Implementation of Statewide Election Data to Examine Fairness of South Carolina District Maps: A Comparative Analysis of Approaches for Approximating Results in Uncontested Races

After each census, researchers analyze election data to provide information relevant to the redistricting process. South Carolina is among a collection of states which face certain issues regarding election analysis of fairness due to the presence of a large percentage of uncontested races. Although uncontested results are known to create analysis challenges, there is not a universal consensus on how to best handle these situations. Here we explore quantification of partisan fairness and the impact of using statewide election county-level data as a proxy for estimating uncontested results. We develop a district approximation method using statewide elections at the county scale and use known metrics to qualitatively and quantitatively evaluate resulting election characteristics in historical and simulated election contexts. The same metrics were then used to perform a thorough comparative analysis of other common approximation methods. We find county-level election data to be an effective tool in approximating uncontested elections by providing evidence to support the notion that county-level data is effective under multiple election conditions. Furthermore, analysis of different approximation methods show how measures of partisan fairness for a particular election can change based upon a particular approximation method, potentially affecting future interpretations of uncontested election results.