Mathematically Quantifying Non-responsiveness of the 2021 Georgia Congressional Districting Plan
Mathematically Quantifying Non-responsiveness of the 2021 Georgia Congressional Districting Plan
复制标题
从数学角度量化 2021 年佐治亚州国会选区计划的无反应性
DOI:
10.1145/3551624.3555300
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发表时间:
2022
期刊:
影响因子:
--
通讯作者:
Herschlag, Gregory Joseph
中科院分区:
文献类型:
--
作者:
Zhao, Zhanzhan;Hettle, Cyrus;Gupta, Swati;Mattingly, Jonathan Christopher;Randall, Dana;Herschlag, Gregory Joseph
To audit political district maps for partisan gerrymandering, one may determine a baseline for the expected distribution of partisan outcomes by sampling an ensemble of maps. One approach to sampling is to use redistricting policy as a guide to precisely codify preferences between maps. Such preferences give rise to a probability distribution on the space of redistricting plans, and Metropolis-Hastings methods allow one to sample ensembles of maps from the specified distribution. Although these approaches have nice theoretical properties and have successfully detected gerrymandering in legal settings, sampling from commonly-used policy-driven distributions is often computationally difficult. As of yet, there is no algorithm that can be used off-the-shelf for checking maps under generic redistricting criteria. In this work, we mitigate the computational challenges in a Metropolized-sampling technique through a parallel tempering method combined with ReCom[11] and, for the first time, validate that such techniques are effective on these problems at the scale of statewide precinct graphs for more policy informed measures. We develop these improvements through the first case study of district plans in Georgia. Our analysis projects that any election in Georgia will reliably elect 9 Republicans and 5 Democrats under the enacted plan. This result is largely fixed even as public opinion shifts toward either party and the partisan outcome of the enacted plan does not respond to the will of the people. Only 0.12% of the ∼ 160K plans in our ensemble were similarly non-responsive.
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DOI:
10.1080/10618600.2020.1739532
发表时间:
2020-05-07
影响因子:
2.4
作者:
Fifield, Benjamin;Higgins, Michael;Tarr, Alexander
通讯作者:
Tarr, Alexander
影响因子:
5.4
作者:
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J. Solomon
影响因子:
1.6
作者:
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通讯作者:
Pegden, Wesley
DOI:
10.1137/21m1418010
发表时间:
2019
期刊:
SIAM J. Appl. Math.
影响因子:
--
作者:
E. Autry;Daniel Carter;G. Herschlag;Zach Hunter;J. Mattingly
通讯作者:
J. Mattingly
DOI:
10.1214/23-aoas1763
发表时间:
2020
期刊:
ArXiv
影响因子:
--
作者:
Cory McCartan;K. Imai
通讯作者:
K. Imai