While I understand the purpose and, to some extent, methods of gerrymandering, I actually have problems with the opposite: what constitutes a fair redistricting? Math Professor Moon Duchin of Tufts University has been working on that problem, and her team has taken the approach, from what I can gather, of generating hundreds, thousands, even millions of maps, and then evaluating them against a set of criteria. Those criteria?
“The opposite of gerrymandering isn’t proportional representation; the opposite of gerrymandering is not gerrymandering,” Jordan Ellenberg, a math professor at the University of Wisconsin and a co-author of the 2019 mathematicians’ brief to the Supreme Court, wrote in an essay in Slate that Duchin likes to quote.
And although Duchin advocates computing power as a potentially game-changing tool, she doesn’t propose taking humans out of the process.
“In all the different states, as we approach redistricting now and into the future, we need to keep on having these debates about what principles we want embodied in our maps,” she said. “Different states will come to different ideas about local fairness, about what fairness looks like there. I hope that they’ll use techniques like this to help them get closer to those ideals.” [WaPo]
In other words, the professor has punted on that question.
And that’s OK. The question seems to be hard, and rather than decreeing an answer and then fighting about it, Professor Duchin presents a collection of possible answers and stands back.
Duchin and her team have a website here.
