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Women are greatly underrepresented in positions of political leadership around the world. In seeking to explain this underrepresentation, some researchers have pointed to people's tendencies to stereotype leaders as more similar to men than women as these tendencies can support the belief that women are unsuited to leadership. This project aimed to test whether a subtle linguistic intervention was able to ameliorate this gender bias in political leadership stereotypes across different languages and national contexts (country/region N = 42, language N = 30, sample N = 22,996). Specifically, this project examined whether gender-fair language (e.g., the use of paired pronouns ‘he or she’) can reduce the tendency for people to stereotype political leaders as more similar to men than women. To increase the rigor with which these stereotypes were measured, this project complemented the dominant ‘cheap talk’ measure of personal stereotype content with an incentivised community measure of this content. As expected, participants stereotyped political leaders as more similar to men than women; this pattern was stronger on the incentivised measure of community stereotypes. Unexpectedly, there was no evidence that paired pronouns reduced this bias (there was weak exploratory evidence that paired nouns increased participants' tendencies to stereotype political leaders as more similar to women). This project suggests that the ability of gender-fair language interventions to ameliorate gender bias in the political leadership domain may be limited.
Think political leader — think he or she? A multi-country test of a gender-fair language intervention to reduce gendered leadership stereotypes / Peters, K., Jeftić, A., Ballard, T., Zhou, S., Steffens, N.K., Inceoglu, I., Ryan, M.K., Bongiorno, R., Eagly, A., Arriaga, P., Espinosa, A., Aczel, B., Adetula, A., Aglioti, S.M., Akca, E., Akman Direkçi, E., Alizadeh, Z., Alonso-Arbiol, I., Amru, M.F., Andre, J., et al.. - In: THE LEADERSHIP QUARTERLY. - ISSN 1048-9843. - 2026, 37:(2026), p. 101991. [10.1016/j.leaqua.2026.101991]
Think political leader — think he or she? A multi-country test of a gender-fair language intervention to reduce gendered leadership stereotypes
Women are greatly underrepresented in positions of political leadership around the world. In seeking to explain this underrepresentation, some researchers have pointed to people's tendencies to stereotype leaders as more similar to men than women as these tendencies can support the belief that women are unsuited to leadership. This project aimed to test whether a subtle linguistic intervention was able to ameliorate this gender bias in political leadership stereotypes across different languages and national contexts (country/region N = 42, language N = 30, sample N = 22,996). Specifically, this project examined whether gender-fair language (e.g., the use of paired pronouns ‘he or she’) can reduce the tendency for people to stereotype political leaders as more similar to men than women. To increase the rigor with which these stereotypes were measured, this project complemented the dominant ‘cheap talk’ measure of personal stereotype content with an incentivised community measure of this content. As expected, participants stereotyped political leaders as more similar to men than women; this pattern was stronger on the incentivised measure of community stereotypes. Unexpectedly, there was no evidence that paired pronouns reduced this bias (there was weak exploratory evidence that paired nouns increased participants' tendencies to stereotype political leaders as more similar to women). This project suggests that the ability of gender-fair language interventions to ameliorate gender bias in the political leadership domain may be limited.
Think political leader — think he or she? A multi-country test of a gender-fair language intervention to reduce gendered leadership stereotypes / Peters, K., Jeftić, A., Ballard, T., Zhou, S., Steffens, N.K., Inceoglu, I., Ryan, M.K., Bongiorno, R., Eagly, A., Arriaga, P., Espinosa, A., Aczel, B., Adetula, A., Aglioti, S.M., Akca, E., Akman Direkçi, E., Alizadeh, Z., Alonso-Arbiol, I., Amru, M.F., Andre, J., et al.. - In: THE LEADERSHIP QUARTERLY. - ISSN 1048-9843. - 2026, 37:(2026), p. 101991. [10.1016/j.leaqua.2026.101991]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/502590
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simulazione ASN
Il report seguente simula gli indicatori relativi alla propria produzione scientifica in relazione alle soglie ASN 2023-2025 del proprio SC/SSD. Si ricorda che il superamento dei valori soglia (almeno 2 su 3) è requisito necessario ma non sufficiente al conseguimento dell'abilitazione. La simulazione si basa sui dati IRIS e sugli indicatori bibliometrici alla data indicata e non tiene conto di eventuali periodi di congedo obbligatorio, che in sede di domanda ASN danno diritto a incrementi percentuali dei valori. La simulazione può differire dall'esito di un’eventuale domanda ASN sia per errori di catalogazione e/o dati mancanti in IRIS, sia per la variabilità dei dati bibliometrici nel tempo. Si consideri che Anvur calcola i valori degli indicatori all'ultima data utile per la presentazione delle domande.
La presente simulazione è stata realizzata sulla base delle specifiche raccolte sul tavolo ER del Focus Group IRIS coordinato dall’Università di Modena e Reggio Emilia e delle regole riportate nel DM 589/2018 e allegata Tabella A. Cineca, l’Università di Modena e Reggio Emilia e il Focus Group IRIS non si assumono alcuna responsabilità in merito all’uso che il diretto interessato o terzi faranno della simulazione. Si specifica inoltre che la simulazione contiene calcoli effettuati con dati e algoritmi di pubblico dominio e deve quindi essere considerata come un mero ausilio al calcolo svolgibile manualmente o con strumenti equivalenti.