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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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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SAGE Publications
2020
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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. |
format | Online Article Text |
id | pubmed-7197219 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
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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