Census TopDown: The Impacts of Differential Privacy on Redistricting

• URL: http://arxiv.org/abs/2203.05085v1
• Date: Wed, 9 Mar 2022 23:28:53 GMT
• Title: Census TopDown: The Impacts of Differential Privacy on Redistricting
• Authors: Aloni Cohen, Moon Duchin, JN Matthews, Bhushan Suwal
• Abstract summary: We consider several key applications of Census data in redistricting. We find reassuring evidence that TopDown will not threaten the ability to produce districts with tolerable population balance.
• Score: 0.3746889836344765
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The 2020 Decennial Census will be released with a new disclosure avoidance system in place, putting differential privacy in the spotlight for a wide range of data users. We consider several key applications of Census data in redistricting, developing tools and demonstrations for practitioners who are concerned about the impacts of this new noising algorithm called TopDown. Based on a close look at reconstructed Texas data, we find reassuring evidence that TopDown will not threaten the ability to produce districts with tolerable population balance or to detect signals of racial polarization for Voting Rights Act enforcement.

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