart B. Ackermans - 2022 - Synthese 200 (6):1-31.
    In recent decades, economists have developed methods for measuring the country-wide level of inequality of opportunity. The most popular method, called the ex-ante method, uses data on the distribution of outcomes stratified by groups of individuals with the same circumstances, in order to estimate the part of outcome inequality that is due to these circumstances. I argue that these methods are potentially biased, both upwards and downwards, and that the unknown size of this bias could be large. To argue that (...)
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  24. Why: a guide to finding and using causes.Samantha Kleinberg - 2015 - Boston: O'Reilly.
    Can drinking coffee help people live longer? What makes a stock's price go up? Why did you get the flu? Causal questions like these arise on a regular basis, but most people likely have not thought deeply about how to answer them. This book helps you think about causality in a structured way: What is a cause, what are causes good for, and what is compelling evidence of causality? Author Samantha Kleinberg shows you how to develop a set of tools (...)
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  25. Enough blanket metaphysics, time for data-driven heuristics.Wiktor Rorot, Tomasz Korbak, Piotr Litwin & Marcin Miłkowski - 2022 - Behavioral and Brain Sciences 45:e206.
    Bruineberg and colleagues criticisms' have been received but downplayed in the free energy principle (FEP) literature. We strengthen their points, arguing that Friston blanket discovery, even if tractable, requires a full formal description of the system of interest at the outset. Hence, blanket metaphysics is futile, and we postulate that researchers should turn back to heuristic uses of Pearl blankets.
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  26. Causal reductionism and causal structures.Matteo Grasso, Larissa Albantakis, Jonathan Lang & Giulio Tononi - 2021 - Nature Neuroscience 24:1348–1355.
    Causal reductionism is the widespread assumption that there is no room for additional causes once we have accounted for all elementary mechanisms within a system. Due to its intuitive appeal, causal reductionism is prevalent in neuroscience: once all neurons have been caused to fire or not to fire, it seems that causally there is nothing left to be accounted for. Here, we argue that these reductionist intuitions are based on an implicit, unexamined notion of causation that conflates causation with prediction. (...)
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