Our bright team of students from the Data Sciences Department, University of California, Berkeley took on a project during FALL 2021,

Income inequality has long been a crucial topic that cannot be ignored when we talk about the inequalities faced by PwD of all backgrounds. Inequality within PWD is a highly overlooked topic. Race, gender, and education level are key factors causing income equality within PwoD in United States institutions. However, research has not focused on how these identifying factors affect inequality within PwD.

Disability alone creates barriers for PwD in society, however, the intersection of marginalized identities and disability can increase these barriers. In order to develop an in-depth understanding of the inequalities PwD faces, it is necessary to see how gender, race, and education affect PwD opportunities and income.

Through our research, we have developed models for data collection and analysis. By analyzing and visualizing data, we get a clear overview of income inequality within PwD. By making a comparison of our PwD data with their PwoD counterparts, we are able to see how much impact disability has on individuals of all backgrounds. Drawing conclusions from our data analysis we hope to be able to give meaningful recommendations for policy-makers and change-makers within the disability sector.

Check out the executive summary here