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Henne, Paul; O'Neill, Kevin – Cognitive Science, 2022
Mike accidentally knocked against a bottle. Seeing that the bottle was about to fall, Jack was just about to catch it when Peter accidentally knocked against him, making Jack unable to catch it. Jack did not grab the bottle, and it fell to the ground and spilled. In double-prevention cases like these, philosophers and nonphilosophers alike tend to…
Descriptors: Evaluative Thinking, Prevention, Logical Thinking, Individual Differences
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Jamie Amemiya; Gail D. Heyman; Caren M. Walker – Cognitive Science, 2024
How do people come to opposite causal judgments about societal problems, such as whether a public health policy reduced COVID-19 cases? The current research tests an understudied cognitive mechanism in which people may agree about what "actually" happened (e.g., that a public health policy was implemented and COVID-19 cases declined),…
Descriptors: Causal Models, Evaluative Thinking, Logical Thinking, Social Problems
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Mayrhofer, Ralf; Waldmann, Michael R. – Cognitive Science, 2016
Research on human causal induction has shown that people have general prior assumptions about causal strength and about how causes interact with the background. We propose that these prior assumptions about the parameters of causal systems do not only manifest themselves in estimations of causal strength or the selection of causes but also when…
Descriptors: Causal Models, Bayesian Statistics, Inferences, Probability
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Rehder, Bob – Cognitive Science, 2017
This article assesses how people reason with categories whose features are related in causal cycles. Whereas models based on causal graphical models (CGMs) have enjoyed success modeling category-based judgments as well as a number of other cognitive phenomena, CGMs are only able to represent causal structures that are acyclic. A number of new…
Descriptors: Abstract Reasoning, Logical Thinking, Causal Models, Graphs
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Rips, Lance J.; Edwards, Brian J. – Cognitive Science, 2013
This article reports results from two studies of how people answer counterfactual questions about simple machines. Participants learned about devices that have a specific configuration of components, and they answered questions of the form "If component X had not operated [failed], would component Y have operated?" The data from these…
Descriptors: Inferences, Logical Thinking, Cognitive Psychology, Causal Models
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Hattori, Masasi; Oaksford, Mike – Cognitive Science, 2007
In this article, 41 models of covariation detection from 2 x 2 contingency tables were evaluated against past data in the literature and against data from new experiments. A new model was also included based on a limiting case of the normative phi-coefficient under an extreme rarity assumption, which has been shown to be an important factor in…
Descriptors: Stimuli, Responses, Computer Simulation, Heuristics