I have a pretty major update for one of my articles.
It has to do with Justice Jackson's comment that when Black newborns are delivered by Black doctors, they're much more likely to survive, justifying racially discriminatory admissions.
We now know she was wrong🧵
So if you don't recall, here's how Justice Jackson described the original study's findings.
She was wrong to describe it this way, because she mixed up percentage points with percentages, and she's referring to the uncontrolled rather than the fully-controlled effect.
After I saw her mention this, I looked into the study and found that its results all seemed to have p-values between 0.10 and 0.01.
Or in other words, the study was p-hacked.
If you look across all of the paper's models, you see that all the results are borderline significant at best, and usually just-nonsignificant, which is a sign of methodological tomfoolery and results that are likely fragile.
With all that said, I recommended ignoring the paper.
Today, a reanalysis has come out, and it doesn't tell us why the coefficients are all at best marginally significant, but instead, why they're all in the same direction.
The reason has to do with baby birthweights.
So, first thing:
(A) At very low birthweights, babies have higher mortality rates, and they're similar across baby races;
(B) At very low birthweights, babies have higher mortality rates, and they're similar across physician races.
Second thing: Black infants tend to have lower birthweights.
MIxed infants tend to birthweights in-between Blacks and Whites, and there's a mother effect, such that Black mothers have smaller mixed babies than White mothers (selection is still possible)
(A) Black babies with high birthweights disproportionately go to Black doctors;
(B) The Black babies sent to White doctors disproportionately have very low birthweights.
If you control for birthweight when running the original authors' models, two things happen.
For one, they fit a lot better.
For two, the apparently beneficial effect of patient-doctor racial concordance for Black babies disappears:
At this point, we have to ask ourselves why the original study didn't control for birthweight. One sentence in the original paper suggests the authors knew it was a potential issue, but they still failed to control for it.
PNAS also played an important role in keeping the public misinformed because they didn't mandate that the paper include its specification, so no one could see if birthweight was controlled. If we had known the full model details, surely someone would have called this out earlier.
Ultimately, we have ourselves yet another case of PNAS publishing highly popular rubbish and it taking far too long to get it corrected.
Let me preregister something else:
The original paper will continue to be cited more than the correction with the birthweight control.
The public will continue to be misled by the original, bad result. PNAS should probably retract it for the good of the public, but if I had to bet, they won't.
So people like Justice Jackson will continue to cite it to support their case for racial discrimination.
They'll continue doing that even though they're wrong.
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).
The reason why should teach us something about commitment
The government there has previously attempted crackdowns twice in the form of mano dura—hard hand—, but they failed because they didn't hit criminals hard enough
Then Bukele really did
In fact, previous attempts backfired compared to periods in which the government made truces with the gangs.
The government cracking down a little bit actually appeared to make gangs angrier!
You'd have been in your right to conclude 'tough on crime fails', but you'd be wrong.
You have to *actually* enforce the law or policy won't work. Same story with three-strike laws, or any other measure
Incidentally, when did the gang problems begin for El Salvador? When the U.S. exported gang members to it
Diets that restrict carbohydrate consumption lead to improved blood sugar and insulin levels, as well as reduced insulin resistance.
Additionally, they're good or neutral for the liver and kidneys, and they don't affect the metabolic rate.
Carbohydrate isn't the only thing that affects glycemic parameters.
So does fat!
So, for example, if you replace 5% of dietary calories from saturated fat with PUFA, that somewhat improves fasting glucose levels (shown), and directionally improves fasting insulin:
Dietary composition may not be useful for improving the rate of weight loss ceteris paribus, but it can definitely make it easier given what else it changes.
Those non-metabolism details may be why so many people find low-carb diets so easy!