in SF School Districts 

The project utilizes spatial analysis and a Geographic Information Systems (GIS) database to illuminate previously disregarded contextual dimensions of disproportionality in San Francisco Unified School Districts. This involves collecting data—including variables on employment, household income, poverty status, and housing costs from the American Community Survey (ACS), alongside city data on crime and community resources—and aggregating it to school-attendance boundaries. Segregation analysis will be conducted at the neighborhood level using various indices. Geographically weighted regressions and local indicators of spatial association will be employed to assess if neighborhood variables predict disproportionality and to identify where significant clusters of disproportionality, segregation, and associated demographics occur. Crucially, the study addresses the gap left by prior research by focusing on Black families’ assets and collective efficacy within a neighborhood context. Researchers will create a social capital and collective efficacy index for elementary schools and their associated neighborhoods, using ACS, Esri’s Business Analyst, and city data to quantify bridging and bonding social capital. Social capital is defined as the "networks, norms, and trust" that allow participants to pursue shared objectives effectively. A mixed methodology, including interviews, will connect this social capital index to disproportionality data. Parents will be interviewed about the locations of social capital and collective efficacy to facilitate individual activity-space analysis, linking micro- and macro-levels of analysis across schools and neighborhoods. The goal is to use these contextual and spatial data to reframe racial disparities from deficit models to asset-based ones.