Author ORCID Identifier
0009-0009-9640-4483
Defense Date
2025
Document Type
Dissertation
Degree Name
Doctor of Philosophy
Department
Education
First Advisor
Genevieve Siegel-Hawley
Second Advisor
Andrene Castro
Third Advisor
Michael Broda
Fourth Advisor
Margaret Thornton
Abstract
Even after Brown led to the South briefly having the most diverse schools in the nation, schools throughout the Northeast have remained the most segregated in the nation for decades. While federal jurisprudence has made compelling desegregation pursuant to the Equal Protection Clause more challenging, New Jersey has a particularly favorable landscape to address severe segregation. With a highly diverse, densely populated public enrollment, favorable state constitutional precedent, and a history of successfully compelling desegregation, New Jersey is fertile ground exploring regional desegregation. Scholars, judges, and even plaintiffs in ongoing litigation (Latino Action Network v. N.J.) have called for New Jersey to regionally consolidate districts to advance desegregation, but research has not yet explored what regionally consolidated districts might look like, or even how to develop those boundaries. In this dissertation, I develop a redistricting heuristic, SegSwarmEP, which novelly employs an Ant Colony Optimization (ACO) to optimize a combinatorially explosive redistricting problem to examine how New Jersey could regionally desegregate school districts across eight counties with the most segregated districts in the state. After assessing existing segregation, I employ SegSwarmEP to form clusters of existing districts, assessing segregation across three remedial maps compared to existing districts and counties. Compared to existing district boundaries, my heuristic was able to generate remedial maps which reduce interdistrict segregation by as much as 95 percent.
Rights
Creative Commons LIcense Agreement (BY, NC, SA)
Is Part Of
VCU University Archives
Is Part Of
VCU Theses and Dissertations
Date of Submission
12-9-2025