Yesterday was so fun, but hectic! I gave a talk on http://redistrict.science [preprint: https://arxiv.org/abs/1711.04640 ] and it was also coincidentally #GISday. I was focussing on how I did what I did using Javascript, Cython, C, Python, GIS, etc. Today I'd like to talk about the science.
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What we found is that not all gerrymandering is purposeful. It arises because states are hard to redistrict, especially larger states. The more districts a state has the more it is likely to be gerrymandered. [maps: http://redistrict.science — preprint: https://arxiv.org/abs/1711.04640 ]pic.twitter.com/MgRWq0rwWj
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The redder a state is the more our method improvesd it. As you can see from the map (and based on analyses we did), bigger/more populous states are redder. Interactive maps can be found at: http://redistrict.science and the preprint: https://arxiv.org/abs/1711.04640 has many more details.pic.twitter.com/AeESSkcidx
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Take top row [taken from the preprint https://arxiv.org/abs/1711.04640 ], that's Iowa (a), our algorithm (b) improves on it, even tho they are trying their best. That's the thing! Even when it's done by impartial committees, computers still district better! More: http://redistrict.science pic.twitter.com/1oYxiAMbMK
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Replying to @o_guest @sarahdcady
I kind of question this. The Iowa system only looks in any way wonky because the state prioritizes maintaining continuity of existing political boundaries (counties, and cities and townships at the state district level). Not really better, just different priorities.
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Replying to @o_guest @sarahdcady
I’m kind of curious how your algorithm handles the creation of minority majority districts as required by the Civil Rights Act? Do you have partisan modeling using prior cycle elections? Seems like prioritizing urban grouping is going to create D districts with huge
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Replying to @tedger @sarahdcady
@DrLoveBC and address this in the Discussion section of the preprint: https://arxiv.org/abs/1711.046402 replies 0 retweets 1 like
that should have been "and I" 
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