There are people who desperately want this to be untrueđź§µ
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.
Why do identical twins have such similar personalities?
Is it because they're reared together? Is it because people treat them alike due to their visual similarity?
Nope! Neither theory holds water.
Despite looking as similar as identical twins and being reared apart, look-alikes are not similar like identical twins are. In fact, they're no more similar than unrelated people.
This makes sense: they're only minimally more genetically similar than regular unrelated people.
The other thing is that twins reared apart and together have similarly similar personalities.
In fact, there might be a negative environmental effect going on, where twins reared together try to distinguish their personalities more!
Smart people tend to earn higher educations and higher incomes, and to work in more prestigious occupations.
This holds for people from excellent family backgrounds (Utopian Sample) and comparing siblings from the same families!
This is true, meaningful, and the causal relationship runs strongly from IQ to SES, with little independent influence of SES. Just look at how similar the overall result and the within-family results are!
But also look at fertility in this table: quite the reverse!
The reason this is hard to explain has to do with the fact that kids objectively have more similar environments to one another than to their parents.
In fact, for a cultural theory to recapitulate regression to the mean across generations, these things would need to differ!
Another fact that speaks against a cultural explanation is that the length of contact between fathers and sons doesn't matter for how correlated they are in status.
We can see this by leveraging the ages parents die at relative to said sons.
The internet gives everyone access to unlimited information, learning tools, and the new digital economy, so One Laptop Per Child should have major benefits.
The reality:
Another study just failed to find effects on academic performance.
This is one of those findings that's so much more damning than it at first appears.
The reason being, laptop access genuinely provides people with more information than was available to any kid at any previous generation in history.
If access was the issue, this resolves it.
And yet, nothing happens
This implementation of the program was more limited than other ones that we've already seen evaluations for though. The laptops were not Windows-based and didn't have internet, so no games, but non-infinite info too
So, at least in this propensity score- or age-matched data, there's no reason to chalk the benefit up to the weight loss effects.
This is a hint though, not definitive. Another hint is that benefits were observed in short trials, meaning likely before significant weight loss.
We can be doubly certain about that last hint because diabetics tend to lose less weight than non-diabetics, and all of the observed benefit has so far been observed in diabetic cohorts, not non-diabetic ones (though those directionally show benefits).