2019
DOI: 10.1017/s1743923x19000084
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A Feminine Advantage? Delineating the Effects of Feminine Trait and Feminine Issue Messages on Evaluations of Female Candidates

Abstract: Current scholarship offers conflicting conclusions about whether female candidates have a feminine advantage or a disadvantage. Previous work does not consider whether voters respond similarly to all types of messages that might emphasize feminine stereotypes, such as feminine trait and feminine issue messages. I argue that voters will respond differently to trait-based feminine messages relative to issue-based feminine messages. I test the effects of trait-based and issue-based feminine messages through two s… Show more

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Cited by 44 publications
(25 citation statements)
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“…Extant research treats traits and issues as equitable sources of stereotypic information (Herrnson, Lay, and Stokes 2003; Iyengar, Valentino, and Ansolabehere 1996). But recent research suggests that voters interpret feminine traits and feminine issues quite differently (Bauer 2019a). We found that the election year matters for the trait-balancing strategies emphasized by female candidates because traits were relatively rare mentions in the ads of candidates in 2004.…”
Section: Discussionmentioning
confidence: 99%
See 2 more Smart Citations
“…Extant research treats traits and issues as equitable sources of stereotypic information (Herrnson, Lay, and Stokes 2003; Iyengar, Valentino, and Ansolabehere 1996). But recent research suggests that voters interpret feminine traits and feminine issues quite differently (Bauer 2019a). We found that the election year matters for the trait-balancing strategies emphasized by female candidates because traits were relatively rare mentions in the ads of candidates in 2004.…”
Section: Discussionmentioning
confidence: 99%
“…We also might not expect Democratic female candidates to engage in partisan-trait trespassing strategies because experimental research indicates that female candidates, both Democratic and Republican, face a gendered punishment for co-opting traits owned by the opposing political party (Bauer 2019b). This punishment occurs, even for Democratic female candidates, because the gendered trait strategies female candidates adopt are interpreted more strongly through the lens of gender stereotypes rather than the lens of partisan stereotypes (Bauer 2019a). We hypothesize that partisanship will shift trait-balancing strategies such that female candidates will emphasize the gendered traits consistent with their partisanship.…”
Section: A Trait-balancing Approach To Campaign Messagesmentioning
confidence: 99%
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“…This has important implications because facial prominence may have a significant impact on the perception of key personality characteristics of the person portrayed, such as competence and agency (e.g., Schwarz and Kurz, 1989 ), which, in turn, may affect the chances of electoral success. Whereas an association between female politicians and typically masculine issues and domains can be detrimental and trigger backlash against women ( Okimoto and Brescoll, 2010 ; Bauer and Carpinella, 2018 ), strategies aimed at de-emphasizing the possession of feminine traits can enhance women’s likelihood of winning elected offices ( Bauer, 2020 ).…”
Section: Discussionmentioning
confidence: 99%
“…This “notable firsts” coverage for women, in particular, draws attention to the novelty and outlier status of female candidates and reduces policy coverage for female candidates (Turcotte et al 2021), and can lead voters to see these candidates as less qualified for political office or reinforce the status of women as outsiders (Schwindt-Bayer and Reyes-Householder 2017). Important to note is that both women and men can receive feminine stereotypic coverage, but coverage of women’s family roles, as opposed to men’s family roles, can be more damaging because it draws attention to the role incongruity between women, feminine stereotypes, and masculine political leadership roles (Bauer 2019). We assessed the intercoder reliability of our full coding scheme and include that full data in Web Appendix 2.…”
Section: Data Collectionmentioning
confidence: 99%