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G. Elliott Morris Profile picture
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25 Sep, 4 tweets, 2 min read
Nothing in this Kagan essay is new or shocking, but I do find the cohesive packaging useful. The Constitution has no checks against proto-fascist factions abusing multiple branches of government for the pursuit of power. Something has to change—and soon. washingtonpost.com/opinions/2021/…
We have seen multiple crises of the confluence of factionalism & US electoral +other institutions over the last year. Life-threatening covid-19 policy & 1/6 are only the most relevant examples. I have to wonder how bad people think it needs to get before we hit the tipping point.
I think the latter paragraph here from this excellent @jbouie article puts the pieces together very well. A faction of leaders holding power across levels and institutions of government can effectively circumvent the checks and balances of our government nytimes.com/2021/09/24/opi…
I found 280 characters stifling so blogged a bit more about this. I think the interaction of factionalism, identity-driven affective polarization, and right-wing auth-illiberliasm is a unqiely dangerous challenge that is well countered by electoral reform gelliottmorris.substack.com/p/factionalism…

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More from @gelliottmorris

G. Elliott Morris Profile picture
25 Sep
For fuck's sake... My aggregate in CA was 60% Keep Newsom if you just allocated undecideds and corrected for whether polls had the right weighting scheme. That's a 2 point error on vote share! Tiny! This is bad for SOME pollsters, not the industry. Jesus gelliottmorris.substack.com/p/polls-of-cal…
Contrary to popular belief, you don't have to dunk on the polls every time an election result is a little bit surprising to you -- or if you looked at the wrong polling averages
Observing error in a 3rd-party polling average (& 1 that ingested data that was basically withdrawn by a polling house and didn't allocate undecideds!) and then projecting that error onto "polls" as an industry-wide error is a huge analytical misstep IMO.
Read 8 tweets
G. Elliott Morris Profile picture
15 Sep
Aaand there it is folks! Early vote-by-mail results in California's recall election are way ahead of tied-race benchmarks and signal an imminent victory for Governor Gavin Newsom, possibly by high double digits. I'm going to bed early tonight livevoterturnout.com/sandiegoca/Liv…
Listen to the (good) polls, folks!
where is my award for beating dave by one hundred and twenty thousand microseconds
Read 4 tweets
G. Elliott Morris Profile picture
14 Sep
At this point, given the CA recall polling and VBM data, all we're looking for in the early vote tonight is confirmation of projected partisan distributions. Returned ballots are sufficiently Dem that we just need to assess loyalty + turnout. LA county VBM +25 Newsom would do it.
The very fuzzy math here is that early mail ballots statewide (+40) were about 10 points more pro-Biden than the final results (+30) in California in 2020, and LA County (+45) was about 15 pts more Biden than the whole state. So +55 early LA = +30 CA-wide in the end. +25 = tied.
You don't call an election just based on one county, of course. But Los Angeles cast 25% of CA's votes in 2020 so it's a good guide.

Other VBM benchmarks could be:

Recall +11 in Orange County (+19D 2020 VBM = 30 overall :: -11D VBM = 0)
Keep +3 in SD (+33D VBM = 30 :: 3D = 0)
Read 4 tweets
G. Elliott Morris Profile picture
14 Sep
Blog post: Media coverage of California's recall election highlights big issues with popular poll aggregation models

gelliottmorris.substack.com/p/polls-of-cal…

FiveThirtyEight and RealClearPolitics are unable to capture modern outliers or the impacts of non-response & different weighting schemes
Expanding on what I've been saying here and elsewhere
Regardless of what happens in the election, the bottom line is that modern statistical methods can provide better analyses of polling data than the stuff available ten years ago, especially (but not only) because of recent problems in the polling industry. Time to do better.
Read 4 tweets
G. Elliott Morris Profile picture
13 Sep
Here's my final update to this model of California recall polls. I'm calculating an aggregate that adjusts polls based on whether they use partisanship in their weighting schemes, and draws different trends for adjusted v unadjusted data. Newsom +18 +/- 10
gist.github.com/elliottmorris/…
The point of this project was to illustrate the different methods we can use to aggregate polling data — esp in how to improve existing popular averages that don't peer under the hood of how pollsters are processing their data, an increasingly important aspect of public polling.
So, note two things:

1. Popular averages magnify unlikely trends in public opinion by being whipsawed by data that is subject to higher standard errors than a decade ago (when the models were first made). Weighting by party flattens trends by decreasing nonresponse
Read 5 tweets
G. Elliott Morris Profile picture
9 Sep
The thing about Rasmussen (and to a lesser extent, some other right-leaning pollsters and aggregators) is that the conservative information ecosystem has provided a top-dollar audience for confirmation bias, and there's not much AAPOR or good political journos can do about it.
538 could start by banning them, though
add this to the pile
Read 4 tweets

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