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  1. Looking at Mental Images: Eye‐Tracking Mental Simulation During Retrospective Causal Judgment.Kristina Krasich, Kevin O'Neill & Felipe De Brigard - 2024 - Cognitive Science 48 (3):e13426.
    How do people evaluate causal relationships? Do they just consider what actually happened, or do they also consider what could have counterfactually happened? Using eye tracking and Gaussian process modeling, we investigated how people mentally simulated past events to judge what caused the outcomes to occur. Participants played a virtual ball‐shooting game and then—while looking at a blank screen—mentally simulated (a) what actually happened, (b) what counterfactually could have happened, or (c) what caused the outcome to happen. Our findings showed (...)
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  • Mechanistic Theories of Causality Part II.Jon Williamson - 2011 - Philosophy Compass 6 (6):433-444.
    Part I of this paper introduced a range of mechanistic theories of causality, including process theories and the complex-systems theories, and some of the problems they face. Part II argues that while there is a decisive case against a purely mechanistic analysis, a viable theory of causality must incorporate mechanisms as an ingredient, and describes one way of providing an analysis of causality which reaps the rewards of the mechanistic approach without succumbing to its pitfalls.
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  • Mechanistic Theories of Causality Part I.Jon Williamson - 2011 - Philosophy Compass 6 (6):421-432.
    Part I of this paper introduces a range of mechanistic theories of causality, including process theories and the complex-systems theories, and some of the problems they face. Part II argues that while there is a decisive case against a purely mechanistic analysis, a viable theory of causality must incorporate mechanisms as an ingredient, and describes one way of providing an analysis of causality which reaps the rewards of the mechanistic approach without succumbing to its pitfalls.
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  • Models in Systems Medicine.Jon Williamson - 2017 - Disputatio 9 (47):429-469.
    Systems medicine is a promising new paradigm for discovering associations, causal relationships and mechanisms in medicine. But it faces some tough challenges that arise from the use of big data: in particular, the problem of how to integrate evidence and the problem of how to structure the development of models. I argue that objective Bayesian models offer one way of tackling the evidence integration problem. I also offer a general methodology for structuring the development of models, within which the objective (...)
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  • A logic for 'because'.Benjamin Schnieder - 2011 - Review of Symbolic Logic 4 (3):445-465.
    In spite of its significance for everyday and philosophical discourse, the explanatory connective has not received much treatment in the philosophy of logic. The present paper develops a logic for based on systematic connections between and the truth-functional connectives.
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  • EnviroGenomarkers: The Interplay Between Mechanisms and Difference Making in Establishing Causal Claims.Federica Russo & Jon Williamson - 2012 - Medicine Studies 3 (4):249-262.
    According to Russo and Williamson (Int Stud Philos Sci 21(2):157–170, 2007, Hist Philos Life Sci 33:389–396, 2011a, Philos Sci 1(1):47–69, 2011b ), in order to establish a causal claim of the form, ‘_C_ is a cause of _E_’, one typically needs evidence that there is an underlying mechanism between _C_ and _E_ as well as evidence that _C_ makes a difference to _E_. This thesis has been used to argue that hierarchies of evidence, as championed by evidence-based movements, tend to (...)
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  • Why Theories of Causality Need Production : an Information Transmission Account.Phyllis McKay Illari - 2011 - Philosophy and Technology 24 (2):95-114.
    In this paper, I examine the comparatively neglected intuition of production regarding causality. I begin by examining the weaknesses of current production accounts of causality. I then distinguish between giving a good production account of causality and a good account of production. I argue that an account of production is needed to make sense of vital practices in causal inference. Finally, I offer an information transmission account of production based on John Collier’s work that solves the primary weaknesses of current (...)
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  • Information Channels and Biomarkers of Disease.Phyllis Illari & Federica Russo - 2016 - Topoi 35 (1):175-190.
    Current research in molecular epidemiology uses biomarkers to model the different disease phases from environmental exposure, to early clinical changes, to development of disease. The hope is to get a better understanding of the causal impact of a number of pollutants and chemicals on several diseases, including cancer and allergies. In a recent paper Russo and Williamson address the question of what evidential elements enter the conceptualisation and modelling stages of this type of biomarkers research. Recent research in causality has (...)
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