In the 205 years since Gov. Elbridge Gerry of Massachusetts was criticized for drawing legislative-district boundaries to benefit his own political party, the gerrymander has presented a quandary: an obvious mathematical trick whose chicanery is almost impossible to prove mathematically.
In a 2004 Pennsylvania case, its most recent ruling on the matter, the U.S. Supreme Court declared that it could see no clear standard for deciding how much gerrymandering is too much.
In opening its consideration of the case last week, Gill v. Whitford, No. 16-1161, the court was provided with reams of social-science research that put hard numbers on how unfairly some states have drawn their legislative districts. In 2012, Democrats were estimated to represent 51 percent of Wisconsin’s electorate, and President Barack Obama won 53.5 percent of the statewide vote. Yet Democrats won only 39 of the 99 seats in Wisconsin’s Legislature in 2012, and just 36 seats in 2014.
Among the most prominent pieces of academic work given to the Supreme Court last week was a paper that tallied similar "efficiency gaps" in virtually all redistricting plans in the United States since 1972. The paper found that Wisconsin’s redistricting was clearly one of the worst examples.
But is even that level of statistical rigor enough to prove that what Wisconsin did should be forbidden? And what exactly is the role of the academic social sciences in trying to help correct such shortfalls? Especially when, during last week’s oral arguments, Chief Justice John G. Roberts called that academic work "sociological gobbledygook."
As the justices were considering the matter, Philip Rocco, an assistant professor of political science at Marquette University, in Wisconsin, weighed in with a Washington Post commentary arguing that the new academic analyses of gerrymandering should prove key to ending a practice that costs millions of Americans their democratic rights.
Yet in a discussion with The Chronicle, Mr. Rocco acknowledged that the hard data still leave room for interpretations. The following exchange has been edited for length and clarity.
Q. The extent of gerrymandering seems great in Wisconsin. Nevertheless, can the Supreme Court rule out other explanations for seemingly unfair election outcomes, such as the quality of campaigns or random variations in populations?
A. The analysis in this case shows that Wisconsin Democrats could have won a historic number of votes and still not won the state Legislature. The test is for whether the plan is creating an extreme imbalance in the number of seats.
Q. But "extreme" is a word, not a number. Don’t we need a number?
A. I agree there’s not a precise mathematical definition of what "extreme" is. In some sense, social science won’t be able to produce that.
Q. And if social science can’t, then the court might say, "You might think this election outcome is historically unprecedented. But we’re having flooding that now seems historically unprecedented but might be even worse next year."
A. The first part of the analysis is, Do you think gerrymandering is an important constitutional harm? If you do, then the question is, Can the judiciary find a way to enforce it? For better or worse, what has been lacking in the past is some sense of specificity about what is causing parties to lose seats in cases like this.
Q. So we accept that the efficiency-gap measurement is an important tool. Do we also need an agreed-upon standard to apply that tool? The efficiency-gap authors suggested the courts allow no greater than a 7-percent loss in a party’s voting power. Does each state or the court need to choose a specific percentage before this will work?
A. Other social-science standards offered to the court, and there are several, show that it’s impossible, until the next decennial census, for Democrats to convert a majority of votes into a majority of seats in the Wisconsin state Legislature.
Q. Unless maybe you had a social-science analysis from a place like the Heritage Foundation, which argued otherwise?
A. To the extent that the court still cares about things like the Daubert Standard [which guides whether expert witnesses’ testimony is admissible in federal court] for thinking about what a scientific consensus is, by any measure the results come out the same way. There might be differences around the margins, and then that’s another discussion.
Q. What should be the absolute limit on gerrymandering, considering some natural degree of random spread?
A. We can continue to debate the right standard, and we won’t know until we die, and St. Peter tells us. Social science isn’t trying to play the role of God here, nor is it trying to play the role of the court, or the role of the sovereign in a theoretical sense. What it’s trying to do is illustrate that you can delineate the effects and then do something about them.
People might disagree about how extreme is too extreme, and in a sense that does have to be litigated precisely. But I think what they can show is that by a variety of standards — take your pick — every single time you will see that there are some really extreme outliers.
And even if you think, "OK, there’s a lot of uncertainty — the court doesn’t want to appear subjective when it’s making a subjective judgment," the point is that, if you choose a standard like 7 percent, and you include something about intent, that doesn’t lead you to strike down that many plans.
Q. Big picture: Should we hold out hope that social science can really making a meaningful difference in some of these intractable problems we have in society?
A. The whole idea of social science saving democracy from itself is not how I would put it.
Social science begins with what people used to refer to as the social question. And especially in the early 20th century, there were a lot of examples where social scientists were working not to dictate the problems of society from on high, but working kind of in collaboration with people both in government and in social society, actors from philanthropies and labor-oriented interests, and large stakeholders, to solve social problems.
But social science rarely presumes to do that alone, or to sit on high and proclaim the right path. It’s a collaborative endeavor.