Temporal Inequality in the Gig Economy: How Immigrant Generation, Gender, and Algorithmic Management Shape Time Poverty

This study investigates how temporal inequality and autonomy manifest for first- and second-generation immigrant workers in platform economies, focusing on unincorporated self-employment. Employing a mixed-methods approach that integrates quantitative data from the American Time Use Survey (ATUS) with 96 in-depth interviews, this research examines how migration status, algorithmic management, and gender norms shape workers’ control over their time. The findings reveal substantial temporal disparities between first- and second-generation immigrants. First-generation workers in unincorporated self-employment, experience severe time poverty, driven by fragmented work schedules, unpaid waiting periods, and caregiving responsibilities. In contrast, second-generation immigrants report lower levels of time poverty, prioritizing personal well-being and exercising greater temporal autonomy in navigating the gig economy. Drawing on Wajcman’s (2020) theory of temporal inequality and Cottom’s (2020) racial capitalism, this study argues that platform economies intensify temporal exploitation through algorithmic management, disproportionately affecting racialized Latino immigrant workers. This research contributes to the literature by theorizing how temporal exploitation intersects with race, gender, and migration status, demonstrating that platform labor reinforces, rather than mitigates, existing inequalities. These findings highlight the critical need to examine how time is commodified and controlled in the gig economy, especially for marginalized immigrant workers on the periphery of the labor market.