Gender Disparity in COVID-19 Impacts on Academic Careers: An Agent-Based Model

The gender gap in academia has arguably been widened by the COVID-19 pandemic, but little systemic data exists to quantify this gap, let alone to predict how it will play out in the near future. This study sets out to answer the research questions, “What are the short- and long-term impacts of the COVID-19 pandemic on the gender gap in academia?” and “How effective would institutional policies designed to help faculty during the pandemic be?”. To answer these research questions, we use agent-based modeling (ABM) coupled with secondary data from various sources to develop a simulation of academia before and after the pandemic. Drawing from existing databases, this simulation uses demographic parameters such as gender, partner status, and parent status as determinants of productivity and ultimately, promotion and tenure. Our simulation helps us understand the immediate impacts of COVID-19 on productivity and career trajectories of male and female academics, simulate its long-term impacts on gender (in)equality in academia as a whole in 3, 5, 10, or 20 years, and explore how much institutional interventions such as tenure clock extension, support for dependent care, and holistic wellbeing initiatives would relieve such systemic inequality. This study presents concrete data to institutions and administrators to critically re-examine faculty performance evaluation policies and how they can be improved to minimize systemic inequality.