Implicit occupational gender stereotypes in India: A skills-based empirical analysis using multiple IATs

Abstract

The study investigates Occupational Gender Stereotypes (OGS) in India, where women's representation in high skill occupations remains limited despite economic growth. To assess implicit biases, we developed six Occupational Gender IATs (OGIATs) covering 84 occupations, classified using India's National Classification of Occupations (NCO) aligned with ILO standards. 642 participants from the general population completed implicit and explicit measures, such as a Social Role Questionnaire. Results revealed strong implicit associations linking males to high skill occupations (e.g., medical technicians, aircraft controllers) and females to low skill occupations. Men exhibited significantly stronger implicit biases than women, while education level had no effect, indicating that such biases persist regardless of academic attainment. In contrast, explicit measures showed weaker associations, underscoring the gap between conscious beliefs and unconscious bias. These findings highlight the complexity of gender bias in India's labor market and the need for multidimensional assessments. The OGIATs developed offer a robust tool for future research and policy interventions aimed at reducing gender-based disparities in employment and workforce inclusion.