Causal Judgment in the Wild: Evidence from the 2020 U.S. Presidential Election

Quillien, Tadeg; Barlev, Michael

doi:10.1111/cogs.13101

Cited by 7 publications

(14 citation statements)

References 65 publications

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“…In particular, while we focused on situations where all causal links are direct, people often have to make judgments about causal chains (of the form A → B → C , see Johnson & Ahn, 2015; Lagnado & Channon, 2008; Nagel & Stephan, 2016). With the exception of Quillien and Barlev (2022), we also looked exclusively at causal structures where there is no potential confounding between variables (i.e., variables upstream of the outcome variable are statistically independent from each other). In such causal structures, the CESM is particularly simple because it predicts that the causal strength of C for E is simply the correlation between C and E across counterfactuals.…”

Section: Discussionmentioning

confidence: 99%

“…We focus on these two theories because (a) they fit naturally within the counterfactual framework we use here, (b) they make quantitative predictions, and (c) they have been particularly successful at predicting people’s causal judgments across a wide range of tasks (Gerstenberg & Icard, 2020; Gill et al, 2022; Henne et al, 2019; Henne, Kulesza, et al, 2021; Kirfel et al, 2021; Morris et al, 2019; O’Neill et al, 2021; Quillien & Barlev, 2022). We discuss other theories of causal judgment in the General Discussion section.…”

Section: The Problem Of Causal Selectionmentioning

confidence: 99%

“…We selected studies on causal judgment that had a sufficient number of observations to allow a meaningful measure of model fit. These studies collectively cover a wide range of manipulations, stimuli, and dependent variables (Lagnado et al, 2013;Morris et al, 2019;O'Neill et al, 2021;Quillien & Barlev, 2022;Zultan et al, 2012).…”

Section: Reanalysis Of Existing Datamentioning

confidence: 99%

“… Note . The two panels for Quillien and Barlev (2022) correspond to the same human data, but with computational models calibrated with two different election forecasts (see original reference for details). CESM = counterfactual effect size model; NSM = necessity–sufficiency model.…”

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confidence: 99%

“…The accident was contingent on the fact that both drivers crossed the intersection, that neither driver had been delayed in traffic earlier, that someone invented the automobile, and so on. Of course, people spontaneously say that the driver crossing at the red light caused the accident-just like they say that the victory in the swing state caused the presidential candidate's success or that the last-second shot caused the basketball team's victory (Alicke et al, 2011;Henne, Kulesza, et al, 2021;Knobe & Fraser, 2008;Quillien & Barlev, 2022).…”

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confidence: 99%

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Counterfactuals and the logic of causal selection.

Quillien¹,

Lucas²

2024

Psychological Review

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Everything that happens has a multitude of causes, but people make causal judgments effortlessly. How do people select one particular cause (e.g., the lightning bolt that set the forest ablaze) out of the set of factors that contributed to the event (the oxygen in the air, the dry weather … )? Cognitive scientists have suggested that people make causal judgments about an event by simulating alternative ways things could have happened. We argue that this counterfactual theory explains many features of human causal intuitions, given two simple assumptions. First, people tend to imagine counterfactual possibilities that are both a priori likely and similar to what actually happened. Second, people judge that a factor C caused effect E if C and E are highly correlated across these counterfactual possibilities. In a reanalysis of existing empirical data, and a set of new experiments, we find that this theory uniquely accounts for people's causal intuitions.

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Section: Discussionmentioning

confidence: 99%

Section: The Problem Of Causal Selectionmentioning

confidence: 99%

Section: Reanalysis Of Existing Datamentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Counterfactuals and the logic of causal selection.

Quillien¹,

Lucas²

2024

Psychological Review

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Graded causation and moral responsibility

Hoffmann-Kolss,

Rolffs

2024

Erkenn

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Theories of graded causation attract growing attention in the philosophical debate on causation. An important field of application is the controversial relationship between causation and moral responsibility. However, it is still unclear how exactly the notion of graded causation should be understood in the context of moral responsibility. One question is whether we should endorse a proportionality principle, according to which the degree of an agent’s moral responsibility is proportionate to their degree of causal contribution. A second question is whether a theory of graded causation should measure closeness to necessity or closeness to sufficiency. In this paper, we argue that we should indeed endorse a proportionality principle and that this principle supports a notion of graded causation relying on closeness to sufficiency rather than closeness to necessity. Furthermore, we argue that this insight helps to provide a plausible analysis of the so-called ‘Moral Difference Puzzle’ recently described by Bernstein.

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