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Census TopDown: The Impacts of Differential Privacy on Redistricting

Authors :
Cohen, Aloni
Duchin, Moon
Matthews, JN
Suwal, Bhushan
Cohen, Aloni
Duchin, Moon
Matthews, JN
Suwal, Bhushan
Publication Year :
2021

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.

Details

Database :
OAIster
Notes :
application/pdf, English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1260129551
Document Type :
Electronic Resource
Full Text :
https://doi.org/10.4230.LIPIcs.FORC.2021.5