151 | Jordan Ellenberg on the Mathematics of Political Boundaries

Sean Carroll's Mindscape: Science, Society, Philosophy, Culture, Arts, and Ideas

Sean Carroll | Wondery

Society & Culture, Physics, Philosophy, Science, Ideas, Society

4.8 • 4.4K Ratings

🗓️ 14 June 2021

⏱️ 84 minutes

🔗️ Recording | iTunes | RSS

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Summary

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.

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Transcript

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0:00.0	Hello everyone, welcome to the Mindscape Podcast.
0:02.4	I'm your host, Sean Carroll.
0:04.3	There's something that is very common in physics, as well as in other areas of science,
0:08.9	namely course graining.
0:11.2	This is something that you do when you have a situation where there are many things going
0:15.0	on, perhaps at a microscopic level, and you're not keeping track of all those microscopic
0:19.7	things, right?
0:20.7	You don't know exactly where the molecules of air are in the room or in a cup of coffee
0:25.2	or something like that.
0:26.7	You take many different possible arrangements of the microscopic things, and you group them
0:31.7	together.
0:32.7	You say, this set of arrangements is going to count as one big macroscopic configuration.
0:37.6	This difference that's going to count as a different thing.
0:40.2	It turns out that in representative democracy, something very similar happens, right?
0:45.6	You have many, many people, many, many citizens of the democracy, and it's usually impractical
0:51.8	to imagine that all those people will directly vote on every single issue that comes up in
0:57.5	the country.
0:58.5	That's called direct democracy.
1:00.2	It doesn't really work very well.
1:01.7	It hasn't been tried that often.
1:03.5	But instead, what you do is you make a republic, a representative democracy, right?
1:08.0	You have the individual people vote for representatives.
	...

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