After getting some practice with my GIS mapping software and gathering some user feedback from demonstrations, I’ve made an improved legend for election maps.
Functionally, it’s the same as before, but more intuitive now. The color legend measures a unique campaign formula I came up with in grad school I now call the “Partisan Performance Index.”
When measuring voting behavior, I’ve found many times that simply getting the Democratic, Republican, and Swing bases of voters leaves out some important information. Especially since we see such high ticket spliting among suburban voters in the Chicagoland area. That’s were the Partisan Performance Index (PPI) helps define an area. It’s an average of partisan results for all competitive races on the election ballot. An average of races, all the way down to judicial offices, gives you a much better overall feel for a voter district. It will not be swayed by unique races, issues and candidates.
The goal of PPI is to measure how voters cast ballots when they don’t know much walking into the voting booth. What is the normal low information voting behavior? PPI provides the answer. This is important information for down ballot campaigns most candidates run in.
I’ll start using this legend layout for new maps, and slowly update the old ones. The information conveyed is the same though.
As always, leave comments with questions… eventually we can get a FAQ section going.