A metric to detect gerrymandering which uses both Geography and Election Outcomes.
Beginning with a proposed districting plan, the GEO metric uses vote share swaps from neighboring districts to estimate how much flexibility each party has to improve their electoral outcome.
A higher value for party’s GEO score indicates more opportunity to improve their outcome by making small changes. That is, the map may be gerrymandered against that party.
A lower value for a party’s GEO score indicates that their outcome was already potentially optimal. That is, the map may be gerrymandered for that party.
You can find more details in our article The Geography and Election Outcome Metric: An Introduction, published online July 22, 2022 in The Election Law Journal, and available as an Open Access article.
We are working to provide an analysis of the Congressional and state legislative districting plans for all 50 states, available at GEO Metric Analysis of Current Maps. These pages also include the input files needed to run the Python code to compute the GEO metric.
For a summary of the GEO metric scores, as well as several other measures, see
State legislative plans table (Coming soon)
Python code to compute the GEO metric contains the code and instructions for computing the GEO metric.
The STEM in Redistricting team (S. Somersille, T. Ratliff, E. Veomett, M. Campisi) designed the Geography and Election Outcome (GEO) metric and maintains these pages.