> That's not what he's asking. He's asking why there apparently isn't a standard process to locate and clean missing data through investigation, assuming that's the issue.
If that's what he was trying to ask, then I have, as detailed above, some notes on the attempt. But the myth that Social Security numbers were ever designed to work even half-assedly well as a single national ID number will never die, I suppose.
> Bear in mind that social security fraud is a major problem in many countries and impossibly old people is a usual indicator. The famous "blue zones" that were once studied for their long lived people are now believed to mostly be an artifact of undetected pensions fraud.
I can't really evaluate Newman's preprint [1] with much confidence, but it's only been out since September, and the Ig Nobel isn't peer review. Given also that the US state with the largest count of "supercentennarians" in Newman's data, Iowa, has a whopping 37 [2] of them, you're stretching this piece of un-peer-reviewed research far past anything it could reasonably be asked to support - hence, I suspect, the "are now believed" passive-voice weaseling in your claim quoted above.
[2] As given "1.25e-05" (p. 5, ibid.) or 12.5 per million, for a population just over three million. I've taken the liberty of rounding down on the assumption we are not meant to be counting fractional supercentennarians.
SSNs were designed to act as a national ID number for the purposes of the social security system. It's in the name. Why are you describing this as a "myth"? Do you think the people who designed that system sat down and said, right boys, how can we half-ass this?
Peer review hardly means anything in these sorts of fields but seeing as you asked, the same guy has previously published peer-reviewed papers on fraud in Blue Zones research. Here's a press release with some references:
> Dr Newman has previously disproved a 2016 study published in Nature on extreme-age research that accidentally rounded off a substantial amount of its data to zero. His peer-reviewed paper demonstrated that if corrected, this error eliminated the core findings claiming that human lifespan had a defined limit. Then, Dr Newman also countered a 2018 paper which made the opposite claim and, in the process, demonstrated a theoretical result predicting that patterns in old-age data are likely to be dominated by errors.
In investigating this theory, Dr Newman demonstrated fundamental and comedic mismatches between longevity claims and observed patterns. In the process, Dr Newman revealed that the well-publicised “Blue Zones” claims for the secrets of longevity are infallibly flawed.
Dr Newman showed that the highest rates of achieving extreme old age are predicted by high poverty, the lack of birth certificates, and fewer 90-year-olds. Poverty and pressure to commit pension fraud were shown to be excellent indicators of reaching ages 100+ in a way that is ‘the opposite of rational expectations’.
If that's what he was trying to ask, then I have, as detailed above, some notes on the attempt. But the myth that Social Security numbers were ever designed to work even half-assedly well as a single national ID number will never die, I suppose.
> Bear in mind that social security fraud is a major problem in many countries and impossibly old people is a usual indicator. The famous "blue zones" that were once studied for their long lived people are now believed to mostly be an artifact of undetected pensions fraud.
I can't really evaluate Newman's preprint [1] with much confidence, but it's only been out since September, and the Ig Nobel isn't peer review. Given also that the US state with the largest count of "supercentennarians" in Newman's data, Iowa, has a whopping 37 [2] of them, you're stretching this piece of un-peer-reviewed research far past anything it could reasonably be asked to support - hence, I suspect, the "are now believed" passive-voice weaseling in your claim quoted above.
[1] https://www.biorxiv.org/content/10.1101/704080v3
[2] As given "1.25e-05" (p. 5, ibid.) or 12.5 per million, for a population just over three million. I've taken the liberty of rounding down on the assumption we are not meant to be counting fractional supercentennarians.