Replication Data for: Ambivalent Sexism? Shifting Patterns of Gender Bias in Five Arab Countries

  • Jocelyn Sage Mitchell (Creator)
  • Justin D Martin (Creator)
  • Calvert W. Jones (Creator)

Dataset

Description

While institutional support is growing for women in leadership positions across the Arab world, little is known about how rising numbers of women in roles of authority and expertise are being perceived. We examine how general theories of gender bias fit new data from a survey experiment spanning nationally representative samples in five Arab countries. The experiment captured how citizens judge women who adopt the stereotypically masculine role of a “hard-news” journalist. Results challenge conventional wisdom about the prevalence of classic sexism—a generalized antipathy toward women consistent with traditional definitions of prejudice. Instead, we find considerable support for ambivalent sexism, a more nuanced theory positing pro-male (hostile) as well as pro-female (benevolent) biases both detrimental to gender equality and requiring distinctive strategies to address. Although tentative, the findings also make a theoretical contribution suggesting that modernization processes may reverse gender biases, replacing classic patriarchy with so-called benevolent sexism rather than true gender-egalitarianism.
Date made available2022
PublisherHarvard Dataverse

Cite this