Replication Data for: "Gender Stereotypes Across Electoral Contexts"

Abstract: We examine how the office a candidate seeks influences their use of feminine stereotypes in campaign messaging, focusing on the interplay between government branches (legislative and executive) and jurisdictions (local, state, and federal). We argue that when a particular office is seen as more feminine, such as school boards or city councils, women candidates will perceive a strategic opportunity to emphasize feminine traits to showcase their qualifications for that office. Women candidates will be more likely to perceive and leverage these strategic opportunities relative to men because of the congruence between being a woman and feminine stereotypes. Drawing on an exhaustive and novel dataset of about 49,000 televised campaign ads from the 2012 to 2020 election cycles, we analyze candidates' strategic use of masculine and feminine traits across local, state, and federal legislative and executive offices. Contrary to our initial expectations, our findings suggest that women candidates do not significantly tailor their use of feminine stereotypes to match the perceived femininity of the office they seek. We find that women and men are more likely to use masculine traits over feminine traits across all offices. We also find that women appear to employ a dual stereotype strategy across offices with a higher likelihood than men of emphasizing both feminine and masculine traits in strategic messages. The results from the analyses of our novel campaign data contribute to an understanding of how candidates strategically emphasize feminine characteristics across contexts, and how scholars consider the gendered dimensions of political offices. Replication code will be available on Dataverse here: https://dataverse.harvard.edu/dataverse/polbehavior. Note that the data we use from the Wesleyan Media Project prohibits us from posting the raw data online. Others can obtain the data we use here: https://mediaproject.wesleyan.edu/dataaccess/. Our raw data file is therefore not publicly posted. Any scholar who purchases the WMP data and signs their contract can email Nichole Bauer, [e-mail], for our replication data.