Contextual Stochastic Optimization for School Desegregation Policymaking

TL;DR

This paper introduces a novel stochastic optimization framework, RWC, that models school boundary redrawing and student choice to reduce socioeconomic segregation in US schools, demonstrating significant potential for policy application.

Contribution

It develops the first joint redistricting and choice modeling framework integrating machine learning, providing a practical tool for policymakers to reduce school segregation.

Findings

RWC can potentially reduce segregation by 23%.

Significant student reassignments may be necessary to achieve this reduction.

Predicting school choice remains a challenging machine learning problem.

Abstract

Most US school districts draw geographic "attendance zones" to assign children to schools based on their home address, a process that can replicate existing neighborhood racial/ethnic and socioeconomic status (SES) segregation in schools. Redrawing boundaries can reduce segregation, but estimating expected rezoning impacts is often challenging because families can opt-out of their assigned schools. This paper seeks to alleviate this societal problem by developing a joint redistricting and choice modeling framework, called Redistricting with Choices (RWC). The RWC framework is applied to a large US public school district to estimate how redrawing elementary school boundaries might realistically impact levels of socioeconomic segregation. The main methodological contribution of RWC is a contextual stochastic optimization model that aims to minimize district-wide segregation by integrating rezoning constraints with a machine learning-based school choice model. The study finds that RWC yields boundary changes that might reduce segregation by a substantial amount (23%) -- but doing so might require the re-assignment of a large number of students, likely to mitigate re-segregation that choice patterns could exacerbate. The results also reveal that predicting school choice is a challenging machine learning problem. Overall, this study offers a novel practical framework that both academics and policymakers might use to foster more diverse and integrated schools.