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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http://dx.doi.org/10.1038/s41597-022-01808-2 | DOI Listing |
J Public Health Manag Pract
September 2024
Author Affiliations: Department of Social and Behavioral Sciences (Ms Rushovich and Dr Krieger) and Department of Biostatistics (Dr Nethery), Harvard T.H. Chan School of Public Health, Boston, Massachusetts; and Department of Political Science, Massachusetts Institute of Technology (Dr White), Cambridge, Massachusetts.
Context: Technological innovation and access to big data have allowed partisan gerrymandering to increase dramatically in recent redistricting cycles.
Objective: To understand whether and how partisan gerrymandering, including "packing" and "cracking" (ie, respectively concentrating within or dividing specified social groups across political boundaries), distorts understanding of public health need when health statistics are calculated for congressional districts (CDs).
Design: Cross-sectional study using 2020 CDs and nonpartisan simulated districts.
Proc Natl Acad Sci U S A
June 2023
Department of Government, Harvard University, Cambridge, MA 02138.
Congressional district lines in many US states are drawn by partisan actors, raising concerns about gerrymandering. To separate the partisan effects of redistricting from the effects of other factors including geography and redistricting rules, we compare possible party compositions of the US House under the enacted plan to those under a set of alternative simulated plans that serve as a nonpartisan baseline. We find that partisan gerrymandering is widespread in the 2020 redistricting cycle, but most of the electoral bias it creates cancels at the national level, giving Republicans two additional seats on average.
View Article and Find Full Text PDFSci Data
November 2022
Department of Statistics, Harvard University, Cambridge, USA.
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.
View Article and Find Full Text PDFPhys Rev E
December 2021
Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, Massachusetts 02139, USA.
The space of connected graph partitions underlies statistical models used as evidence in court cases and reform efforts that analyze political districting plans. In response to the demands of redistricting applications, researchers have developed sampling methods that traverse this space, building on techniques developed for statistical physics. In this paper, we study connections between redistricting and statistical physics, and in particular with self-avoiding walks.
View Article and Find Full Text PDFPLoS One
October 2020
Fox School of Business, Temple University, Philadelphia, PA, United States of America.
Political redistricting is the redrawing of electoral district boundaries. It is normally undertaken to reflect population changes. The process can be abused, in what is called gerrymandering, to favor one party or interest group over another, resulting thereby in broadly undemocratic outcomes that misrepresent the views of the voters.
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