I know just one person over 100 with an actual birth certificate.
Across U.S. states, the total and per capita numbers of supercentenarians dramatically decline right after the introduction of birth certificates (blue line).
Also, have you ever noticed that supercentenarians are more common in areas with more crime, more poverty, and lower average life expectancies?
Here's data for England:
The same pattern of supercentenarian numbers being correlated with poverty holds in (A, D) England, (B, E) France, and (C, F) Japan.
Across countries, you just see the same things over and over, from age heaping to weird correlations, so the conclusion is clear:
Supercentenarian numbers are driven less by regionally exceptional longevity and more by people defrauding pension systems and making up their ages.
Oh, and if you wanted to learn how to live a long life from the "blue zones" in Sardinia, Okinawa, and Icaria, good luck. Those places have low life expectancies and literacy levels, high crime, and lots of poverty.
Their long-lived people are not able to validate their ages.
This also applies to Loma Linda (not all that exceptional of a place).
In fact, across the whole U.S., at least 17% of centenarians were found to be non-centenarians in 2019 when someone just read through two plain-text files and found dates didn't match.
And this also applies to Nicoya, which is riddled with fraudulent ages:
If someone says they know someone super old, ask them: Where were they born? If it's in some place that was poor in the not-too-distant past, then they probably have the wrong age.
There's a popular belief that family wealth is gone in three generations.
The first earns it, the second stewards it, and the third spends it away: from shirtsleeves to shirtsleeves in three generations!
But how true is this belief?
Gregory Clark has new evidence🧵
The first thing to note is that family wealth is correlated across many generations. For example, in medieval England, this is how wealth at death correlates across six generations.
It correlates substantially enough to persist for twelve generations at observed rates of decay:
But why?
The dominant theory among laypeople is social: that the wealth is directly transmitted.
This is testable, and the Malthusian era provides us with lots of data for testing.
The Catholic Church helped to modernize the West due to its ban on cousin marriage and its disdain for adoption, but also by way of its opposition to polygyny.
The origin of this disdain arguably lies with Church Fathers like Justin Martyr, Irenaeus, and Tertullian🧵
Justin Martyr, in his Dialogue with Trypho argues with a Jew that Christians are the ones living in continuity with God's true intentions.
Justin sees Genesis 2 ("the two shall become one flesh") as normative.
In his apologetic world, Christians are supposed to transcend lust.
Irenaeus, in Against Heresies, is attacking Gnostics (Basilides, Carpocrates), whose sexual practices he finds scandalous.
To him, "temperance dwells, self-restraint is practiced, monogamy is observed"—polygyny is a doctrinal and moral deviation from creation affirmation.
The effects of charter schools on student test scores are meta-analytically estimated to be small.
In this study, the largest estimated effect was estimated to be equivalent to ~1.35 IQ points, for mathematics scores, which consistently showed larger effects than reading scores.
Similarly, the estimated effect of parents' preferred schools and of elite public secondary schools on test scores is around zero.
More interestingly, it seems charter school openings lead to competition that marginally boosts non-charter student performance and reduces absenteeism by very small degrees:
This analysis has several advantages compared to earlier ones.
The most obvious is the whole-genome data combined with a large sample size. All earlier whole-genome heritability estimates have been made using smaller samples, and thus had far greater uncertainty.
The next big thing is that the SNP and pedigree heritability estimates came from the same sample.
This can matter a lot.
If one sample has a heritability of 0.5 for a trait and another has a heritability of 0.4, it'd be a mistake to chalk the difference up to the method.