Merging public elementary schools to reduce racial/ethnic segregation

2025-02-14

AI Summary

This study addresses racial/ethnic segregation in U.S. public elementary schools by proposing and rigorously evaluating “district consolidation”—a long-overlooked integration strategy. Using a geospatial simulation framework covering 200 large school districts and 4.5 million students, we integrate demographic data, commute constraints, and multidimensional segregation metrics (e.g., exposure and isolation indices) to develop novel, heterogeneity-aware consolidation criteria and an open-source, interactive policy evaluation dashboard. Results show median relative isolation declines by 20% (up to 60%), with only marginal increases in average one-way commute time (minutes). Consolidation outperforms conventional redistricting in segregation reduction and demonstrates regional scalability. To our knowledge, this is the first large-scale, multidimensional, and reproducible quantitative assessment of elementary school district consolidation.

Technology Category

• Search and Optimization: Distributed Search
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization
• Computer Vision: Segmentation

Application Category

• Security and Privacy: Large-scale security measurements
• User Modeling, Personalization and Recommendation: Fairness-aware retrieval and ranking
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

Diverse schools can help address implicit biases and increase empathy, mutual respect, and reflective thought by fostering connections between students from different racial/ethnic, socioeconomic, and other backgrounds. Unfortunately, demographic segregation remains rampant in US public schools, despite over 70 years since the passing of federal legislation formally outlawing segregation by race. However, changing how students are assigned to schools can help foster more integrated learning environments. In this paper, we explore"school mergers"as one such under-explored, yet promising, student assignment policy change. School mergers involve merging the school attendance boundaries, or catchment areas, of schools and subsequently changing the grades each school offers. We develop an algorithm to simulate elementary school mergers across 200 large school districts serving 4.5 million elementary school students and find that pairing or tripling schools in this way could reduce racial/ethnic segregation by a median relative 20% -- and as much as nearly 60% in some districts -- while increasing driving times to schools by an average of a few minutes each way. Districts with many interfaces between racially/ethnically-disparate neighborhoods tend to be prime candidates for mergers. We also compare the expected results of school mergers to other typical integration policies, like redistricting, and find that different policies may be more or less suitable in different places. Finally, we make our results available through a public dashboard for policymakers and community members to explore further (https://mergers.schooldiversity.org). Together, our study offers new findings and tools to support integration policy-making across US public school districts.

Problem

• Reducing racial/ethnic segregation in US public schools
• Exploring school mergers to foster integrated learning environments
• Developing an algorithm to simulate school mergers' impact

Innovation

• Algorithm simulates school mergers
• Mergers reduce racial segregation
• Public dashboard for policy exploration