People I (Mostly) Admire Is There a Fair Way to Divide Us? (Update)
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Oct 18, 2025 Moon Duchin, a mathematics professor at the University of Chicago, passionately connects geometry with the challenges of gerrymandering. She explores why fair elections are so tricky, defines key concepts like packing and cracking, and discusses the implications of residential segregation on representation. Duchin introduces innovative mathematical methods like Markov chain sampling to identify gerrymanders and evaluates potential voting system reforms, such as ranked-choice voting, to promote fairness. Her work inspires a fresh perspective on democracy.
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Districting Space Is Vast And Unintuitive
- The space of possible districting plans is astronomically large, far beyond intuitive counts.
- Math methods are needed to sample representative plans and create a baseline for fairness testing.
Sampling Plans With Smarter Random Walks
- Markov-chain sampling walks through districting plans by making small changes repeatedly.
- Duchin's team developed bigger moves (fuse-and-redraw) to explore plan space more efficiently.
Use Ensembles To Spot Outliers
- Ensemble analysis produces a distribution of plausible plans to compare against a proposed map.
- If the proposed plan is an extreme outlier, that suggests intentional manipulation.
