151 | Jordan Ellenberg on the Mathematics of Political Boundaries

151 | Jordan Ellenberg on the Mathematics of Political Boundaries

Any system in which politicians represent geographical districts with boundaries chosen by the politicians themselves is vulnerable to gerrymandering: carving up districts to increase the amount of seats that a given party is expected to win. But even fairly-drawn boundaries can end up quite complex, so how do we know that a given map is unfairly skewed? Math comes to the rescue. We can ask whether the likely outcome of a given map is very unusual within the set of all possible reasonable maps. That's a hard math problem, however — the set of all possible maps is pretty big — so we have to be clever to solve it. I talk with geometer Jordan Ellenberg about how ideas like random walks and Markov chains help us judge the fairness of political boundaries.

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Jordan Ellenberg received his Ph.D. in mathematics from Harvard University in 1998. He is currently the John D. MacArthur professor of mathematics at the University of Wisconsin. He competed in the International Mathematical Olympiad three times, winning a gold medal twice. Among his awards are the MAA Euler Book Prize and a Guggenheim Fellowship. He is the author of How Not to Be Wrong and the novel The Grasshopper King. His new book is Shape: The Hidden Geometry of Information, Biology, Strategy, Democracy, and Everything Else.


Jaksot(417)

304 | James Evans on Innovation, Consolidation, and the Science of Science

304 | James Evans on Innovation, Consolidation, and the Science of Science

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303 | AMA | February 2025

303 | AMA | February 2025

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302 | Chris Kempes on the Biophysics of Evolution

302 | Chris Kempes on the Biophysics of Evolution

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301 | Tina Eliassi-Rad on Al, Networks, and Epistemic Instability

301 | Tina Eliassi-Rad on Al, Networks, and Epistemic Instability

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13 Tammi 20251h 9min

300 | Solo: Does Time Exist?

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Holiday Message | Hits and Misses

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23 Joulu 20242h 1min

299 | Michael Wong on Information, Function, and the Origin of Life

299 | Michael Wong on Information, Function, and the Origin of Life

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