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Detecting Gerrymandering with Mathematical Rigor Lecture Video
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Series Joint School of Mathematics and ACO Colloquium
Time Thursday, February 6, 2020 - 1:30pm for 1 hour (actually 50 minutes)
Location Skiles 005
Speaker Wesley Pegden – Mathematics, Carnegie Mellon University
Organizer Prasad Tetali
In recent years political parties have more and more expertly crafted political districtings to favor one side or another, while at the same time, entirely new techniques to detect and measure these efforts are being developed.
The speaker will discuss a rigorous method which uses Markov chains---random walks---to statistically assess gerrymandering of political districts without requiring heuristic validation of the structures of the Markov chains which arise in the redistricting context. In particular, we will see two examples where this methodology was applied in successful
lawsuits which overturned district maps in Pennsylvania and North Carolina.
The lecture video is now available in Georgia Tech's Institutional Repository, SMARTech.
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- Workflow Status: Published
- Created By: sbarone7
- Created: 02/28/2020
- Modified By: sbarone7
- Modified: 02/28/2020
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