“Can math stop partisan gerrymandering?”

Sam Wang and Brian Remlinger LAT oped:

Setting aside the Monte Carlo analysis, the most straightforward way to determine if gerrymandering has gone too far is to ask whether one side’s wins were exceptionally lopsided compared with the other. In North Carolina in 2016, for example, Democrats won their three seats by an average margin of 37 points, while Republicans won by only 21 points. Using what may be the world’s most widely-used statistical test, the “t-test,” such an outcome would only occur by chance 1 out of 350 times. Courts would still have to decide where to draw the line — 1 out of 350 may be ridiculous, but what’s acceptable? Since scientists consider 1 out of 20 “statistically significant,” perhaps that’s the most logical threshold.

More complex measures of extreme gerrymandering are possible too, such as the efficiency gap, which political scientists have devised to estimate how many votes have been “wasted.”

A statistical standard could certainly harmonize with existing election law, which already requires that districts have equal populations, but allows odd shapes to accommodate minority voting rights. Because of their ubiquity in the sciences, the t-test or efficiency gap are likely to withstand detailed critiques in a court challenge.

Five justices, including Associate Justice Anthony M. Kennedy, have expressed interest in establishing a standard such as the ones we have described. If Kennedy were to finally rein in gerrymandering, that would cap an already-distinguished legacy of his nearly 30 years on the Supreme Court.


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