The influence of gender-ethnic intersectionality on gender stereotypes about IT skills and knowledge

One line of investigation in attempting to better understand the gender imbalance in the information technology (IT) field is to examine gender stereotypes about the skills and knowledge in the IT profession. A survey of 4046 university students in the United States was conducted to examine gender stereotypes held by contemporary university students (White, Black and Latino men and women) about the skills and knowledge in the IT profession. The Individual Differences Theory of Gender and IT was used as the motivating theory for this study because it enabled the incorporation of gender-ethnic intersectionality in the research design. The results revealed that while gender stereotypes about the skills and knowledge involved in the IT profession do exist, they are not uniform across all members of a gender group. The men tended to rate all of the skills as more masculine than did the women respondents. Technical skills were more consistently stereotyped by both men and women in each of the gender-ethnic groups than were nontechnical skills. However, gender stereotypes about nontechnical skills were more contested and revealed both within-gender and within-ethnicity variation. The women students’ rating of nontechnical skills as less masculine than the men suggests that these nontechnical skills are being incorporated into the women’s sense of gender identity. These results show that gender-ethnic intersectionality provides one important explanation for within-gender variation in gender stereotypes that are held by contemporary university students. These findings suggest promising avenues for interventions to address not only the masculine gender stereotyping of skills in the IT profession, but also differential gender stereotyping of technical vs. nontechnical skills and variation in gender stereotyping by the intersectionality of gender-ethnic groups.

The influence of gender-ethnic intersectionality on gender stereotypes about IT skills and knowledge

  • Author Trauth, Eileen M.; Cain, Curtis C.; Joshi, K.D.; Kvasny, Lynette; Booth, Kayla M.
  • Publication Title SIGMIS Database
  • Publication Year 2016
  • BPC Focus Gender, Underrepresented Racial/Ethnic Groups, Black/African American Students, Latinx/Hispanic
  • Methodology Survey, Multi-institution
  • Analytic Method ANOVA
  • Institution Type Minority Serving Institutions, Historically Black Colleges, Universities/Predominantly Black Institutions, Hispanic Serving Institutions
  • DOI 10.1145/2980783.2980785
  • URL https://doi.org/10.1145/2980783.2980785