Geoff Allen

The Underclass Is in Session What do we see when we view the structure of academic labor as it is, not as we wish it to be?

Here’s the online version. The whole issue, “What is Academic Labor Now?” is deeply important.

Ethnonationalism is intrinsically utopian in a general sense; it is aesthetics mistaken for effective real-world politics, it is what happens when collective narcissism leads people to overestimate the extent to which common categorical identity is responsible for social order. (1/n)

Jordan Ott has got to figure out how to respond to bigger lineups. The Achilles heel of this Suns team, and being exploited more and more by the smart teams around the league.

The political effects of X's feed algorithm https://doi.org/10.1038/s41586-026-10098-2 Received: 16 December 2024 Accepted: 4 January 2026 Published online: 18 February 2026 Open access • Check for updates Germain Gauthier,5, Roland Hodler?5, Philine Widmer35 & Ekaterina Zhuravskaya3,4,5 m Feed algorithms are widely suspected to influence political attitudes. However, previous evidence from switching off the algorithm on Meta platforms found no political effects'. Here we present results from a 2023 field experiment on Elon Musk's platform X shedding light on this puzzle. We assigned active US-based users randomly to either an algorithmic or a chronological feed for 7 weeks, measuring political attitudes and online behaviour. Switching from a chronological to an algorithmic feed increased engagement and shifted political opinion towards more conservative positions, particularly regarding policy priorities, perceptions of criminal investigations into Donald Trump and views on the war in Ukraine. In contrast, switching from the algorithmic to the chronological feed had no comparable effects. Neither switching the algorithm on nor switching it off significantly affected affective polarization or self-reported partisanship. To investigate the mechanism, we analysed users' feed content and behaviour. We found that the algorithm promotes conservative content and demotes posts by traditional media. Exposure to algorithmic content leads users to follow conservative political activist accounts, which they continue to follow even after switching off the algorithm, helping explain the asymmetry in effects. These results suggest that initial exposure to X's algorithm has persistent effects on users' current political attitudes and account-following behaviour, even in the absence of a detectable effect on partisanship.

A new paper shows that less than 2 months of exposure to Twitter’s algorithmic feed significantly shifts people’s political views to the right.

Moving from chronological feed to the algorithmic feed also increases engagement.

This is one of the most concerning papers I’ve read in awhile.

Shock Values: Prices and Inflation in American Democracy by Carola Binder (Forthcoming Article)

Forthcoming book review in the JEL: "Shock Values: Prices and Inflation in American Democracy by Carola Binder" by Michael D. Bordo.

Democrats are +22 on the generic ballot among independents in YouGov's latest survey. They are doing well with engaged voters and running ~even with people who don't follow news, a big shift left since 2024 ( www.gelliottmorris.com/p/trump-lost...)

that's right wall st journal

Thousands of institutions abandoned programs, ended or rewrote scholarships, closed down clubs and publications, all in pre-emptive compliance.

And you know why?

Mostly because they wanted to do it if they thought they could blame someone else for it.

The Rise of Skywalker has the worst ending of a movie I have ever experienced.

This article is frustrating to me because it is a bad faith effort at explaining what might be an actual concern.

Article: The political effects of X’s feed algorithm Abstract: Feed algorithms are widely suspected to influence political attitudes. However, previous evidence from switching off the algorithm on Meta platforms found no political effects1. Here we present results from a 2023 field experiment on Elon Musk’s platform X shedding light on this puzzle. We assigned active US-based users randomly to either an algorithmic or a chronological feed for 7 weeks, measuring political attitudes and online behaviour. Switching from a chronological to an algorithmic feed increased engagement and shifted political opinion towards more conservative positions, particularly regarding policy priorities, perceptions of criminal investigations into Donald Trump and views on the war in Ukraine. In contrast, switching from the algorithmic to the chronological feed had no comparable effects. Neither switching the algorithm on nor switching it off significantly affected affective polarization or self-reported partisanship. To investigate the mechanism, we analysed users’ feed content and behaviour. We found that the algorithm promotes conservative content and demotes posts by traditional media. Exposure to algorithmic content leads users to follow conservative political activist accounts, which they continue to follow even after switching off the algorithm, helping explain the asymmetry in effects. These results suggest that initial exposure to X’s algorithm has persistent effects on users’ current political attitudes and account-following behaviour, even in the absence of a detectable effect on partisanship.

Figure 2. ITT estimates of feed-setting changes on engagement and political attitudes. ITT effect estimates of switching the algorithm on and off (in s.d.). Left, effect of moving from the chronological to the algorithmic feed for users initially on the chronological feed. Right, effect of moving in the opposite direction for users initially on the algorithmic feed. For each outcome, the results of two specifications are reported. Blue, unconditional estimates with robust s.e., controlling only for the initial feed setting and, where applicable, pre-treatment outcome levels. Orange: conditional estimates, controlling for pre-treatment covariates using GRFs; 90% and 95% CIs are reported. Numerical effect sizes and P values correspond to the conditional estimates (all tests are two-sided). The unit of observation is respondent. From top to bottom, sample sizes are n = 4,965, n = 3,337, n = 4,965, n = 4,965, n = 4,596, n = 4,596 and n = 4,850. Tests are described in Methods. Supplementary Information Table 2.16 reports the exact numerical point estimates, s.e., CIs and sample sizes for every specification. All outcomes are standardized. Additional results are presented in Supplementary Information section 2. PCA, first principal component from principal component analysis.

X's algorithm is in fact doing what you think it's doing. www.nature.com/articles/s41...

Abstract Academic freedom is an unusual and complex set of norms and practices. It arises out of the combination of the corporate self-governance of medieval universities and the spirit of disciplinary scientific inquiry in modern research universities. It combines a principle of antiorthodoxy as to conclusions with the robust associational self-governance of scholarly communities whose members evaluate one another as participants in that shared enterprise. It has never been easily or wholly embraced by wider societies; today it is under wholesale attack. This article combines conceptual, normative, and historical analyses of academic freedom as a general norm with attention to conflicts over it in the mid-to-late 2010s and early 2020s. Some genuinely hard cases and questions tested the meaning of academic freedom and university values well before the current crisis.

Now posted ahead of print:

"Conceptualizing Academic Freedom," forthcoming, Annual Review of Political Science.

(Uncorrected proofs, so a few minor edits different from the version that will be published in June.)

doi.org/10.1146/annu...

The History of China by Chris Stewart. Similar depth, though because he's covering all of China's dynasties and pre-dynasties it is a little more 10000 feet in nature.

John Lone is so good in that.

The Fresh Princip, perhaps?

The pace at which US wealth concentration is rising is simply staggering

The concentration of AI wealth into the hands of a few tech barons + plutocratic capture ==> unchartered territory

You're in my neck of the woods! Enjoy the nice weather!

He looked a bit rushed for no reason at the end there. Just got a bit nervy.

They were at least on a roster...

What are people's thoughts about the best book on why Reconstruction failed? I'm trying to put together a reading list for a class.

Exactly. Say whatever you want about Che's beliefs and behaviors, he was committed and put it all on the line for those beliefs. Hasan has done nothing comparable. How one even gets to that comparison is beyond me.

But also, like, that's a NUTS comparison.

Always great to hear Rob Watson of the BBC call Reform a center right party... /s

Top 5 states, anti-Trump/ICE protest crowd size
MA, DC*, CA*, MN*, WA
*Occupied by ICE/Troops (also IL, NC, OR)

Top red states (nearly tied)
UT (532), MT (522)

Outlier state
NJ (likely attended in NY/PA)

Crowd size correlated w/ urbanized pop. (r=.47, p<.01)

Data source: @chenoweth.bsky.social

With AI, it soon could!

The movement is extraordinarily disciplined, despite escalatory rhetoric, threats, & violence against the movement, immigrants, and observers. Over 99% of reported protests featured no arrests, 99.8% had no participant injuries or property damage, and 99.9% reported no injuries to law enforcement.

Republican parties in the Southwest are not exactly drawing from the top of the file anymore.

You get used to it. I have number 3 coming up.