'The Supreme Court Is Allergic To Math'
The Supreme Court does not compute. Or at least some of its members would rather not. The justices, the most powerful jurists in the land, seem to have a reluctance — even an allergy — to taking math and statistics seriously.
For decades, the court has struggled with quantitative evidence of all kinds in a wide variety of cases. Sometimes justices ignore this evidence. Sometimes they misinterpret it. And sometimes they cast it aside in order to hold on to more traditional legal arguments. (And, yes, sometimes they also listen to the numbers.) Yet the world itself is becoming more computationally driven, and some of those computations will need to be adjudicated before long. Some major artificial intelligence case will likely come across the court’s desk in the next decade, for example. By voicing an unwillingness to engage with data-driven empiricism, justices — and thus the court — are at risk of making decisions without fully grappling with the evidence.
This problem was on full display earlier this month, when the Supreme Court heard arguments in Gill v. Whitford, a case that will determine the future of partisan gerrymandering — and the contours of American democracy along with it. As my colleague Galen Druke has reported, the case hinges on math: Is there a way to measure a map’s partisan bias and to create a standard for when a gerrymandered map infringes on voters’ rights?
The metric at the heart of the Wisconsin case is called the efficiency gap. To calculate it, you take the difference between each party’s “wasted” votes — votes for losing candidates and votes for winning candidates beyond what the candidate needed to win — and divide that by the total number of votes cast. It’s mathematical, yes, but quite simple, and aims to measure the extent of partisan gerrymandering.
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Justice Neil Gorsuch balked at the multifaceted empirical approach that the Democratic team bringing the suit is proposing be used to calculate when partisan gerrymandering has gone too far, comparing the metric to a secret recipe: “It reminds me a little bit of my steak rub. I like some turmeric, I like a few other little ingredients, but I’m not going to tell you how much of each. And so what’s this court supposed to do? A pinch of this, a pinch of that?”
Justice Stephen Breyer said, “I think the hard issue in this case is are there standards manageable by a court, not by some group of social science political ex … you know, computer experts? I understand that, and I am quite sympathetic to that.”
And Chief Justice John Roberts, most of all, dismissed the modern attempts to quantify partisan gerrymandering: “It may be simply my educational background, but I can only describe it as sociological gobbledygook.” This was tough talk — justices had only uttered the g-word a few times before in the court’s 230-year history. Keep in mind that Roberts is a man with two degrees from Harvard and that this case isn’t really about sociology. (Although he did earn a rebuke from the American Sociological Association for his comments.) Roberts later added, “Predicting on the basis of the statistics that are before us has been a very hazardous enterprise.” FiveThirtyEight will apparently not be arguing any cases before the Supreme Court anytime soon.
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I reached Eric McGhee, a political scientist and research fellow at the Public Policy Institute of California who helped develop the central gerrymandering measure, a couple days after the oral argument. He wasn’t surprised that some justices were hesitant, given the large amount of analysis involved in the case, including his metric. But he did agree that the court’s numbers allergy would crop up again. “There’s a lot of the world that you can only understand through that kind of analysis,” he said. “It’s not like the fact that a complicated analysis is necessary tells you that it’s not actually happening.”
During the Gill v. Whitford oral argument, the math-skeptical justices groped for an out — a simpler legal alternative that could save them from having to fully embrace the statistical standards in their decisionmaking. “When I read all that social science stuff and the computer stuff, I said, ‘Is there a way of reducing it to something that’s manageable?’” said Justice Breyer, who is nevertheless expected to vote with the court’s liberal bloc.
It’s easy to imagine a situation where the answer for this and many other cases is, simply, “No.” The world is a complicated place.
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McGhee, who helped develop the efficiency gap measure, wondered if the court should hire a trusted staff of social scientists to help the justices parse empirical arguments. Levinson, the Texas professor, felt that the problem was a lack of rigorous empirical training at most elite law schools, so the long-term solution would be a change in curriculum. Enos and his coauthors proposed “that courts alter their norms and standards regarding the consideration of statistical evidence”; judges are free to ignore statistical evidence, so perhaps nothing will change unless they take this category of evidence more seriously.
But maybe this allergy to statistical evidence is really a smoke screen — a convenient way to make a decision based on ideology while couching it in terms of practicality.
“I don’t put much stock in the claim that the Supreme Court is afraid of adjudicating partisan gerrymanders because it’s afraid of math,” Daniel Hemel, who teaches law at the University of Chicago, told me. “[Roberts] is very smart and so are the judges who would be adjudicating partisan gerrymandering claims — I’m sure he and they could wrap their minds around the math. The ‘gobbledygook’ argument seems to be masking whatever his real objection might be.”