The Ohio Gerrymandering Decision

Today’s decision striking down Ohio’s congressional districts as unconstitutional partisan gerrymanders is notable in several respects. First, it was again unanimous. By my count, this is the fourth consecutive decision (following those in Maryland, Michigan, and North Carolina) in which every judge has agreed that certain challenged districts are unlawful. Adding the Wisconsin case to the set, fourteen out of fifteen judges have ruled in favor of the plaintiffs in the recent wave of partisan gerrymandering litigation. Moreover, six of these judges have ruled against districts that were drawn by the party of the president who appointed them (two Democratic appointees in Maryland, one Republican appointee in Michigan, one Republican appointee in North Carolina, one Republican appointee in Ohio, and one Republican appointee in Wisconsin). In an era of growing judicial polarization, this level of bipartisan consensus is remarkable.

Second, the Ohio decision adopted the same partisan vote dilution standard as the earlier Michigan, North Carolina, and Wisconsin rulings. Under this test, “Plaintiffs must prove (1) a discriminatory partisan intent in the drawing of each challenged district and (2) a discriminatory partisan effect on those allegedly gerrymandered districts’ voters. Then, (3) the State has an opportunity to justify each district on other, legitimate legislative grounds.” The Ohio decision was also particularly clear about the role of plan-wide measures of partisan asymmetry in this analysis. These metrics “reveal if, and by how much, the map benefits one party over another by facilitating the more efficient translation of that party’s votes into seats.” “Multiple partisan-bias metrics should be used, and consistency across metrics and across data sets is key in evaluating this type of evidence.” Districts should thus be invalidated only if they belong to a map whose “partisan-bias metrics all point in the same direction” and reveal that “the redistricting plan is an historical outlier in its partisan effects.”

Third, the Ohio decision was the first to confront a serious argument that the Voting Rights Act justified the map’s bias. According to the defendants, the VRA required them to draw a black-majority district in northeastern Ohio (District 11, stretching from Cleveland to Akron) and thus to pack Democrats in that district. But as the court pointed out, there was no evidence of “effective white bloc-voting” in northeastern Ohio, meaning that no VRA claim in that area could succeed. In addition, the defendants made District 11 much more heavily black than it needed to be to elect a black-preferred candidate. “A 45% BVAP would be sufficient to elect the black-preferred candidate by a comfortable margin.”

And fourth, the Ohio decision was the first to analyze the plaintiffs’ associational claim using Anderson-Burdick balancing—a framework that Dan Tokaji has long advocated. As Dan has explained, Anderson-Burdick properly focuses courts’ attention on how severe the plaintiffs’ associational burdens are. Only heavier burdens trigger heightened scrutiny; lighter burdens, of the kind imposed by many district maps, result in something closer to rational basis review. Anderson-Burdick also properly instructs courts to balance the plaintiffs’ associational burdens against the government’s justifications for them. It thus avoids condemning all (or even most) maps designed by a single party: a scenario that several justices have warned against. Time will tell if the Ohio court’s use of Anderson-Burdick proves as durable as the partisan vote dilution standard it adopted.

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