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I’d be interested in an interactive version of this where you could assign a percentage of those votes to the person who lost the state as a naive proxy for “what would have happened if the people who thought their vote didn’t matter because [D|R] would win anyway”. I know it wouldn’t be an actual measure but it’d be fun to mess with anyway.

In particular I find it kinda interesting that CA and TX are both didn’t vote and both historically considered “easy wins”

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jj4211@lemmy.world ⁨1⁩ ⁨day⁩ ago
I think you are on to something, but I’d say it actually largely deflates the ‘people didn’t vote and if they had, maybe the outcome would have been different’ narrative.

“Did not vote” rules in non-swing states. I wager that, for example, most people didn’t vote in california not because they see their candidate as a lost cause, but because they know “their” candidate has carried the state for sure.

So in a shift to proportional electoral vote or popular vote, you’d probably get a lot more voters engaged in California, Hawaii, NY, and pick up democrat votes but you’d also get more red voters from Alaska, Texas, Utah, Kansan, Oklahoma, Arkansas, Alabamba, Tennesse… etc… I’m not sure which group manages to bring out more non-voters in that scenario…

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- qqq@lemmy.world ⁨1⁩ ⁨day⁩ ago
  
  I wager that, for example, most people didn’t vote in california not because they see their candidate as a lost cause, but because they know “their” candidate has carried the state for sure.
  
  That’s a natural interpretation as well. I wonder if it’d be possible to at least guess at whether it was that or “my person won’t win so what’s the point”. There are probably so many other factors. For example the “did not vote map” looks surprisingly similar to the SOVI map: www.atsdr.cdc.gov/…/svi-interactive-map.html
  
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