There is a widespread myth that the obesity epidemic started in or around 1980.
This is based on a misunderstanding of the relationship between body fat percentage and BMI, which is used to classify someone as "obese".
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You can see this nonlinearity replicate in numerous contexts.
For example here it is in the Heritage Family Study.
The distribution of BMIs shifts right as bodyfat percentages increase across the distribution, but the mean and variance increase faster than body fatness does due to that nonlinearity, which shows up because it's part of how BMIs are constructed.
I simulated 100,000 people to show how often people are "thrice-exceptional": Smart, stable, and exceptionally hard-working.
I've highlighted these people in red in this chart:
If you reorient the chart to a bird's eye view, it looks like this:
In short, there are not many people who are thrice-exceptional, in the sense of being at least +2 standard deviations in conscientiousness, emotional stability (i.e., inverse neuroticism), and intelligence.
To replicate this, use 42 as the seed and assume linearity and normality
In Singapore, they use corporal punishment so that captured criminals can be rapidly released. When criminals are caned, kidney pads are attached to them, they're tied to a trestle, and then they're struck with a hard rod.
Graffiti? Eight strikes.
You just vandalized a set of walls and you've been given the choice between two punishments.
First choice: Go to prison for one year.
Second choice: Received 24 hits from the cane.
What do you personally choose?
Which option do you believe that other good people who stupidly got involved in a crime would pick?
Male and female biology PhDs without children are similarly likely to have tenure-track jobs after they receive their PhDs.
Males may get slightly ahead, but not enough to explain the sex gap in tenure🧵
To understand the larger gap in tenure-tracking, we have to look at the group of biology PhDs with children.
For men, their odds of of being in a tenure-track position just keep going up with the years.
For women, their odds plateau after having kids.
This comparison is subject to some confounding, but you can nevertheless see that the impact of a child on the gap is timed to when the birth of the child happens, suggesting that it really is a causal impact of having a kid.
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: