4 found
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  1. Conditionals and the Hierarchy of Causal Queries.Niels Skovgaard-Olsen, Simon Stephan & Michael R. Waldmann - 2021 - Journal of Experimental Psychology: General 1 (12):2472-2505.
    Recent studies indicate that indicative conditionals like "If people wear masks, the spread of Covid-19 will be diminished" require a probabilistic dependency between their antecedents and consequents to be acceptable (Skovgaard-Olsen et al., 2016). But it is easy to make the slip from this claim to the thesis that indicative conditionals are acceptable only if this probabilistic dependency results from a causal relation between antecedent and consequent. According to Pearl (2009), understanding a causal relation involves multiple, hierarchically organized conceptual dimensions: (...)
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    Preemption in Singular Causation Judgments: A Computational Model.Simon Stephan & Michael R. Waldmann - 2018 - Topics in Cognitive Science 10 (1):242-257.
    Causal queries about singular cases are ubiquitous, yet the question of how we assess whether a particular outcome was actually caused by a specific potential cause turns out to be difficult to answer. Relying on the causal power framework, Cheng and Novick () proposed a model of causal attribution intended to help answer this question. We challenge this model, both conceptually and empirically. We argue that the central problem of this model is that it treats causal powers that are probabilistically (...)
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    Time and Singular Causation—A Computational Model.Simon Stephan, Ralf Mayrhofer & Michael R. Waldmann - 2020 - Cognitive Science 44 (7).
    Causal queries about singular cases, which inquire whether specific events were causally connected, are prevalent in daily life and important in professional disciplines such as the law, medicine, or engineering. Because causal links cannot be directly observed, singular causation judgments require an assessment of whether a co‐occurrence of two events c and e was causal or simply coincidental. How can this decision be made? Building on previous work by Cheng and Novick (2005) and Stephan and Waldmann (2018), we propose a (...)
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    Interpolating Causal Mechanisms: The Paradox of Knowing More.Simon Stephan, Katya Tentori, Stefania Pighin & Michael R. Waldmann - 2021 - Journal of Experimental Psychology: General 150 (8):1500-1527.
    Causal knowledge is not static; it is constantly modified based on new evidence. The present set of seven experiments explores 1 important case of causal belief revision that has been neglected in research so far: causal interpolations. A simple prototypic case of an interpolation is a situation in which we initially have knowledge about a causal relation or a positive covariation between 2 variables but later become interested in the mechanism linking these 2 variables. Our key finding is that the (...)
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