School desegregation by redrawing district boundaries

Schools in the United States remain heavily segregated by race and income. Previous work demonstrates districts can promote group diversity within their schools with policies like redrawing attendance zones. Yet, the promise of such policies in many areas is limited by the fact that most school segregation occurs between school districts, and not between schools in the same district. I adapt Markov Chain Monte Carlo algorithms from legislative redistricting to redraw school district boundaries that decrease segregation while maintaining desirable criteria like distance to school and using only existing school facilities. Focusing on New Jersey, where the segregation of Black and Hispanic students from White and Asian students is among the worst in the country, I demonstrate that redrawing school districts could reduce more than 40% of existing segregation in the median New Jersey county, compared to less than 5% for redrawing attendance zones alone. Finally, I show how my proposed methodology can be applied to as few as two districts to reduce segregation in proposed consolidations, when small districts are merged into a larger district.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2024-09-27
DOI
https://doi.org/10.1038/s41598-024-71578-x
Citations
6
Primary Topic
School Choice and Performance
Type
article
Field-Weighted Citation Impact
12.58
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

School desegregation by redrawing district boundaries

Tyler Simko
6 citations
Scientific Reports
School Choice and Performance
12.58
article

School desegregation by redrawing district boundaries

Tyler Simko
article en
6 citations

Abstract

Schools in the United States remain heavily segregated by race and income. Previous work demonstrates districts can promote group diversity within their schools with policies like redrawing attendance zones. Yet, the promise of such policies in many areas is limited by the fact that most school segregation occurs between school districts, and not between schools in the same district. I adapt Markov Chain Monte Carlo algorithms from legislative redistricting to redraw school district boundaries that decrease segregation while maintaining desirable criteria like distance to school and using only existing school facilities. Focusing on New Jersey, where the segregation of Black and Hispanic students from White and Asian students is among the worst in the country, I demonstrate that redrawing school districts could reduce more than 40% of existing segregation in the median New Jersey county, compared to less than 5% for redrawing attendance zones alone. Finally, I show how my proposed methodology can be applied to as few as two districts to reduce segregation in proposed consolidations, when small districts are merged into a larger district.

Scientific ReportsVol. 14(1)
Princeton University (US)
Reduced inequalities
Openalex Percentile: Top 1%
School Choice and Performance
12.58
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

School desegregation by redrawing district boundaries — Tyler Simko · Scientific Reports (2024) | TGRS Research Map | TGRS