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
Love GIS so thanks for posting. In what way do you see Iowa's improved? Specifically, why is it better to put Ames with Des Moines?
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Only under the definition of improvement as we use it in the preprint. https://arxiv.org/abs/1711.04640
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