Using Data Science for Social Good: Mapping Opportunity Youth

Opportunity youth—individuals aged 16 to 24 who are disconnected from education and employment due to significant barriers—constitute a sizable yet underserved demographic whose marginalization leads to substantial social and economic costs. This paper demonstrates how data science can be harnessed for social good by mapping the distribution of opportunity youth across different regions. We develop an Opportunity Youth Index by integrating fragmented data from sources such as the American Community Survey, the Adoption and Foster Care Analysis and Reporting System, FBI Crime Data, and Bureau of Justice Statistics incarceration reports. Focusing on four key indicators—disconnected youth, youth in foster care, justice-impacted youth, and children with an incarcerated parent—we employ statistical methods and computational techniques to estimate local concentrations of opportunity youth. The resulting index provides insights for policymakers and community organizations, highlighting areas where targeted interventions can make the most impact. This work illustrates the potential of data science to address complex social issues and is presented in an accessible manner to engage a younger audience.