The website CityLab recently published a comprehensive article about data’s use in both fighting and perpetuating gerrymandering. The article, by Teresa Mathew, quotes PolicyMap Senior Data Analyst Bernie Langer:
“The software has advanced to the point where it can be done very methodically, writing the code that sets the goal of having the most wasted votes,” says Bernie Langer, a Senior Data Analyst at PolicyMap, a site that provides mapping data for public use. “Because of all of the polarization that’s going on, it’s a lot easier than it used to be to guess who an individual person would vote for based on their demographic and income status. You don’t need to find out what the individual voting records are—you can just use census data to look where there are people of certain races, income, educational attainment. That data is so granular it can be down to a census block group, and the software can efficiently make these gerrymandered districts.”
The article also references a post on PolicyMap’s Mapchats blog, by Data Analyst Lauren Payne-Riley, in which she delves into the various types of gerrymandering, and potential solutions.