Explanatory preferences for complexity matching.

People are adept at generating and evaluating explanations for events around them. But what makes for a satisfying explanation? While some scholars argue that individuals find simple explanations to be more satisfying (Lombrozo, 2007), others argue that complex explanations are preferred (Zemla, et...

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Main Authors: Jonathan B Lim, Daniel M Oppenheimer
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2020-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0230929
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author Jonathan B Lim
Daniel M Oppenheimer
author_facet Jonathan B Lim
Daniel M Oppenheimer
author_sort Jonathan B Lim
collection DOAJ
description People are adept at generating and evaluating explanations for events around them. But what makes for a satisfying explanation? While some scholars argue that individuals find simple explanations to be more satisfying (Lombrozo, 2007), others argue that complex explanations are preferred (Zemla, et al. 2017). Uniting these perspectives, we posit that people believe a satisfying explanation should be as complex as the event being explained-what we term the complexity matching hypothesis. Thus, individuals will prefer simple explanations for simple events, and complex explanations for complex events. Four studies provide robust evidence for the complexity-matching hypothesis. In studies 1-3, participants read scenarios and then predicted the complexity of a satisfying explanation (Study 1), generated an explanation themselves (Study 2), and evaluated explanations (Study 3). Lastly, in Study 4, we explored a different manipulation of complexity to demonstrate robustness across paradigms. We end with a discussion of mechanisms that might underlie this preference-matching phenomenon.
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spelling doaj.art-7d3a12791991470881bd2e38358f949c2022-12-21T22:36:54ZengPublic Library of Science (PLoS)PLoS ONE1932-62032020-01-01154e023092910.1371/journal.pone.0230929Explanatory preferences for complexity matching.Jonathan B LimDaniel M OppenheimerPeople are adept at generating and evaluating explanations for events around them. But what makes for a satisfying explanation? While some scholars argue that individuals find simple explanations to be more satisfying (Lombrozo, 2007), others argue that complex explanations are preferred (Zemla, et al. 2017). Uniting these perspectives, we posit that people believe a satisfying explanation should be as complex as the event being explained-what we term the complexity matching hypothesis. Thus, individuals will prefer simple explanations for simple events, and complex explanations for complex events. Four studies provide robust evidence for the complexity-matching hypothesis. In studies 1-3, participants read scenarios and then predicted the complexity of a satisfying explanation (Study 1), generated an explanation themselves (Study 2), and evaluated explanations (Study 3). Lastly, in Study 4, we explored a different manipulation of complexity to demonstrate robustness across paradigms. We end with a discussion of mechanisms that might underlie this preference-matching phenomenon.https://doi.org/10.1371/journal.pone.0230929
spellingShingle Jonathan B Lim
Daniel M Oppenheimer
Explanatory preferences for complexity matching.
PLoS ONE
title Explanatory preferences for complexity matching.
title_full Explanatory preferences for complexity matching.
title_fullStr Explanatory preferences for complexity matching.
title_full_unstemmed Explanatory preferences for complexity matching.
title_short Explanatory preferences for complexity matching.
title_sort explanatory preferences for complexity matching
url https://doi.org/10.1371/journal.pone.0230929
work_keys_str_mv AT jonathanblim explanatorypreferencesforcomplexitymatching
AT danielmoppenheimer explanatorypreferencesforcomplexitymatching