Can a Mathematician Help Prevent Gerrymandering in Virginia? | Virginie News

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By STEVE THOMPSON, The Washington Post

When Virginians voted last year to create a commission to draw the state’s political districts, many hoped to avoid the partisanship that has marred previous redistribution efforts.

Gerrymandering – rigging cards to favor a political party or candidate – has long been used by incumbents in Virginia and elsewhere to retain or expand political power. Both sides agree that this undermines the integrity of the elections, but the complexity of the mapping makes prevention difficult.

Today, the Virginia commission is considering an offer of help from someone accustomed to solving complex problems: a mathematician.

Moon Duchin, a math professor at Tufts University who specializes in geometry, has been immersed in redistribution problems since 2016, when she taught a course on voting theory. Duchin thought the field of geometry should be able to help. She quickly founded the MGGG Redistricting Lab, an effort to apply data science to redistricting.

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The laboratory, which emerged from an informal research collective called the Metric Geometry and Gerrymandering Group, has helped refine the techniques for constructing representative samples of the universe of valid redistribution maps for a given jurisdiction. When human-generated maps deviate far from statistical standards, it can be indicative of gerrymandering or some other program, say Duchin and other mathematicians.

In 2018, Pennsylvania Gov. Tom Wolf (D) hired Duchin to assess the fairness of a congressional map revised by lawmakers, after that state’s Supreme Court ruled that a previous card was an illegal gerrymander. . Duchin found that the “bias in favor of Republicans (was) extremely unlikely on the new map,” she later wrote, putting the odds at around 0.1%.

In 2019, Duchin’s lab organized a group of mathematical and legal experts to file an amicus brief with the United States Supreme Court regarding the new mathematical method. They touted what they said was an emerging scientific consensus that computer sampling techniques can help distinguish maps drawn to conform to clear and transparent goals – such as creating compact districts and maintaining communities. communities together – maps created with hidden agendas like partisan gerrymandering.

In this landmark case, Rucho v. Common Cause, the court ultimately ruled that federal judges did not have the power to prevent politicians from drawing constituencies to preserve or expand their party’s power.

Duchin has worked with commissions and groups across the country, including the Michigan Independent Citizens Redistricting Commission, the Wisconsin People’s Maps Commission, and the Arizona Independent Redistricting Commission. His work has reported numerous cases of gerrymandering by both parties.

Last month, she offered her services to the Virginia Redistribution Commission. The bipartisan commission, which has an equal number of Democratic and Republican members, has faced traditional partisan pressure. Members voted 10 to 4 this summer to hire two groups of lawyers – a Democrat and a Republican – to make sure neither party gets an advantage. Then they also voted to hire two different map designers.

Democratic lawyer Gerald Hebert told commissioners at their August 23 meeting that he approached Duchin’s team to be their map designer. She refused, saying she didn’t want to work for one side or the other. Hébert therefore chose another map designer and proposed that the commission hire Duchin to consult with both parties, perhaps to help evaluate their proposed maps.

Committee co-chair Greta J. Harris, a Democrat, warmly welcomed the offer.

“I am delighted that Ms Duchin is on the call,” said Harris, one of the committee’s non-legislative members, after Duchin was introduced by telephone at the meeting. “The work that I have reviewed and that his lab is doing really tries to remove the partisan nature that can be so prevalent in any redistribution process.”

It was still not clear what the other members of the committee thought of the idea. A lawyer on the Republican side, Bryan Tyson, said at the meeting that he needed more time to review it.

“I could see some value depending on what it is,” he said. “But I want to understand what the outlines of it are.”

Commissioners vowed to avoid talking about the redistribution process outside of public meetings, and several members declined to comment or did not return messages from the Washington Post. Harris declined to comment except to say that she expected the decision to hire Duchin to be discussed at a future meeting.

Virginians overwhelmingly approved a constitutional amendment last fall to create the commission rather than continuing to allow the General Assembly to draw the state’s political districts. The process takes place every 10 years, based on US Census data.

The committee has 45 days to submit new cards to the General Assembly. If the commission cannot come to an agreement, or if the legislature rejects the plan, the Virginia Supreme Court would create the new maps.

The creation of the commission came after years of legal battles over gerrymandering. The cards in place now were created by a special master after federal courts repeatedly found that the Virginia Republicans’ cards unconstitutionally grouped black voters in a handful of districts.

A 2018 white paper from Duchin’s lab found that a plan for the House of Delegates presented by Democrats also diluted the black vote.

Duchin said in an interview that she did not want to be part of any partisan agenda. Rather, she’s looking for work “where you can kind of call bullets and strikes,” she said.

“I am a mathematician who uses open source algorithms, open source computer programs,” she said. “Which means not only that there is behind it a body of literature that has been developed outside of the political context, but also that everything we do with algorithms is completely transparent, because anyone can watch the code and understand how it works. “

A technique Duchin relies on, which she and others have called “the set method,” works by randomly creating tens of thousands of cards drawn according to the priorities given to the computer. The result is a collection – or set – of thousands of cards that reflect the much larger number (often trillions of billions) of cards that could be drawn in the same jurisdiction based on those priorities.

Sets can help solve an issue that has long plagued card drawers: a lack of neutral benchmarks, Duchin said.

“You will see people arguing, for example, over whether, if you redistributed without bias, would you get a result proportional to the vote? Is it a bit like the state of nature? she said. “People have been fighting about this for at least several decades, if not longer. “

In recent years, and with the help of improvements made by Duchin’s lab, mathematicians have learned to harness computational power to create such benchmarks.

“There are fast and efficient algorithms that build you lots of blueprints,” Duchin said. “Not only are they numerous, but we can explain how they are distributed in the world of possibilities. It’s new, and it’s pretty exciting.

Many people approach redistribution with an intuitive feeling that a state should elect representatives from each party in proportion to that party’s voters. According to this concept, called proportionality, when a party has 40 percent of the voters, it should get 4 out of 10 political representatives.

But mathematical research shows that due to political geography and demographic patterns – how densely or dispersed voters are for different parties, for example – things don’t necessarily turn out that way naturally. Duchin says getting rid of gerrymandering does not mean getting rid of the partisan advantages created by geography and demography; it means preventing people from intentionally orchestrating partisan advantages.

“The opposite of gerrymandering is not proportional representation; the opposite of gerrymandering is not gerrymandering, ”wrote Jordan Ellenenberg, professor of mathematics at the University of Wisconsin and co-author of the 2019 mathematicians brief to the Supreme Court, in an essay by Slate that Duchin likes to quote.

And while Duchin advocates computational power as a potentially revolutionary tool, she doesn’t offer to remove humans from the process.

“In all the different states, as we approach redistribution now and into the future, we need to continue to have these debates about the principles that we want to embody in our maps,” she said. “Different states will come up with different ideas about local equity, what equity looks like there. I hope they will use techniques like this to help them come closer to those ideals.

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