I see this a lot on here especially, where people regard themselves as being well-informed, at the bleeding edge, etc due to reading and quoting scientific pape

I see this a lot on here especially, where people regard themselves as being well-informed, at the bleeding edge, etc due to reading and quoting scientific papers, especially ones with interesting or counter-intuitive results. But one paper that may or may not have used valid statistical analysis doesn't really prove anything. That's exactly what the article is about. It's fine for scientists to propose weird and outlandish theories with just enough analytical duct tape to ensure they aren't completely absurd. But those theories are meant to be analyzed more deeply and critically before anything is done with them, not just blindly assumed to be true because somebody published a paper on it and nobody refuted it yet. There's a lot of statistical tricks that are tough to detect. Like is your sample truly random and representative? How could you even prove that? Like the rat part study purporting to show that drugs are only really dangerously addictive if you're also socially isolated and miserable. It's cool, and I kind of want it to be true, but it seems it's actually highly dependent on exactly what kind of rats you have and where you got them. Similarly, most of the time when you analyze a bunch of statistics, you're looking for a conclusion like that it's 95% likely that A is caused by B. That's only 1 in 20 though, so you should actually expect that if you do the same check for B through U, and none of them really cause A, you will falsely find that one of those letters causes A. But nobody published a paper for checking C through U, so you can't tell.