Gender Data for Gender Equality

 Prerequisite Course: SIPAU6500 - Quantitative Analysis I. In recent years, despite enhanced awareness about the magnitude and multifaceted nature of gender inequalities on the one hand, and the promises of the ‘Data Revolution’ on the other hand, critical gaps remain in both data availability and usage to both fully capture the underlying dynamics, drivers and outcomes of gender inequalities, and to promote gender equality. The goal of this course is to train advanced students on the historical and latest discussions, opportunities, challenges, requirements and limitations of leveraging various types of data to fill ‘gender data gaps’ and promote gender equality. It is designed as an intermediate-level course on the issue that touches on its historical, sociopolitical, cultural and economic dimensions, as well as technical and analytical aspects related to data access, reliability, and the political economy and ethics of collecting, analyzing and using data for social change. It fundamentally seeks to ask and partially address the question of whether and how data, including ‘traditional’ data (such as official statistic and quantitively and qualitative survey data) and non-traditional data (such as social media and online data, telecom operators’ data, satellite imagery) can be leveraged concretely to pursue greater gender equality through analysis, advocacy and policy. It will also discuss risks associated with data collection and analysis and digital technologies more broadly including those related to privacy and safety, biases, harassment, and discrimination. In doing so, it will zoom in on a few sensitive themes, including sexual and gender-based violence (SGBV), child marriage and female genital mutilation (FGM), as well as socioeconomic and political empowerment and inclusion, especially although not exclusively in countries and regions of the “Global South” (or “Global Majority”). The curriculum will combine lectures, group discussions, hands-on tutorials, and a group project.