Imperfect Models of the World: Gender Stereotypes and Assumptions in Covid-19 Responses

As the Covid-19 pandemic has unfolded, epidemiologists have been working to build and refine models of how the disease is spread through populations: at the same time, policy-makers around the world have been taking measures to try to stem the transmission of disease, which are based on models of how they think the world works. These models may be implicit, or made explicit including through the use of statistics and data science: frequently, though, they are based on stereotypes and assumptions about how individuals and systems operate. This paper argues that it is crucial to understand to whom models are useful, and who they ignore. This paper looks at the gendered assumptions – and resulting gaps - in policy responses, which betray an understanding of the world that neglects the experiences of women and of trans and non-binary people. It examines how gendered assumptions, gender binaries and stereotypes weaken responses to the pandemic, and how they reinforce imperfect models of the world that have detrimental impacts on the people who are not included.