Using unsupervised learning again, we find and describe eight major census tract types, or characteristic mixtures of voter clusters at the census tract level.

We analyze data appended to the national voter file to find six ideological superclusters of voters which we split further into 21 final clusters. Georgia’s voter cluster distribution is presented as an example.

This analysis of the Texas voter file proceeds stepwise from clustering voters based on issue scores to identifying gerrymandering and examining anomalous election outcomes from the 2020 general election.