Lady, Girl, Female, or Woman: Sexism and Cognitive Busyness Predict Use of Gender-Biased Nouns
Abstract
Two studies investigated whether modern sexism predicts men’s use of gender-biased terms for women. When established norms suggest a preference for neutral terms (e.g., woman, female), men lower in sexism should avoid potentially biased terms (e.g., lady, girl). Adhering to such an established norm, however, may require conscious effort. In Study 1, men lower in modern sexism used fewer gender-biased terms in a written format than did men higher in modern sexism. Study 2 replicated this result using an oral format but only when men were not cognitively busy with another task. Cognitive busyness apparently interfered with low modern sexists’ efforts to use more neutral terms. Implications for other forms of gender-biased language, as well as for long-term change in the use of gender-biased language, are discussed.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In Cralley and Ruscher (2005), when cognitive load was increased, no differences between high-sexism and low-sexism individuals were observed.
“However, when cognitive load was increased, no differences between high-sexism and low-sexism individuals were observed.”
From What affects people’s use of and attitudes toward gender-inclusive language? A literature review (2025) · cites this paper as Cralley and Ruscher (2005)
In Cralley and Ruscher (2005), men with higher sexism scores used more sexist terms than those with lower sexism in both written and spoken descriptions.
“In both written and spoken descriptions, men with higher sexism scores used more sexist terms (e.g., girl or babe) than those with lower sexism.”
From What affects people’s use of and attitudes toward gender-inclusive language? A literature review (2025) · cites this paper as Cralley and Ruscher (2005)
Individuals with stronger sexist attitudes use more gender-biased words.
“use more gender-biased words (Cralley & Ruscher, 2005)”
From A Sexist Language? Gender Differences in Attitudes and Use of Gender-Inclusive Pronouns (2025) · cites this paper as Cralley & Ruscher, 2005
Cited by
Sorted by citations
What affects people’s use of and attitudes toward gender-inclusive language? A literature review
Lange, E., & von Stockhausen, L. (2025) · Frontiers in Psychology · doi:10.3389/fpsyg.2025.1657753 · Cited by 5 · see citing works
A Sexist Language? Gender Differences in Attitudes and Use of Gender-Inclusive Pronouns
Remsö, A., Bäck, H., & Renström, E. A. (2025) · Journal of Language and Social Psychology · doi:10.1177/0261927x251335305 · Cited by 3 · see citing works
- Authors
- Cralley, E. L., & Ruscher, J. B.
- Affiliations
- Tulane University (US)
- Corresponding author
- Ruscher, Janet B.
- ORCID
- Ruscher, Janet B.
- Venue
- Journal of Language and Social Psychology
- Publisher
- SAGE Publications
- Published
- 2005-09
- Volume
- 24
- Issue
- 3
- Pages
- 300-314
- ISSN
- 0261-927X (ISSN-L)
- 1552-6526
- OpenAlex
- W1985288202
- Cited by
- 41
- References
- 0
- Citations by year
- 2025: 2 · 2024: 2 · 2022: 3 · 2021: 3 · 2020: 1 · 2019: 1 · 2018: 1 · 2017: 2 · 2016: 2 · 2015: 4 · 2014: 6 · 2013: 3 · 2012: 5
- FWCI
- 1.58
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Language and Social Psychology (publishedVersion)
- Topics
- Social Sciences › Gender Studies › Gender Studies in Language
- Social Sciences › Sociology and Political Science › Social and Intergroup Psychology
- Social Sciences › Gender Studies › Gender and Feminist Studies
- Keywords
- modern sexism, gender-neutral language, address terms, cognitive load, gender norms
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
