There are people who desperately want this to be untrue🧵
One example of this came up earlier this year, when a "Professor of Public Policy and Governance" accused other people of being ignorant about SAT scores because, he alleged, high schools predicted college grades better.
The thread in question was, ironically, full of irrelevant points that seemed intended to mislead, accompanied by very obvious statistical errors.
For example, one post in it received a Community Note for conditioning on a collider.
But let's ignore the obvious things. I want to focus on this one: the idea that high schools explain more of student achievement than SATs
The evidence for this? The increase in R^2 going from a model without to a model with high school fixed effects
This interpretation is bad.
The R^2 of the overall model did not increase because high schools are more important determinants of student achievement. This result cannot be interpreted to mean that your zip code is more important than your gumption and effort in school.
If we open the report, we see this:
Students from elite high schools and from disadvantaged ones receive similar results when it comes to SATs predicting achievement. If high schools really explained a lot, this wouldn't be the case.
What we're seeing is a case where R^2 was misinterpreted.
The reason the model R^2 blew up was because there's a fixed effect for every high school mentioned in this national-level dataset
That means that all the little differences between high schools are controlled—a lot of variation!—so the model is overfit, explaining the high R^2
This professor should've known better for many reasons.
For example, we know there's more variation between classrooms than between school districts when it comes to student achievement.
Trump says his secret weapon in the fight to reform institutions of higher learning (38 USC § 3452(f)) is accreditation
He would actually gain a lot by deploying another weapon. This weapon is no secret to Democrats, but Republicans have only rarely used it
The weapon is data🧵
SFFA v. Harvard was a landmark case by the U.S. Supreme Court, wherein it was found that Harvard had been engaging in racially discriminatory admissions in violation of the law.
Per the court's decision, universities do not have the right to consider race during admissions.
SFFA v. Harvard was first filed in 2013 and the case was ultimately decided in 2023.
It took ten full years to decide against Harvard, even though the evidence that they discriminated in favor of Black students was shockingly obvious and insurmountable.
The picture looks much the same as the one last year🧵
When you rescale these curves by the numbers who took the test, you get this:
If you subset to the states where basically all high school students take the test (the "Representative" sample), the picture looks highly similar to the national one:
I just got done listening to Rogan's interview of Vance
It was substantive, and it is nice to hear that Vance would bring a lot of reasonability to the Trump White House if elected
Due to how long the interview was, it also showed off Vance's unusual-for-a-Republican priorities
To be frank, Vance is a Christian Democrat from 2008.
His views are basically just rejecting recent, wacky things and wanting a state that stays out of the way of the healthy, while providing extensive services for the unhealthy.
Vance focuses a lot on mental health, drug addiction, and people who he believes might only be temporarily struggling.
This makes total sense if you know about how disturbingly bad his early life was, and how it was plagued by drug addiction and poverty problems.
I'm not going to rig an ongoing poll by linking directly to it, but I will say that >90% of respondents so far were wrong:
The answer is climate🧵
Anatomically modern humans first appeared around 200,000 years ago.
After a few false starts, the dawn of man took place with a series of dispersions out of Africa about 60,000 years ago.
By 40-50 thousand years ago, humans had made it most places, and by 10-20, to the Americas
Practically all of that time dispersing took place as hunter-gatherers.
Specifically, nomadic hunter-gatherers. The real advent that made agriculture possible wasn't changing the mode of subsistence per se, but changing to sedentism.
What does labor-saving technology do to workers? Does it make them poor? Does it take away their jobs?
Let's review!
First: Most papers do support the idea that technology takes people's jobs.
This needs qualified.
Most types of job-relevant technology do take jobs, but innovation is largely excepted, because, well, introducing a new innovation tends to, instead, give employers money they can use to hire people.
But if technology takes jobs, why do we still have jobs?
Simple: Because through stimulating production and demand, it also reinstates laborers!
This is supported by the overwhelming majority of studies:
I just read one of the most interesting climatic reconstructions I've ever seen.
This one gives us temperature records for the last 485 MILLION years.
The reconstruction is based on a lot of different methods, but the one that really stood out was the part where they leveraged the shell chemistry of single-celled organisms' fossils.
Wild that this is possible and someone thought of it!
With these little organisms' data in hand, it's possible to obtain a high-fidelity picture of the past in which we emerged on the global scene.
That picture is one that averages much, much colder than basically any other period in time.