Implicit Gender Bias in Linguistic Descriptions for Expected Events: The Cases of the 2016 United States and 2017 United Kingdom Elections
© The Author(s) 2020. 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 S...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
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SAGE Publications
2021
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| Online Access: | https://hdl.handle.net/1721.1/136270 |
| _version_ | 1826211598375583744 |
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| author | von der Malsburg, Titus Poppels, Till Levy, Roger P |
| author2 | Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences |
| author_facet | Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences von der Malsburg, Titus Poppels, Till Levy, Roger P |
| author_sort | von der Malsburg, Titus |
| collection | MIT |
| description | © The Author(s) 2020. 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. |
| first_indexed | 2024-09-23T15:08:31Z |
| format | Article |
| id | mit-1721.1/136270 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T15:08:31Z |
| publishDate | 2021 |
| publisher | SAGE Publications |
| record_format | dspace |
| spelling | mit-1721.1/1362702023-03-01T20:53:31Z 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 Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences © The Author(s) 2020. 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. 2021-10-27T20:34:38Z 2021-10-27T20:34:38Z 2020 2021-03-23T17:46:36Z Article http://purl.org/eprint/type/JournalArticle https://hdl.handle.net/1721.1/136270 en 10.1177/0956797619890619 Psychological Science Creative Commons Attribution 4.0 International license https://creativecommons.org/licenses/by/4.0/ application/pdf SAGE Publications Sage |
| spellingShingle | 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 |
| url | https://hdl.handle.net/1721.1/136270 |
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