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Mathematicians are deploying algorithms to stop gerrymandering

For decades one of those users was Thomas Hofeller, “the Michelangelo of the modern gerrymander,” long-time official director of the Republican National Committee redistribution, who died in 2018.

Gerrymandering’s schemes include “cracking” and “regrouping” – the scattering of votes for a party across districts, thereby diluting their power and stuffing like-minded voters into a single district, wasting the power they would have. somewhere else. The city of Austin, Texas, is cracked, divided into six neighborhoods (it’s the largest American city that doesn’t anchor a neighborhood).

In 2010, the full force of the threat materialized with the Republicans Majority Project, or REDMAP. He spent $ 30 million on state legislative restricted ballot races, with winning results in Florida, North Carolina, Wisconsin, Michigan and Ohio. “The victories in 2010 gave them the power to draw the cards in 2011,” says David Daley, author of, Ratf ** ked: The real story behind the secret plan to steal American democracy.

“What was dark art is now dark science.”


The fact that technology has advanced by leaps and bounds since the previous redistribution round only amplified the result. “It made the gerrymanders drawn that year much more durable and long lasting than any other gerrymanders in our country’s history,” he says. “It’s the sophistication of the computer software, the speed of the computers, the amount of data available, that allows fan cartographers to run their maps through 60 or 70 different iterations and really fine-tune and optimize the partisan performance of those maps. . “

As Michael Li, a redistribution expert at the Brennan Center for Justice at New York University Law School, puts it: “What was once dark art is now dark science. And when manipulated cards are implemented in an election, he says, they are almost impossible to overcome.

A mathematical microscope

Mattingly and his team Duke continued to write code that they believe will produce a “huge victory, algorithmically”, preparing for the actual application of their latest tool, which debuted in an article (currently in progress). revision) with the technically heady title “Monte Carlo Multiscale Merge-and-Split Markov Chain for Redistribution.” “

Advancing the technical discourse, however, is not the top priority. Mattingly and his colleagues hope to educate politicians and the public, as well as lawyers, judges, fellow mathematicians, scientists, anyone interested in the cause of democracy. In July, Mattingly gave a public lecture with a more accessible headline that got right to the point: “Can You Hear the Will of the People in the Vote?”

Misshapen quarters are often considered the mark of a gerrymander. With the 2012 map in North Carolina, congressional districts were “very odd looking beasts,” says Mattingly, who (along with his key collaborator, Greg Herschlag) provided expert testimony in some of the lawsuits. judicial proceedings that followed. Over the past decade, there have been court challenges across the country, in Illinois, Maryland, Ohio, Pennsylvania, and Wisconsin.

But while these disfigured neighborhoods “make really nice posters, coffee mugs and t-shirts,” says Mattingly, “the truth is, stopping weird geometries won’t stop gerrymandering.” And in fact, with all of the technologically sophisticated sleight of hand, a gerrymandered card can prove difficult to detect.

These North Carolina Congressional District maps illustrate how geometry is not a sure-fire indicator of gerrymandering. The 2012 NC map, with its bizarre district boundaries, has been viewed by the courts as a racial gerrymander. The replacement, the 2016 NC card, looks quite different and tame by comparison, but has been seen as an unconstitutional political gerrymander. Jonathan Mattingly’s analysis of Duke and his team showed that the 2012 and 2016 cards were politically equivalent in their partisan results. An officially appointed expert drew the NC 2020 card.


Tools developed simultaneously by a number of mathematical scientists provide what is called an “extreme outliers test”. Each researcher’s approach is slightly different, but the result is this: a card suspected of being gerrymandered is compared to a large collection, or “set”, of unbiased and neutral cards. The mathematical method at work, based on so-called Markov chain Monte Carlo algorithms, generates a random sample of maps from a universe of possible maps and reflects the probability that a given map satisfies various political considerations.

Overview maps are coded to capture various principles used to draw districts, taking into account how those principles interact with the geopolitical geometry of a state. The principles (which vary from state to state) include criteria such as keeping districts relatively compact and connected, making them roughly equal in population, and preserving counties, municipalities and communities with interests. common. And district cards must comply with the United States Constitution and the Voting Rights Act of 1965.

With the release of the 2020 data by the Census Bureau, Mattingly and his team will load the dataset, run their algorithm, and generate a collection of typical, non-partisan district plans for North Carolina. From this wide distribution of cards and taking into account historical voting patterns, they will discern benchmarks that should serve as safeguards. For example, they’ll assess the relative likelihood that these cards will produce various election outcomes – say, how many seats Democrats and Republicans won – and by what margin: with a 50-50 split in the vote, and given the votes plausible models, a neutral card is unlikely to give Republicans 10 seats and Democrats only three (as was the case with this 2012 card).

“We use computational math to determine what we would expect as results from unbiased maps, and then we can compare with a particular map,” says Mattingly.

In mid-September, they will announce their findings, then hope state lawmakers heed the safeguards. Once new district maps are released later in the fall, they will analyze the results and engage in the public and political conversations that will ensue. play a central role.

“I don’t want to just convince someone that something is wrong,” Mattingly says. “I want to give them a microscope so they can look at a map and understand its properties, and then draw their own conclusions.”

Jonathan mattingly
Jonathan Mattingly is an applied mathematician at Duke University.


When Mattingly testified in 2017 and 2019, analyzing two subsequent iterations of North Carolina district maps, the court agreed that the maps in question were overly partisan gerrymanders, discriminating against Democrats. Wes Pegden, mathematician at Carnegie Mellon University, testified using a similar method in a case in Pennsylvania; the court recognized that the card in question discriminated against Republicans.

“Courts have long struggled with how to measure partisan gerrymandering,” Li said. “But then there seemed to be a breakthrough, when court after court struck down cards using some of these new tools. “

When the North Carolina case went to the United States Supreme Court in 2019 (along with a Maryland case), mathematician and geneticist Eric Lander, a professor at Harvard and MIT who is now the principal President Biden’s scientific adviser, observed in a brief that “computer technology has caught up with the problem it created. He considered the extreme outliers standard – a test that simply asks, “What fraction of the redistribution plans is less extreme than the proposed plan?” “- a” simple quantitative mathematical question to which there is a right reply.”

The majority of judges concluded otherwise.

“The five Supreme Court justices are the only ones who seemed to have trouble seeing how the math and models worked,” says Li. “The state and other federal courts have been successful in applying it – it doesn’t. was not beyond the intellectual capacity of the courts to handle, nor was a complex case of sex discrimination or a complex case of securities fraud. But five Supreme Court justices said, “It’s too difficult for us. “

“They also said, ‘It’s not up to us to fix this, it’s up to the states to fix this; it’s up to Congress to sort that out; it’s not for us to fix, ”Li said.

Will it matter?

According to Daley, the Supreme Court ruling gives state lawmakers “a green light and no speed limit on the type of partisan gerrymanders they can adopt when creating maps later this month- this”. At the same time, he says, “the technology has improved to such an extent that we can now use it. [it] to see through the tech-driven gerrymanders that are created by lawmakers.



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