Unconscious Bias in Job Titles: Implicit Associations Between Four Different Linguistic Forms with Women and Men

Fatfouta, Ramzi; Sczesny, Sabine

doi:10.1007/s11199-023-01411-8

Sex Roles

2023

DOI: 10.1007/s11199-023-01411-8

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Unconscious Bias in Job Titles: Implicit Associations Between Four Different Linguistic Forms with Women and Men

Ramzi Fatfouta,

Sabine Sczesny

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Cited by 2 publications

References 55 publications

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Toward Visibility: Using the Swedish Gender-Inclusive Pronoun Hen Increases Gender Categorization of Androgynous Faces as Nonbinary

van Berlekom,

Sczesny,

Sendén

2024

Journal of Language and Social Psychology

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Nonbinary people face invisibility and misrecognition. This research investigated how the use of the Swedish gender-inclusive neopronoun hen influenced the gender categorization of faces beyond the binary. In a between-subjects design, participants ( N = 368) were instructed to use the gender-inclusive neopronoun hen, the binary masculine pronoun han (he), or no pronoun in a writing task. Then, they categorized androgynous morphed faces by selecting one of four response options (“woman,” “man,” “nonbinary,” or “I don't know”). Altogether, the results indicated that few participants responded “I don't know,” indicating that categorizing gender by appearance is common. As expected, the use of the gender-inclusive pronoun increased nonbinary categorizations, whereas the use of the masculine pronoun did not increase man categorizations, documenting that gender-inclusive pronouns increase the visibility of nonbinary people. Gender binary beliefs were associated with less nonbinary categorization. The discussion outlines how these findings can inform social policymaking.

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Toward Visibility: Using the Swedish Gender-Inclusive Pronoun Hen Increases Gender Categorization of Androgynous Faces as Nonbinary

van Berlekom,

Sczesny,

Sendén

2024

Journal of Language and Social Psychology

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“The Authors” Make Me Think Equally of Women and Men: Exploring Mixed-Gender Representations in a Visual Categorisation Task

Kim,

Öttl,

Gygax

et al. 2023

Open Psychology

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A common goal for gender-fair language policies is to promote terms that elicit balanced activation of gender categories. Expanding previous research on the activation of feminine versus masculine categories through person nouns, we used a word-picture response priming design with gendered human faces as target stimuli, to explore whether a simultaneous activation of more than one gender category can be captured empirically. Focusing on Norwegian (Bokmål), we tested whether reading stereotypical (i.e. role nouns, e.g. “care givers”) and categorical gendered person nouns (i.e. name pairs, e.g. “Elin and Sandra”) facilitates the categorisation of face pairs that match the gender of the designated people. In Experiment 1 (N = 32), gender-specific (feminine or masculine) word primes were tested, before gender-balanced word primes (non-stereotyped role nouns; pairs of a female and a male name) were added in Experiment 2 (N = 39). In both experiments, the visual targets were pairs of faces (two female faces, two male faces, or one male and one female face). Consistent with previous results for English, we found gender-specific priming effects, supporting the notion that gender categories activated by linguistic stimuli may also exert influence outside of language processing. Most importantly, mixed-gender faces were successfully primed by non-stereotypical role nouns providing initial support for the idea of a balanced activation of gender categories.

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Unconscious Bias in Job Titles: Implicit Associations Between Four Different Linguistic Forms with Women and Men

Cited by 2 publications

References 55 publications

Toward Visibility: Using the Swedish Gender-Inclusive Pronoun Hen Increases Gender Categorization of Androgynous Faces as Nonbinary

Toward Visibility: Using the Swedish Gender-Inclusive Pronoun Hen Increases Gender Categorization of Androgynous Faces as Nonbinary

“The Authors” Make Me Think Equally of Women and Men: Exploring Mixed-Gender Representations in a Visual Categorisation Task

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