May 6, 2021
By Sara Zaske, WSU News
PULLMAN, Wash. With state legislatures nationwide preparing for the once-a-decade redrawing of voting districts, a research team has developed a better computational method to help identify improper gerrymandering designed to favor specific candidates or political parties.
In an article in the Harvard Data Science Review, the researchers describe the improved mathematical methodology of an open source tool called GerryChain. The tool can help observers detect gerrymandering in a voting district plan by creating a pool, or ensemble, of alternate maps that also meet legal voting criteria. This map ensemble can show if the proposed plan is an extreme outlier one that is very unusual from the norm of plans generated without bias, and therefore, likely to be drawn with partisan goals in mind.
Open-source mathematical tool detects gerrymandering theiet.org - get the latest breaking news, showbiz & celebrity photos, sport news & rumours, viral videos and top stories from theiet.org Daily Mail and Mail on Sunday newspapers.
May 06, 2021
To help ensure voting districts are equitably redrawn after the 2020 census, researchers have developed an open-source tool that can help congressional redistricting observers spot unusual configurations.
GerryChain uses mathematical and computational models to generate a representative collection of maps that would meet legal voting rules and priorities for new districts. It can be used as a baseline for comparison in the evaluation of newly proposed plans and can indicate outlier configurations that may be the result of partisan goals.
The software was first developed by a team led by Daryl DeFord, an assistant mathematics professor at Washington State University (WSU), as a part of the 2018 Voting Rights Data Institute. In 2018, GerryChain was used in Virginia to analyze maps proposed to remedy House of Delegates districts that a federal court ruled were unconstitutional racial gerrymanders.
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IMAGE: Visualization of sampled county-preserving Virginia Congressional voting districts, created with the ReCom method in Gerrychain. view more
Credit: Daryl DeFord, Washington State University
PULLMAN, Wash. With state legislatures nationwide preparing for the once-a-decade redrawing of voting districts, a research team has developed a better computational method to help identify improper gerrymandering designed to favor specific candidates or political parties.
In an article in the Harvard Data Science Review, the researchers describe the improved mathematical methodology of an open source tool called GerryChain. The tool can help observers detect gerrymandering in a voting district plan by creating a pool, or ensemble, of alternate maps that also meet legal voting criteria. This map ensemble can show if the proposed plan is an extreme outlier one that is very unusual from the norm of plans generated without bias, and therefore, likely to be drawn with p