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

Nuno Mota, Negar Mohammadi, Palash Dey, Krishna P. Gummadi, Abhijnan Chakraborty

2021Year
8Citations
3Top-tier citations

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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