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Implicit Gender Bias in Linguistic Descriptions for Expected Events: The Cases of the 2016 United States and 2017 United Kingdom Elections

Gender stereotypes influence subjective beliefs about the world, and this is reflected in our use of language. But do gender biases in language transparently reflect subjective beliefs? Or is the process of translating thought to language itself biased? During the 2016 United States (N = 24,863) and...

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Detalles Bibliográficos
Autores principales: von der Malsburg, Titus, Poppels, Till, Levy, Roger P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7197219/
https://www.ncbi.nlm.nih.gov/pubmed/31913768
http://dx.doi.org/10.1177/0956797619890619
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author von der Malsburg, Titus
Poppels, Till
Levy, Roger P.
author_facet von der Malsburg, Titus
Poppels, Till
Levy, Roger P.
author_sort von der Malsburg, Titus
collection PubMed
description Gender stereotypes influence subjective beliefs about the world, and this is reflected in our use of language. But do gender biases in language transparently reflect subjective beliefs? Or is the process of translating thought to language itself biased? During the 2016 United States (N = 24,863) and 2017 United Kingdom (N = 2,609) electoral campaigns, we compared participants’ beliefs about the gender of the next head of government with their use and interpretation of pronouns referring to the next head of government. In the United States, even when the female candidate was expected to win, she pronouns were rarely produced and induced substantial comprehension disruption. In the United Kingdom, where the incumbent female candidate was heavily favored, she pronouns were preferred in production but yielded no comprehension advantage. These and other findings suggest that the language system itself is a source of implicit biases above and beyond previously known biases, such as those measured by the Implicit Association Test.
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spelling pubmed-71972192021-01-08 Implicit Gender Bias in Linguistic Descriptions for Expected Events: The Cases of the 2016 United States and 2017 United Kingdom Elections von der Malsburg, Titus Poppels, Till Levy, Roger P. Psychol Sci Research Articles Gender stereotypes influence subjective beliefs about the world, and this is reflected in our use of language. But do gender biases in language transparently reflect subjective beliefs? Or is the process of translating thought to language itself biased? During the 2016 United States (N = 24,863) and 2017 United Kingdom (N = 2,609) electoral campaigns, we compared participants’ beliefs about the gender of the next head of government with their use and interpretation of pronouns referring to the next head of government. In the United States, even when the female candidate was expected to win, she pronouns were rarely produced and induced substantial comprehension disruption. In the United Kingdom, where the incumbent female candidate was heavily favored, she pronouns were preferred in production but yielded no comprehension advantage. These and other findings suggest that the language system itself is a source of implicit biases above and beyond previously known biases, such as those measured by the Implicit Association Test. SAGE Publications 2020-01-08 2020-02 /pmc/articles/PMC7197219/ /pubmed/31913768 http://dx.doi.org/10.1177/0956797619890619 Text en © The Author(s) 2020 https://creativecommons.org/licenses/by-nc/4.0/ This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Research Articles
von der Malsburg, Titus
Poppels, Till
Levy, Roger P.
Implicit Gender Bias in Linguistic Descriptions for Expected Events: The Cases of the 2016 United States and 2017 United Kingdom Elections
title Implicit Gender Bias in Linguistic Descriptions for Expected Events: The Cases of the 2016 United States and 2017 United Kingdom Elections
title_full Implicit Gender Bias in Linguistic Descriptions for Expected Events: The Cases of the 2016 United States and 2017 United Kingdom Elections
title_fullStr Implicit Gender Bias in Linguistic Descriptions for Expected Events: The Cases of the 2016 United States and 2017 United Kingdom Elections
title_full_unstemmed Implicit Gender Bias in Linguistic Descriptions for Expected Events: The Cases of the 2016 United States and 2017 United Kingdom Elections
title_short Implicit Gender Bias in Linguistic Descriptions for Expected Events: The Cases of the 2016 United States and 2017 United Kingdom Elections
title_sort implicit gender bias in linguistic descriptions for expected events: the cases of the 2016 united states and 2017 united kingdom elections
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7197219/
https://www.ncbi.nlm.nih.gov/pubmed/31913768
http://dx.doi.org/10.1177/0956797619890619
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