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4 changes: 2 additions & 2 deletions content/publication/brockbank2024monster.md
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title = "Without his cookies, he's just a monster: A counterfactual simulation model of social explanation"
date = "2024-05-12"
authors = ["E. Brockbank","M. Govil","J. E Fan","T. Gerstenberg"]
authors = ["E. Brockbank", "J. Yang", "M. Govil","J. E. Fan","T. Gerstenberg"]
publication_types = ["3"]
publication_short = "_Proceedings of the 46th Annual Conference of the Cognitive Science Society_"
publication = "Brockbank, E., Govil, M., Fan, J. E., Gerstenberg, T. (2024). Without his cookies, he's just a monster: A counterfactual simulation model of social explanation. In _Proceedings of the 46th Annual Conference of the Cognitive Science Society_."
publication = "Brockbank, E., Yang, J., Govil, M., Fan, J. E., Gerstenberg, T. (2024). Without his cookies, he's just a monster: A counterfactual simulation model of social explanation. In _Proceedings of the 46th Annual Conference of the Cognitive Science Society_."
abstract = "Everyday reasoning about others involves accounting for why they act the way they do. With many explanations for someone's behavior, how do observers choose the best one? A large body of work in social psychology suggests that people's explanations rely heavily on traits rather than external factors. Recent results have called this into question, arguing that people balance traits, mental states, and situation to make sense of others' actions. How might they achieve this? In the current work, we hypothesize that people rely on counterfactual simulation to weigh different explanations for others' behavior. We propose a computational model of this process that makes concrete predictions about when people will prefer to explain events based on the actor's traits or their situation. We test the predictions of this model in an experimental paradigm in which trait and situation each guide behavior to varying degrees. Our model predicts people's causal judgments well overall but is less accurate for trait explanations than situational explanations. In a comparison with simpler causal heuristics, a majority of participants were better predicted by the counterfactual model. These results point the way toward a more comprehensive understanding of how social reasoning is performed within the context of domain-general causal inference."
image_preview = ""
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6 changes: 3 additions & 3 deletions docs/bibtex/cic_papers.bib
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%% This BibTeX bibliography file was created using BibDesk.
%% https://bibdesk.sourceforge.io/
%% Created for Tobias Gerstenberg at 2024-05-13 09:25:20 +0200
%% Created for Tobias Gerstenberg at 2024-05-14 10:59:36 +0200
%% Saved with string encoding Unicode (UTF-8)
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@inproceedings{brockbank2024monster,
abstract = {Everyday reasoning about others involves accounting for why they act the way they do. With many explanations for someone's behavior, how do observers choose the best one? A large body of work in social psychology suggests that people's explanations rely heavily on traits rather than external factors. Recent results have called this into question, arguing that people balance traits, mental states, and situation to make sense of others' actions. How might they achieve this? In the current work, we hypothesize that people rely on counterfactual simulation to weigh different explanations for others' behavior. We propose a computational model of this process that makes concrete predictions about when people will prefer to explain events based on the actor's traits or their situation. We test the predictions of this model in an experimental paradigm in which trait and situation each guide behavior to varying degrees. Our model predicts people's causal judgments well overall but is less accurate for trait explanations than situational explanations. In a comparison with simpler causal heuristics, a majority of participants were better predicted by the counterfactual model. These results point the way toward a more comprehensive understanding of how social reasoning is performed within the context of domain-general causal inference.},
author = {Brockbank, Erik and Govil, Mishika and Fan, Judith E and Gerstenberg, Tobias},
author = {Brockbank, Erik and and Yang, Justin and Govil, Mishika and Fan, Judith E and Gerstenberg, Tobias},
booktitle = {{Proceedings of the 46th Annual Conference of the Cognitive Science Society}},
date-added = {2024-05-12 17:46:35 +0200},
date-modified = {2024-05-12 17:46:35 +0200},
date-modified = {2024-05-14 10:59:35 +0200},
editor = {Larissa K Samuelson and Stefan Frank and Mariya Toneva and Allyson Mackey and Eliot Hazeltine},
title = {{Without his cookies, he's just a monster: A counterfactual simulation model of social explanation}},
year = {2024}}
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2 changes: 1 addition & 1 deletion docs/member/tobias_gerstenberg/index.html
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Expand Up @@ -443,7 +443,7 @@ <h2 id="publications">Publications</h2>
</div>
<div class="pub-list-item" style="margin-bottom: 1rem" itemscope itemtype="http://schema.org/CreativeWork">
<span itemprop="author">
E. Brockbank, M. Govil, J. E Fan, T. Gerstenberg</span>
E. Brockbank, J. Yang, M. Govil, J. E. Fan, T. Gerstenberg</span>

(2024).

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4 changes: 2 additions & 2 deletions docs/publication/brockbank2024monster/index.html
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<h1 itemprop="name" class ="title-text">Without his cookies, he&#39;s just a monster: A counterfactual simulation model of social explanation</h1>
<p class="pub-authors" itemprop="author">

E. Brockbank, M. Govil, J. E Fan, T. Gerstenberg
E. Brockbank, J. Yang, M. Govil, J. E. Fan, T. Gerstenberg

</p>
<span class="pull-right">
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<div class="col-sm-10">
<div class="row">
<div class="col-xs-12 col-sm-3 pub-row-heading">Publication</div>
<div class="col-xs-12 col-sm-9">Brockbank, E., Govil, M., Fan, J. E., Gerstenberg, T. (2024). Without his cookies, he&rsquo;s just a monster: A counterfactual simulation model of social explanation. In <em>Proceedings of the 46th Annual Conference of the Cognitive Science Society</em>.</div>
<div class="col-xs-12 col-sm-9">Brockbank, E., Yang, J., Govil, M., Fan, J. E., Gerstenberg, T. (2024). Without his cookies, he&rsquo;s just a monster: A counterfactual simulation model of social explanation. In <em>Proceedings of the 46th Annual Conference of the Cognitive Science Society</em>.</div>
</div>
</div>
<div class="col-sm-1"></div>
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2 changes: 1 addition & 1 deletion docs/publication/index.html
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<div class="pub-list-item" style="margin-bottom: 1rem" itemscope itemtype="http://schema.org/CreativeWork">
<span itemprop="author">
E. Brockbank, M. Govil, J. E Fan, T. Gerstenberg</span>
E. Brockbank, J. Yang, M. Govil, J. E. Fan, T. Gerstenberg</span>

(2024).

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6 changes: 3 additions & 3 deletions static/bibtex/cic_papers.bib
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%% This BibTeX bibliography file was created using BibDesk.
%% https://bibdesk.sourceforge.io/
%% Created for Tobias Gerstenberg at 2024-05-13 09:25:20 +0200
%% Created for Tobias Gerstenberg at 2024-05-14 10:59:36 +0200
%% Saved with string encoding Unicode (UTF-8)
Expand Down Expand Up @@ -40,10 +40,10 @@ @inproceedings{keshmirian2024chain

@inproceedings{brockbank2024monster,
abstract = {Everyday reasoning about others involves accounting for why they act the way they do. With many explanations for someone's behavior, how do observers choose the best one? A large body of work in social psychology suggests that people's explanations rely heavily on traits rather than external factors. Recent results have called this into question, arguing that people balance traits, mental states, and situation to make sense of others' actions. How might they achieve this? In the current work, we hypothesize that people rely on counterfactual simulation to weigh different explanations for others' behavior. We propose a computational model of this process that makes concrete predictions about when people will prefer to explain events based on the actor's traits or their situation. We test the predictions of this model in an experimental paradigm in which trait and situation each guide behavior to varying degrees. Our model predicts people's causal judgments well overall but is less accurate for trait explanations than situational explanations. In a comparison with simpler causal heuristics, a majority of participants were better predicted by the counterfactual model. These results point the way toward a more comprehensive understanding of how social reasoning is performed within the context of domain-general causal inference.},
author = {Brockbank, Erik and Govil, Mishika and Fan, Judith E and Gerstenberg, Tobias},
author = {Brockbank, Erik and and Yang, Justin and Govil, Mishika and Fan, Judith E and Gerstenberg, Tobias},
booktitle = {{Proceedings of the 46th Annual Conference of the Cognitive Science Society}},
date-added = {2024-05-12 17:46:35 +0200},
date-modified = {2024-05-12 17:46:35 +0200},
date-modified = {2024-05-14 10:59:35 +0200},
editor = {Larissa K Samuelson and Stefan Frank and Mariya Toneva and Allyson Mackey and Eliot Hazeltine},
title = {{Without his cookies, he's just a monster: A counterfactual simulation model of social explanation}},
year = {2024}}
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