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Just before Covid, a gun store was robbed in my town. I worked in a different gun store, so we got some of the inside scoop. Proprietor of the robbed store used to work on my computer whenever I fucked it up too badly. The shop was the shittiest one in the county, lodged in a former meat market. The robbers just pulled part of the roof off the building to get into the secure room.
Turned out to be the local high school football team. They stole around fifty guns, fifteen of which have been recovered some seven years later. The recovered guns have been used in at least three homicides so far. One was just recovered at a traffic stop this year, one killed a high school senior just after prom not two weeks ago. Perp there hasn't been identified or caught.
The kids who robbed the place were caught within days. It remains unclear exactly how many people were involved, at least two unnamed juveniles were processed, but shield laws prevent the public knowing anything. Three of the older kids were charged for the robbery, one got no time, other two got three and ten months respectively, despite not cooperating with police in the recovery of the firearms or identification of other perpetrators. Everyone involved was put into a youth criminal diversion program that released them without a criminal record.
The ringleader and one who got the most time, one Travontis (Drink!) Miller, was given the ten month sentence, but due to the protective nature of the diversion program, it will never be public knowledge that he plead guilty to multiple firearm felonies or how long he actually served of that jail term. What we do know is that he was out prior to December of 2021, because that's when he was arrested for a series of other crimes we're not entirely sure what happened.
He was charged with assault and battery (strangulation), robbery and domestic violence, but once again was given protected youth status despite being in his twenties by this point (the program runs until age 24). He also picked up charges of resisting arrest and being in possession of one of the stolen firearms from the original gun store case. These charges too were concealed under the diversion program.
So when people tell me that what we really need to cut down on gun violence in this country is to ensure that every state has a different magazine limit, or force used gun sales into stores, or ban AR-15s, or not allow gun companies to advertise, it makes me irrationally angry. This dude, when he hits 25, will have no criminal record and will be able to pass a background check to buy a firearm legally. At least until his next felony, which I don't expect to take long.
Below are two quote sets for those who didn't read the articles, first the prosecution in the original case:
The judge wasn't interested, and had The Science on his side.
But sure, the problem with gun violence in the US is that Billy Bob put a giggle trigger on his PSA.
Edit: added/fixed links
Science should have nothing to do with law. If the science says something, let Congress reflect that in the law, but Judges do not have the authority to simply declare this kind of thing. Warren and his court have been a disaster for this country.
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.
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.
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.
I am a ML researcher, in Industry without a PhD. The papers are absolutely for me. https://www.nature.com/articles/s41598-025-07087-2 This paper I recently tried to replicate for research on IoT cuffless BP, it absolutely fails to replicate. Not only that, but it also suffers from massive subject leakage on how it splits the data. It's pretty much overfit with a 75% overlap between signals and then it shuffles those between train and val. Even copying it's splitting approach I failed to get more than a MAE SBP of 6.07 and DBP of 4.3. Paper claims sub 2.0 for both.
Then there's this: https://arxiv.org/pdf/2512.19428. Maybe you know Grassmann flows and manifolds but I definitely did not learn this naturally. I pretty much need a background tutorial on this.
I actually enjoyed this paper's concept: https://arxiv.org/pdf/2602.14972 But needing to read 2-3 additional papers, one of which was super mathy proving out the intuition was a lot of work. It still takes me a bit to conceptualize this because it is DEEP in the bayesian world.
Maybe you are in a different subfield than I am, but I have consistently failed to replicate paper results for the occasional paper for the last 4-5 years. It happens, it's a thing. If I say that to other industry researchers they pretty much agree. One of the reasons we think poorly of academics.
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