Do you know where the term "gerrymandering" came from?

I probably did at one point, somewhere back in the previous millennium, but that brain cell, like so many others, has passed on to a location far, far away.

Anyway, I have learned (or perhaps relearned) that it originated in 1812 when a fellow named Elbridge Gerry, a signer of the Constitution and a VP for President James Madison who at the time was governor of Massachusetts, drew a bizarre-looking district that favored his party over the rival party in a portion of Boston. The curvy lines looked something like a salamander. So it became "Gerry's salamander" and, later, "Gerry-mander."

This fun fact comes not from a historian but a mathematician who strongly believes her field of interest is capable of taming the ongoing madness that inevitably erupts when a new census requires redrawing the voting lines, as will be the case after 2020.

Moon Duchin, a professor at Tufts University, has developed a complex mathematical analysis that she believes can prevent the party in power from stacking the deck, a practice that involves jamming the other side's voters into just a few districts and/or spreading them across several districts so they lose their clout.

Duchin warns that not all ugly shapes are unfair (they can be based on physical geography, which makes sense in some cases) and that seemingly normal shapes can be unfair.

Her analysis uses a scientific computing concept called Markov chain Monte Carlo, which as far as I can tell is random sampling when there's too much information to crunch every single number.

I tried to comprehend everything in a lengthy article she wrote about this in Scientific American, but after encountering terms like "equinumerous rook partitions" and "combinatorial enumeration" and "ergodic theory," I suffered a minor stroke.

Fortunately, Duchin has a true believer in Kent State University prof Steve Gagola, and he will serve as our interpreter.

"The beauty of Duchin's algorithm is that it does NOT suggest any particular redistricting map,” Gagola says. “Rather, it uses a metric to measure the level of bias in any proposed map and the maps that are close to the proposed one. ...

"This is important because I can see rejecting its use based on 'giving up control to an elite group of academicians.' No control is given up regarding preparation of a district map. If a particular redistricting is identified as too extremely gerrymandered, then the problem [would be] thrown back to the politicians ... until they get it right."

Some places have already embraced the concept. Pennsylvania Gov. Tom Wolf used Duchin's analysis to confirm another study that concluded a 2011 plan was extremely partisan. And that a second try was equally partisan.

The Kent professor points out that the highest court has had problems deciding on a workable standard for identifying extreme gerrymandering. Duchin's idea, he says, is the answer.

“We think the time is right to make a computational intervention,” Duchin wrote. “The mathematics of gerrymandering is surprisingly rich ... and computing power is arguably just catching up with the scale and complexity of the redistricting problem.

“Despite our group's technical orientation, our central goal is to reinforce and protect civil rights.”

Works for me. Gerrymandering hurts all of us, in part because when one party is guaranteed to win a district, the more extreme wing of that party tends to gain additional clout.

Most of us don't want to wander any farther toward the extremes. Most of the answers are somewhere in the middle.

Says Gagola, “Do you think that our Ohio politicians will embrace a metric that will gauge the fairness of any proposed redistricting map?”

I'm not sure I want to hold my breath, but that would certainly be nice.

Bob Dyer can be reached at 330-996-3580 or bdyer@thebeaconjournal.com. He also is on Facebook at www.facebook.com/bob.dyer.31