Assistant professor @DukePoliSci https://xitter.cf/t.co/p2zcpB8UBE
Joined February 2012
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Jon Green retweeted
A few notes, we give you the chance to build your own forecast going back to 1946. If you think there is another polling error like in 2016, or want to see what the model would say in 1956, try all these possibilities, make your own modeling decisions, and see the numbers change!
New 2026 US House & Senate election forecasts, using all political science knowledge we could systematize, & our statistical methods from “If a Statistical Model Predicts That Common Events Should Occur Only Once in 10,000 Elections, Maybe It’s the Wrong Model” with @DannyCEbanks and @Jonathan_N_Katz. GaryKing.org/electit
We make these forecasts available (including all the input data, methods, and procedures), not only for their possible public interest, but because academics learn by making themselves vulnerable to being proven wrong. We will make no changes to our post-primary forecasts (which do not use polls) but will update two other sets on this site incorporating poll results as new ones appear. Comments on the paper or forecasts are welcome!
Jon Green retweeted
New 2026 US House & Senate election forecasts, using all political science knowledge we could systematize, & our statistical methods from “If a Statistical Model Predicts That Common Events Should Occur Only Once in 10,000 Elections, Maybe It’s the Wrong Model” with @DannyCEbanks and @Jonathan_N_Katz. GaryKing.org/electit
We make these forecasts available (including all the input data, methods, and procedures), not only for their possible public interest, but because academics learn by making themselves vulnerable to being proven wrong. We will make no changes to our post-primary forecasts (which do not use polls) but will update two other sets on this site incorporating poll results as new ones appear. Comments on the paper or forecasts are welcome!
Jon Green retweeted
Listening to @UpFirst podcast increases trust in podcast news + NPR but that doesn’t spill over into trust in news more generally. Glad this paper w/ @junghwanyang @simonsaysnothin @p_barbera is out!
Randomizing uptake of NPR's @UpFirst podcast for 5 days increases news consumption & knowledge of events (esp. among more right-leaning voters), trust in NPR, etc but not trust in the news more generally; no effect on attitudes or political beliefs. An @andyguess et al. joint
chevy didn't make a 327 in '55, the 327 didn't come out until '62
Jon Green retweeted
We are excited to announce the schedule for SoWEPS-11, the Southern Workshop in Empirical Political Science, held at Duke on October 29–30! 🎉 Check out the full program below and register here: docs.google.com/forms/d/e/1F…
Jon Green retweeted
Kimberly Guilfoyle’s traveling stylist, Fancy James, is an immediate first ballot hall of fame minor Trump world character
Inside Kimberly Guilfoyle’s Final Days as Ambassador to Greece wsj.com/politics/policy/kimb…
Jon Green retweeted
📢New paper in @The_JOP on the reciprocal nature of citizens’ support for democratic transgressions.
We show that citizens reciprocate undemocratic behavior: When confronted with violations by political opponents, citizens’ support for transgressions by their own side doubles
Jon Green retweeted
There's a story going around: after the drone strikes on Yandex data centres, comments on AfD and MAGA accounts collapsed.
We monitor 17,000+ politicians, media and civil society accounts in 30+ countries. 50,000+ posts a day.
So we checked.
We don't see it. 🧵
Jon Green retweeted
🚨New paper🚨out in @SocMedSoc w/ John Wagner and @jennifer_oser 🎉
We all know who's a political influencer on social media, right? Well... we may THINK we do, but what we're actually measuring is very different. How different? 🧵👇
models getting better at writing code and worse at writing-writing was arguably one of the better-case scenarios for social science tbh
AI can do essentially all the technical parts of empirical social science research now---but there's still an essential role for human researchers and universities.
It's been 9 months since we started exploring how AI was going to transform empirical social science research. Here's a periodic update on how my thinking has evolved since then:
(1) The most powerful AI models, including the kinds of multi-agent systems delivering recent math results, are now capable of doing essentially any kind of technical empirical social science research you could desire. I no longer write any data collection, munging, or analysis code directly.
(2) Norms are evolving slower than I expected, but it is increasingly seen as weird if someone posts a working paper without evidence that they have used AI to verify that the results are directly reproducible with their code and data. This is a great sign.
(3) AI has, if anything, gotten WORSE rather than better at writing. As a result, the best papers combine AI-driven empirical analyses with human writing (though AI is quite helpful for things like managing bibliographies, finding relevant web links, etc).
(4) Human direction is still essential for pointing AI at the most interesting and most valuable empirical questions, and for interpreting the results, making sense of them, and communicating them.
We are going to need institutions that are independent of the labs that can verify knowledge claims and direct AI-driven research towards the most fundamental questions of knowledge that AI labs won't be positioned to pursue effectively themselves. This is a tremendous opportunity for places like Stanford, and I'm excited to see how it evolves.
vote share is a continuous variable
Sorry, no, winning in Michigan in a D+9 year does not show you can win anywhere.
A Dem majority requires wins in Alaska, Texas, and other states that El-Sayed would lose even in a very friendly year.
slowboring.com/p/an-honest-f…
Jon Green retweeted
I see some people treating this post as evidence Trump wasn't taken out of context in the previous speech. In fact, this post even *more* obviously takes him out of context.
This time, Trump said right after this comment, "We're not gonna let that happen. We protect our cities, we protect our country." (Rupar's post includes that comment, but the caption doesn't). And right before this comment, Trump was talking about how oil prices are not as high as people thought the war would send them. In other words, he was, as he has on previous occasions, contrasting the big damage Iran could (supposedly) do to cities with a nuclear weapon with the (supposedly) minimal harm of the war.
Here are the full relevant remarks. (Critics are free to call them inappropriate, but people should see the entire monologue.)
"And just as I promised, I am ensuring that Iran will never have a nuclear weapon...Never. They know that. They know that. And we'll be out of there soon. And you watch those oil prices come down like a rock, and watch everything; everything else is coming down. Oil is coming down. You know, we pay less than oil, and we did that whole thing with - because that was a big operation that should have been done by past presidents for many years. It should have been done, but nobody wanted to take it on. We had no choice. Because we can't let them have a nuclear weapon. And I'll tell you what. Oil: a little more, maybe more than a little, but a lot of people thought it'd be 3, 4, 5 times that. When I went in, I thought it could be much higher than that. But we are paying less than under the Biden administration; he didn't do anything. He gave you the highest inflation in history. He didn't do anything. But you want to see trauma? You want to see problems? And I said it the other day: Let them hit a missile into San Diego or Los Angeles. On the way - let them hit - you want to see a horror show? You want to see problems? Let them hit San Diego. Let them hit Los Angeles. And you want to see some bad things happen, you want to see a country that would be in freefall. We're not going to let that happen. We protect our cities, we protect our country. We're not letting that happen. And they'd use it too. They'd use it. They would use it."
xitter.cf/atrupar/status/2107987…
Jon Green retweeted
a new paper forthcoming in British Journal of Political Science!
we use a novel choice task to estimate values in the Schwartz Value Space and study how these values structure political preferences among kids, one of their parents, and a U.S. sample.
