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We investigate the claim that the Utah congressional districts enacted in 2011 represent an unfair Republican gerrymander, and we evaluate the most common measures of partisan fairness and gerrymandering in the context of Utah's congressional districts. We do this by generating large ensembles of alternative redistricting plans using Markov chain Monte Carlo methods. We also propose a new metric of partisan fairness in Utah, namely, the Republican vote share in the least-Republican district. This metric only makes sense in settings with at most one competitive district, but it is very effective for quantifying gerrymandering and for evaluating other metrics used in such settings.

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