For the past six months or so, I’ve been working on turning my initial computational redistricting prototype into something that can generate congressional districts for full U.S. states. Along the way, I’ve learned a lot about the legal and technical intricacies of redistricting, and I’ve written some code to generate maps (available on GitHub).
The U.S. Supreme Court just released decisions concerning two major gerrymandering cases, Gill v. Whitford (PDF) and Benisek v. Lamone (PDF). Though the cases are related, Gill v. Whitford is the more high-profile and important case; indeed, much of Benisek v. Lamone was concerned with whether or not it was appropriate for lower courts to wait on the precedent of the Gill decision before deciding on Benisek. In both cases, the Court voted unanimously to uphold previously drawn district maps in Wisconsin and Maryland rather than requiring the maps be redrawn.
About a week ago, I was thoroughly surprised and delighted to receive an email from Daniel Gross informing me that I am a spring 2018 AI Grant Fellow. With that status comes many invaluable research resources, including $20,000 of Google Cloud Engine credit.
Gerrymandering, the practice of unfairly allocating congressional districts to maximize a special interest’s electoral advantage, has been in the news a lot lately. This term, the Supreme Court has heard Gill v. Whitford and Benisek v. Lamone, two cases surrounding alleged partisan gerrymandering in Wisconsin and Maryland, respectively, and Pennsylvania’s Supreme Court recently redrew the state’s congressional districts.
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