in SF School Districts 

TUCSON, Ariz. — The University of Arizona is joining a major national effort to transform how urban school districts support Black elementary students. Dr. Chris Lukinbeal, Professor of Geography and Director of the GIST Programs at The University of Arizona, is a principal investigator on a new three-year study (2026–2029) titled "From Disparities to Thriving: A Systemic Approach to Disability Identification, Discipline, and Black Student Success." Funded by the Spencer Foundation, the project moves beyond traditional bureaucratic checklists to investigate why racial gaps in special education and school discipline persist. While the study focuses on the San Francisco Unified School District (SFUSD), the University of Arizona’s role is central to understanding the "where" of student success.

Dr. Lukinbeal, a geographer and cartographer, will lead the project’s spatial analysis. His work focuses on "spatial social capital"—the networks, trust, and community resources within neighborhoods and schools that help students thrive. Qualitative work will engage students and parents to visualize their subjective perceptions of thriving, safety, belonging and opportunity. This approach connects a student’s daily spatial activities to broader neighborhood data like housing, demographics, employment, and community assets to see how these environments influence school experiences. "We are reframing racial disparities from a focus on 'deficits' to an asset-based model," the research team noted, highlighting how Lukinbeal’s maps will identify significant clusters of opportunity. By 2029, the team aims to provide schools with interactive "data stories" and maps that combine hard statistics with the lived experiences of families, creating a scalable model for student thriving nationwide

This interdisciplinary team includes:

· Alfredo J. Artiles (Stanford University), who guides the overall research on educational equity.

· Rebecca A. Cruz (Johns Hopkins University), an expert in longitudinal data and school discipline.

· Laticia Errie De Erving and Jenny Jimenez Payne (SFUSD), who lead district-wide initiatives for Black student achievement and special education.

· Allison Firestone (SFUSD) and Laura Wentworth (Stanford), who manage the partnership between researchers and local schools.

· Hari Subramonyam (Stanford University), who specializes in designing human-centered data tools.

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.