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I've started listening to SCOTUS oral arguments as a podcast, and some of my consistent complaints are the lack of statistical literacy, and some justices really wanting to lean on "scientists" as an unelected fourth branch of government.
I think your suggestion here is the right one: let Congress interpret the science in writing laws; don't have the Judicial branch try to do scientific literature reviews.
It's not like we don't have lots of evidence of negligent or even outright fraudulent publications in even reputable journals.
A $50,000,000,000 bill on the sidewalk is empowering Cremieux Recoil (or, humbly, moi, or several other candidates, or a committee composed thereof), to make a statistics exam which is administered to currently empowered decision makers. Those who fail after being provided 1 year to study for it are exiled. It will never happen because we live in an idiocracy, but one can dream.
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There was a meta analysis done once that showed about 50% of peer reviewed papers turn out to be false. If you look at something like PubMed epidemiological literature, a lot of it is riddled with multicollinearity that severely impacts the precision of their regression estimates. This was actually acknowledged in findings of their own studies. But it generalizes across disciplines. You find it in Neoclassical economics where models have been repeatedly subjected to different datasets and the existing structure falls completely apart.
This is the replication crisis. And it wasn't just one metastudy. People try replicating published results from prominent journals and keep finding around half don't replicate. And of course for psychology it is a vast majority not replicating.
I think I've said it before hear: given the replication crisis a single published paper is a very weak unit of evidence. No one should significantly shift their views based on so little and so weak of evidence. If many papers by different researchers all point in the same direction then we should seriously consider the results.
Yep. I’ve mentioned the Reproducibility Crisis here before. Science isn’t as airtight and rock solid as people think it is. Small sample size effects, lack of long-term consistent results, etc.
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At some point in the last 50 years or so it seems to have become acceptable to let students take classes like "Statistical Analysis" without having first demonstrated basic competence in Calculus and I would argue that this has had a disastrous effect on rates of numeracy across a multitude of disciplines.
How do you recognize an error in your estimate if you do not have a clear understanding of what that estimate represents?
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It's extremely bad in ML literature, where pressure to publish and get your citation + h-index up means that people publish all kinds of non-replicate-able junk. Nobody wants another incremental advancement paper so every paper is revolutionary. I cannot tell you the number of times I've taken a paper that looked interested, either used their code or re-implemented it approximately, used their datasets and gotten far worse results. The new trick, or really old trick making a resurgence, is to include all kinds of arcane math in the paper and not provide any code so its impossible to replicate it without a math PhD in that area.
Research papers are written for phds, and if you don't have a phd then you are not the target audience. Unreproducibility and over-mathiness of ML research is a common meme among the online ML-adjacent communities, but it's just not true. The ML community has done far more than any other community to encourage reproducibility and they've had a lot of success in doing so.
Source: I am an ML researcher with only a mediocre publication record. I've got my own gripes with the system that have led to my pub-record being mediocre, but reproducibility is not one of them.
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Speaks really poorly of the quality of the publication too, if it’s allowed to pass. I remember reading a paper once in a “journal” (that actually had some legitimate backing) about the possibility of igniting Saturn with a nuclear weapon and I was thinking, “What the fuck is this shit?,” as I made my way through it. Academia in no way is this sort of purified, pristine landscape of nothing but rigorous logical and scientific clarity that people think it is. There’s at least as much bad science as people think there is good. And some areas of it are outright corrupt.
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