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Exploring Tradeoffs in Automated School Redistricting: Computational and Ethical Perspectives

AAAI 2023 · Learning theory and algorithms › Prediction and decision losses · approach: Adaptive testing and experiments · 2 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use RecomChain rather than SPATIALAutomated school redistricting · School District A and B, all school levelsRER (%): 56.53 -> 60.43; 81.17 -> 82.08; 80.43 -> 81.16; 59.24 -> 61.18; 84.56 -> 85.25; 86.47 -> 86.53Helped
Use RecomChain rather than SPATIALAutomated school redistricting · School District A, elementary schoolsBAL (%): 86.56 -> 88.05Helped
Use RecomChain rather than SPATIALAutomated school redistricting · School District A, middle and high schoolsBAL (%): 92.71 -> 92.67; 97.42 -> 97.36No clear effect
Use RecomChain rather than SPATIALAutomated school redistricting · School District B, all school levelsBAL (%): 90.85 -> 94.25; 91.68 -> 92.20; 91.47 -> 92.47Helped
Replace Polsby-Popper with retained edge ratio in the compactness objective (ablation)SPATIAL · School District B, elementary, middle, and high schoolscomputational time (minute/run): 443.80; 228.67; 119.31 (Polsby-Popper) -> 102.66; 50.07; 65.04 (Retained Edge Ratio)Helped
Replace Polsby-Popper with retained edge ratio in the compactness objective (ablation)FlipChain and RecomChain · School District B, all school levelscomputational time (minute/run): +20.51% efficiency enhancementHelped
Use recombination transitions instead of single-node flips (ablation)MCMC redistricting framework · School District A and B, all school levelsRER (%): 58.80 -> 60.43; 80.19 -> 82.08; 79.52 -> 81.16; 59.50 -> 61.18; 83.71 -> 85.25; 85.37 -> 86.53Helped
Increase balance-objective weight α (ablation)Redistricting objective · School District B, all school levelsretained student ratioHurt
Increase balance-objective weight α (ablation)Redistricting objective · School District B, all school levelsstudent diversityNo clear effect
Optimize balance and student diversity without optimizing compactness (ablation)FlipChain · School District B, all school levelsboundary compactnessHurt
Use recombination transitions instead of single-node flips (ablation)MCMC redistricting framework · School District B, middle and high schoolsretained student ratioHurt

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