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by rarefied_tomato 1990 days ago
I can get behind statistical and CS concepts being used to detect gerrymandered districts. There's a whole related field of anomaly detection.

My quackery sense tingles when I hear NP-completeness was mentioned in the argument. Do you have more info on the claimed relevance to gerrymandering?

1 comments

Of course, you can find the full explanation in the amicus brief: https://www.brennancenter.org/sites/default/files/legal-work...

It is NP complete in determining to an absolute degree that a redistricting plan is excessively unfair, as the number of possibly districts grows exponentially. Demonstrating to a quantitative degree is more clear (eg stop drawing more maps after a few billion).

I highly recommend anyone interested read at least the summary of the above brief, but relevant details from page 4 are reproduced:

"With modern computer technology, it is now straightforward to (i) generate a large collection of redistricting plans that are representative of all possible plans that meet the State’s declared goals (e.g., compactness and contiguity); (ii) calculate the partisan outcome that would occur under each such plan, based upon actual precinct-level votes in one or more recent elections; (iii) display the distribution of the outcomes across these plans; and (iv) situate the State’s chosen plan along that continuum to reveal the degree to which that plan is an outlier. One can analyze outcomes for a statewide plan as a whole, or for an individual district within a plan. In this way, it is now straightforward to measure the quantitative degree to which a partisan gerrymander is excessive."

I'll check it out. Thanks!

Edit: I didn't find anything in that particular resource. A similar work mentioning complexity is here: https://desh2608.github.io/static/report/ohio.pdf

Roughly, it boils down to a constrained search for the best mapping of precincts into districts, which is NP-hard.