The prospect of convincing courts to intervene in partisan gerrymandering has inspired a great deal of research and, recently, public attention. But how can neutral parties such as courts and independent redistricting commissions discern when a district map is unfairly gerrymandered? We review the case law and the leading measures of substantive fairness, explaining why, alone, they are unlikely to be sufficient for neutral decision makers to ascertain gerrymanders. We then explain the concept of outlier analysis, a particularly promising intervention into the field, but one that is computationally challenging, as it requires generating a sample of reasonable district maps. We review the major approaches to assembling these samples, and we present recommendations for improvement and future research that could help lead to the development of a consensus approach to assessing whether a map is gerrymandered.
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