A team of US researchers has proposed improvements to a computational method for identifying likely gerrymandering designed to favor specific candidates or political parties during elections.
Gerrymandering is the practice of gaining a political advantage by manipulating constituency boundaries. This involves diluting the opposing party’s voters by spreading them over many districts and concentrating them in a small number of districts to reduce their influence in other districts.
Gerrymandering can result in constituencies with absurd shapes that are difficult to justify. An article in Harvard Data Science Review describes improvements to the mathematical methodology behind a tool called GerryChain, which aims to detect gerrymandering.
The tool detects likely instances of gerrymandering by creating a “pool” of alternative electoral district cards that also meet legal voting criteria, such as having a similar number of voters in each district.
This pool of districts can be used to demonstrate when proposed districts are extremely different from the automatically generated plans and are therefore likely to have been prepared with political goals in mind.
GerryChain was created in 2018 by Washington State University mathematician professor Daryl DeFord for the Voting Rights Data Institute. In an earlier iteration, it was used to analyze district maps proposed for elections to the Virginia House of Delegates, which a federal court ruled was subject to unconstitutional racial gerrymanders.
“We wanted to build an open-source software tool and make it available to people interested in reform, especially in states with skewed baselines,” said DeFord, who is co-lead author of the study.
“It can be an impactful way for people to get involved in this process, especially by entering this year’s redistribution cycle, where there will be many opportunities to point to less than optimal behavior.
” The new paper focuses on how the mathematical and computational models implemented in GerryChain can be used to contextualize proposed districts by providing examples of alternative valid plans to compare them with.
These plans can be used when a voting plan is challenged in court as gerrymandered. The proposed Virginia House of Representatives district plan had 12 constituencies with a black population of 55 percent or more;
comparing this to a pool of alternative legal plans, it turned out that the proposal was an extreme outlier from what was possible and was therefore very likely drawn with the intention of reducing the influence of black voters.
One of the biggest challenges in creating voting cards is the sheer number of possibilities, DeFord said: “There are more viable plans in many states than there are molecules in the universe. That’s why you want this kind of math tool.
“The GerryChain tool uses a method called a spanning tree recombination: to create an alternate voting map, the method involves taking two districts, merging them, before splitting them up in another way. allows for greater change, with multiple voting blocks changing at once.
It can create many alternative plans within a few hours or days and can be used by anyone. However, the authors say computers should not be relied upon to make final voting plans; rather that this method provides a tool for analyzing baselines and evaluating possible alternatives.
“This isn’t some magical black box where you press the button and you get a set of perfect plans,” said DeFord. “It requires really serious collaboration with social scientists and lawyers. Since the rules are written and implemented by humans, this is a fundamentally human process. “