Neo-Traditionalism, One or Many? Structure of Gender Roles at Individual and Country Levels

Tuesday, July 15, 2014: 10:45 AM
Room: Harbor Lounge A
Oral Presentation
Marharyta FABRYKANT , National Research University, Russia
Transformation of gender roles is regarded as one of the key dimensions of modernization. Notions of gender, as hardly any other set of beliefs, possess universal relevance and pervade everyday life. Not surprisingly, the gender issue has become one of the key themes in rhetoric and sources of mass mobilization for neo-traditionalism. As a result of the polarization of positions in global public debate, most gender role expectations are easily recognized as belonging to either a liberal or a neo-traditionalist value set. What remains less clear, however, is the variability of modernization patterns for different gender norms. Do all role expectations form a one-dimensional factor, or are there several autonomous dimensions of notions about gender, each with its own liberal versus neo-traditionalist extremes? Can the same dimensions be used to compare gender role expectations at individual and country levels? To answer these questions, we analyzed the integrated database of the European Values Survey and World Values Survey by means of multilevel structural equations modeling. The formulations of relevant items, as well as the current theoretical agenda, suggested their possible division of gender roles into those describing behavior in work and family settings. The results, however, revealed a division along different lines: the first factor comprises duties, both in public and private spheres, while the second factor includes hedonist gender role expectations, related to self-fulfillment and enjoyment. At the country level, the first factor proved to be non-existent, while the second was reproduced with almost the same structure as at the individual level. Thus, gender roles are both horizontally and vertically differentiated, and form different dimensions of neo-traditionalism. To account for these differences, we compare sets of predictors for the two factors, with special regard to cross-level interactions.