Work

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

Year: 2020

Type: article

Abstract: 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 translating thought to language itself biased? During the 2016 US (N=24,863) and 2017 UK (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 US, even when the female candidate was expected to win, ’she’ references were rarely produced and induced substantial comprehension disruption. In the UK, where the incumbent female candidate was heavily favored, ’she’ was preferred in production but yielded no comprehension advantage. These and other findings suggest that the language system itself is as a source of implicit biases next to previously known biases such as those measured by the implicit association test.

Source: Psychological Science

DOI: 10.1177/0956797619890619

Authors: Titus von der Malsburg, Till Poppels, Roger P. Levy

Institutions: University of Potsdam, Massachusetts Institute of Technology, University of California San Diego

Language: English

Topic: Gender Studies in Language

Subfield: Gender Studies

Field: Social Sciences

Domain: Social Sciences

SDGs: Reduced inequalities, Gender equality

Open Access status: hybrid

Estimated APC paid: $3,000