research-article

Fair Partitioning of Public Resources: Redrawing District Boundary to Minimize Spatial Inequality in School Funding

Authors:

Negar Mohammadi,

Krishna P. Gummadi,

Abhijnan ChakrabortyAuthors Info & Claims

WWW '21: Proceedings of the Web Conference 2021

Pages 646 - 657

https://doi.org/10.1145/3442381.3450041

Published: 03 June 2021 Publication History

Abstract

Public schools in the United States offer tuition-free primary and secondary education to their students, and are divided into school districts funded by the local and state governments. Although the primary source of school district revenue is public money, several studies have pointed to the inequality in funding across different school districts. In this paper, we focus on the spatial geometry/distribution of such inequality, i.e., how the highly funded and lesser funded school districts are located relative to each other. Due to the major reliance on local property taxes for school funding, we find existing school district boundaries promoting financial segregation, with highly-funded school districts surrounded by lesser-funded districts and vice-versa.

To counter such issues, we formally propose the Fair Partitioning problem to divide a given set of schools into k districts such that the spatial inequality in the district-level funding is minimized. However, the Fair Partitioning problem turns out to be computationally challenging, and we formally show that it is strongly -complete. We further provide a greedy algorithm to offer practical solution to Fair Partitioning, and show its effectiveness in lowering spatial inequality in school district funding across different states in the United States.

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Cited By

Gillani NBeeferman DVega-Pourheydarian COverney CVan Hentenryck PRoy D(2023)Redrawing Attendance Boundaries to Promote Racial and Ethnic Diversity in Elementary SchoolsEducational Researcher10.3102/0013189X23117085852:6(348-364)Online publication date: 15-May-2023
https://doi.org/10.3102/0013189X231170858
Singh DDas SChakraborty A(2023)FairAssign: Stochastically Fair Driver Assignment in Gig Delivery PlatformsProceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency10.1145/3593013.3594040(753-763)Online publication date: 12-Jun-2023
https://dl.acm.org/doi/10.1145/3593013.3594040

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cover image ACM Conferences

WWW '21: Proceedings of the Web Conference 2021

April 2021

4054 pages

ISBN:9781450383127

DOI:10.1145/3442381

Editors:
Jure Leskovec
Stanford
,
Marko Grobelnik
Jožef Stefan Institute
,
Marc Najork
Google
,
Jie Tang
Tsinghua University
,
Leila Zia
Wikimedia Foundation

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Published: 03 June 2021

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Cited By

Gillani NBeeferman DVega-Pourheydarian COverney CVan Hentenryck PRoy D(2023)Redrawing Attendance Boundaries to Promote Racial and Ethnic Diversity in Elementary SchoolsEducational Researcher10.3102/0013189X23117085852:6(348-364)Online publication date: 15-May-2023
https://doi.org/10.3102/0013189X231170858
Singh DDas SChakraborty A(2023)FairAssign: Stochastically Fair Driver Assignment in Gig Delivery PlatformsProceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency10.1145/3593013.3594040(753-763)Online publication date: 12-Jun-2023
https://dl.acm.org/doi/10.1145/3593013.3594040

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