Duke University Professor to explain emerging math tool at upcoming conference that will be used across the U.S. to help identify when political boundaries are unfairly gerrymandered in the coming redistricting cycle
Durham, NC, June 29, 2021 (GLOBE NEWSWIRE) -- As state legislatures get set to draw new congressional and legislative lines this fall, a leading Duke University mathematician is sending a strong message that it’s time for people to demand that maps be drawn fairly, and he says for the first time in American history, we have the tools to do it: modern math sampling.
“Political boundaries need to be drawn in a manner that enables election results to accurately reflect changes in political preferences among the electorate,” said Jonathan Christopher Mattingly, Professor of Mathematics and Statistical Science at Duke University, who will be presenting a free and livestreamed public lecture as part of the Society of Industrial and Applied Mathematics (SIAM) Annual Meeting on July 20. “If we don’t do that, our elections will never reflect the political will of the people at the ballot box and regardless of what party you align with, that’s not good,” he added.
Mattingly’s team of researchers is leading the way when it comes to understanding and quantifying gerrymandering, the intentional manipulation of political districts to benefit a particular political party or group. Their proven method – which uses a repeated random sampling method called Monte Carlo to generate non-biased maps according to public policy and electoral guidelines – will be used by several groups across the U.S. to assess proposed redistricting across the country and identify incidences of gerrymandering as new districts are drawn in September.
“Gerrymandering is not about pointing to strange-looking maps or ensuring proportional representation, something our electoral system is simply not designed to do,” said Mattingly. “It’s about having an agreed upon set of principles we value in public policy that we want our maps to reflect, and the question is, were those principles followed or were other criteria secretly used to bias a map towards one party or another? Math can tell the difference.”
The U.S. political system chooses representatives for local geographic districts every 10 years. By applying their math model, the Duke University researchers show how the simple act of redrawing district boundaries can flip which party wins a majority in a dramatic way.
“Because our maps are drawn based on properties of public policy and relevant court rulings, as well as geographic size, number of constituents and regions of ethnicity, they help us to understand what a political outcome should look like based on the votes,” Mattingly explained. “We can then compare that result to the map proposed by the legislature and if the outcome is very different, it leads one to question whether there was a hidden agenda.”
Mattingly, who was awarded the Defender of Freedom award by the nonpartisan watchdog group Common Cause for his work on quantifying gerrymandering, has testified in several court cases related to gerrymandering. Based in large part on his testimony, all congressional and legislative maps in the state were deemed unconstitutional and replaced for the 2020 elections. As a result, the legislative delegation in North Carolina went from 10 Republicans and three Democrats, to eight Republicans and five Democrats, just by redrawing the lines fairly.
In his upcoming SIAM Annual Meeting presentation, entitled Can You Hear the Will of the People in the Vote? Assessing Fairness in Redistricting, Mattingly will demonstrate how math will similarly be used across the U.S. this fall to show what fair, unbiased maps should look like ahead of redistricting. The presentation is free for the public and media to attend. It will be streamed on Zoom and posted to SIAM’s YouTube afterwards. Register here to watch the presentation live.
“This is a big moment in our history,” he said. “We’ve been building and refining our methods for the past five to eight years and now we have an unprecedented opportunity to check the effect of gerrymandering and inform the public. Math is providing the filter we need to ensure the vote of the people truly translates into their will.”
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