Cohort 2024
Maryland Center on Economic Policy
Examining the Effects of Fines and Fees on Residents with Low Incomes
Baltimore City and Prince George’s County, MD
People are charged fines and fees for “services” at every stage of the criminal legal system. Examples of services these fees pay for include parole and probation, public defender representation, jail room and board, and criminal record expungement. These fees are imposed regardless of a person’s ability to pay, and in Maryland, they can be especially devastating for low-income Black and brown residents. Whereas Black and brown residents make up 29 percent of Maryland’s population, because of systemic and social inequalitiesthey are incarcerated at a much higher rate, making up 71 percent of the prison population. Criminal legal debt has especially severe effects on low-income residents and is a form of racialized wealth extraction. Yet there is no publicly available information that explicitly outlines owed criminal legal debt. The Maryland Center on Economic Policy, a leading advocate for data transparency in Maryland, has experience with Maryland’s criminal legal system and with data dashboards. It now seeks to acquire data on debt resulting from fines and fees and analyze the effects on low-income residents in Baltimore City and Prince George’s County, two of the most affected localities in the state.
With Catalyst Grant funding, the Maryland Center on Economic Policy will partner with the Job Opportunities Task Force to collect and analyze data on criminal legal system fines and fees via publicly available data and public information act requests. With the data the two organizations will conduct an impact analysis to determine how Maryland’s policy and fee structure affects different groups, particularly Black and brown residents. The findings will also be shared with community partners to encourage discussion and policy reform around fines and fees in the criminal legal system. In addition, the organizations will explore the feasibility of developing a data dashboard based on these data.
