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Simulated redistricting plans for the analysis and evaluation of redistricting in the United States

This article introduces the 50stateSimulations, a collection of simulated congressional districting plans and underlying code developed by the Algorithm-Assisted Redistricting Methodology (ALARM) Project. The 50stateSimulations allow for the evaluation of enacted and other congressional redistrictin...

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Autores principales: McCartan, Cory, Kenny, Christopher T., Simko, Tyler, Garcia, George, Wang, Kevin, Wu, Melissa, Kuriwaki, Shiro, Imai, Kosuke
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9652457/
https://www.ncbi.nlm.nih.gov/pubmed/36369510
http://dx.doi.org/10.1038/s41597-022-01808-2
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author McCartan, Cory
Kenny, Christopher T.
Simko, Tyler
Garcia, George
Wang, Kevin
Wu, Melissa
Kuriwaki, Shiro
Imai, Kosuke
author_facet McCartan, Cory
Kenny, Christopher T.
Simko, Tyler
Garcia, George
Wang, Kevin
Wu, Melissa
Kuriwaki, Shiro
Imai, Kosuke
author_sort McCartan, Cory
collection PubMed
description This article introduces the 50stateSimulations, a collection of simulated congressional districting plans and underlying code developed by the Algorithm-Assisted Redistricting Methodology (ALARM) Project. The 50stateSimulations allow for the evaluation of enacted and other congressional redistricting plans in the United States. While the use of redistricting simulation algorithms has become standard in academic research and court cases, any simulation analysis requires non-trivial efforts to combine multiple data sets, identify state-specific redistricting criteria, implement complex simulation algorithms, and summarize and visualize simulation outputs. We have developed a complete workflow that facilitates this entire process of simulation-based redistricting analysis for the congressional districts of all 50 states. The resulting 50stateSimulations include ensembles of simulated 2020 congressional redistricting plans and necessary replication data. We also provide the underlying code, which serves as a template for customized analyses. All data and code are free and publicly available. This article details the design, creation, and validation of the data.
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spelling pubmed-96524572022-11-15 Simulated redistricting plans for the analysis and evaluation of redistricting in the United States McCartan, Cory Kenny, Christopher T. Simko, Tyler Garcia, George Wang, Kevin Wu, Melissa Kuriwaki, Shiro Imai, Kosuke Sci Data Data Descriptor This article introduces the 50stateSimulations, a collection of simulated congressional districting plans and underlying code developed by the Algorithm-Assisted Redistricting Methodology (ALARM) Project. The 50stateSimulations allow for the evaluation of enacted and other congressional redistricting plans in the United States. While the use of redistricting simulation algorithms has become standard in academic research and court cases, any simulation analysis requires non-trivial efforts to combine multiple data sets, identify state-specific redistricting criteria, implement complex simulation algorithms, and summarize and visualize simulation outputs. We have developed a complete workflow that facilitates this entire process of simulation-based redistricting analysis for the congressional districts of all 50 states. The resulting 50stateSimulations include ensembles of simulated 2020 congressional redistricting plans and necessary replication data. We also provide the underlying code, which serves as a template for customized analyses. All data and code are free and publicly available. This article details the design, creation, and validation of the data. Nature Publishing Group UK 2022-11-11 /pmc/articles/PMC9652457/ /pubmed/36369510 http://dx.doi.org/10.1038/s41597-022-01808-2 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Data Descriptor
McCartan, Cory
Kenny, Christopher T.
Simko, Tyler
Garcia, George
Wang, Kevin
Wu, Melissa
Kuriwaki, Shiro
Imai, Kosuke
Simulated redistricting plans for the analysis and evaluation of redistricting in the United States
title Simulated redistricting plans for the analysis and evaluation of redistricting in the United States
title_full Simulated redistricting plans for the analysis and evaluation of redistricting in the United States
title_fullStr Simulated redistricting plans for the analysis and evaluation of redistricting in the United States
title_full_unstemmed Simulated redistricting plans for the analysis and evaluation of redistricting in the United States
title_short Simulated redistricting plans for the analysis and evaluation of redistricting in the United States
title_sort simulated redistricting plans for the analysis and evaluation of redistricting in the united states
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9652457/
https://www.ncbi.nlm.nih.gov/pubmed/36369510
http://dx.doi.org/10.1038/s41597-022-01808-2
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