Model output visualisation code from Agent-based models of the cultural evolution of occupational gender roles

The causes of sex differences in human behaviour are contested, with ‘evolutionary’ and ‘social’ explanations often being pitted against each other in the literature. Recent work showing positive correlations between indices of gender equality and the size of sex differences in behaviour has been argued to show support for ‘evolutionary’ over ‘social’ approaches. This argument, however, neglects the potential for social learning to generate arbitrary gender segregation. In the current paper we simulate, using agent-based models, a population where agents exist as one of two ‘types’ and can use social information about which types of agents are performing which ‘roles’ within their environment. We find that agents self-segregate into different roles even where real differences in performance do not exist, if there is a common belief (modelled as priors) that group differences may exist in ‘innate’ competence. Facilitating role changes such that agents should move without cost to the predicted highest-rewards for their skills (i.e. fluidity of the labour market) reduced segregation, while forcing extended exploration of different roles eradicated gender segregation. These models are interpreted in terms of bio-cultural evolution, and the impact of social learning on the expression of gender roles.