The silver lining in the Supreme Court gerrymandering decision

The Supreme Court decision in Gill v. Whitford was surely a huge disappointment to many who were hoping the court might finally rule on partisan gerrymandering. Refusing to reach the merits of the case, the high court held that the plaintiffs lacked standing to bring suit, ruling that the challengers failed to claim a personal injury, since they did not show that their individual districts had been harmed in the redistricting.

The holding might be mourned as a missed opportunity in the fight against partisan gerrymandering in the United States. But the reality is that the Supreme Court may have handed the challengers a gift. The petitioners were simply not ready to fully answer the questions that swing justices, particularly Justice Anthony Kennedy, want answered.

{mosads}In earlier cases, Kennedy has been clear why he and other justices have been so squeamish about interfering in partisan gerrymandering lawsuits. The Supreme Court wants a clear, accurate and objective standard for determining when such partisan gerrymandering has occurred. Given the election stakes, the last thing the justices want is to have their decisions appear to the American people as politically motivated, and an objective measure will insulate them from that critique.

The challengers proposed such a standard with the “efficiency gap,” a mathematical tool that purportedly measures partisan gerrymandering. Since its creation four years ago, mathematicians have raised various concerns about this tool. One of the problems relevant to the Whitford case is that the efficiency gap simply cannot identify the specific voting districts within a state that have been most affected by gerrymandering. It only offers a general statement that voting rights have been harmed in the state. The Supreme Court wanted an algorithm that was district specific, and the efficiency gap just does not meet that need.

In her concurrence, Justice Elena Kagan sought to address this problem by offering a new legal theory of political gerrymandering. According to Kagan, plaintiffs could argue that partisan gerrymandering violated First Amendment right to free association. The benefit of this claim, according to Kagan, is that it would not require plaintiffs to point to specific district injuries. Showing statewide harm would be sufficient. This theory is novel, and it is not clear that the Supreme Court would adopt it as a winning one.

The alternative is to improve the tools used to identify partisan gerrymandering. In fact, for several years outside the public eye, teams of mathematicians have been working on precisely that project. Many have been meeting at workshops organized by the Metric Geometry Gerrymandering Group. This is a mathematics group with a mission to help the political system operate more fairly and democratically. The result has been an explosion of research, both in new methods of detecting gerrymanders, as well as in analysis of metrics and algorithms. Several promising alternatives have come to the fore, and perhaps the most appealing is called “outlier analysis.”

Outlier analysis relies on an algorithm that generates a random sample of tens of thousands of redistricting maps. These are all valid maps, in that they satisfy widely accepted parameters for what a districting plan should look like, with contiguous geography and compact shape, among other measures. For each of these maps, the analysis determines how many districts each party would have won using past election data. Most voting maps generate roughly comparable numbers of Republican and Democratic representatives getting seats in Congress. But some of the maps are extreme outliers that greatly benefit one particular party. If the map that is drawn by the state is one of those extreme outliers, a strong presumption exists that the map was made with partisan interests in mind.

Research has confirmed that outlier analysis generates a test for partisan gerrymandering that is even more useful than the efficiency gap under most circumstances and has another benefit. A variant of the outlier analysis, developed by researchers at Duke University, can be used to identify which specific districts within the state have been most affected by partisan gerrymandering. In other words, this method provides precisely what the Supreme Court has requested in its Whitford decision.

As plaintiffs reframe their arguments to address the ruling, they will undoubtedly consider all the options available to them. Perhaps they will introduce new evidence to show which specific voting districts were intentionally gerrymandered. Perhaps they will take up the new First Amendment route, allowing for statewide evidence, suggested by Kagan.

The challengers will also do well to consider the latest mathematical research on partisan gerrymandering. Mathematicians, for all their strengths, are not typically seen as the great bulwarks of democracy. But mathematicians can be patriotic citizens too, and they have heard the call for help. It is time we listened to what they have to say.

Aaron Rappaport is a professor of law at the University of California Hastings College Of Law and a former assistant director of the White House National Economic Council. Ellen Veomett, Ph.D., is an associate professor of mathematics at St. Mary’s College of California.