Making Compactness Matter: Evaluating a Population-Based Compactness Measure in Pennsylvania

Keywords: redistricting, compactness
Abstract Type: Paper Abstract

Abstract

District shapes and compactness have historically been a major signal, both to lawmakers and the public, that some kind of malfeasance, or gerrymandering, has occurred. We argue, however, that much of the discussion of compactness in policy and academic spaces neglects a clear theory of why compactness matters for fair representation, choosing to take a purely geometric understanding of compactness as sufficient. In this paper, we extend DeFord et al.'s (2021) Partisan Dislocation metric to measure the compactness of districts not based on their geometry but how they separate voters into different districts at different spatial scales. We conceptualize the harms of noncompact districts as politically isolating individuals from their neighbors, making activities like canvassing more difficult and decreasing awareness of which districts voters belong to. We develop a multiscalar, population-based measure of compactness using geocoded voterfiles. We evaluate this new metric in Pennsylvania, examining how compactness is operationalized in a collection of redistricting plans submitted to the 2021 Draw The Lines PA mapping competition.