I mainly have evidence for the absolute level, not necessary for the trend (in science getting worse). For the trend, I could point to Goodhart phenomena like having to rely on the publication per unit time metric being gamed, and getting worse as time progresses.
I also think that in this context, the absolute level is evidence of the trend, when you consider that the number of scientists has increased; if the quality of science in general has not increased with more people, it's getting worse per unit person.
For the absolute level, I've noticed scattered pieces of the puzzle that, against my previous strong presumption, support my suspicions. I'm too sleepy to go into detail right now, but briefly:
There's no way that all the different problems being attacked by researchers can be really, fundamentally different: the functionspace is too small for a unique one to exist for each problem, so most should be reducible to a mathematical formalism that can be passed to mathematicians who can tell if it's solvable.
There is evidence that such connections are not being made. The example I use frequently is ecologists and the method of adjacency matrix eigenvectors. That method has been around since the 1960s and forms the basis of Google's PageRank, allowing it to identify crucial sites. Ecologists didn't apply it to the problem of identifying critical ecosystem species until a few years ago.
I've gone into grad school myself and found that existing explanations of concepts is a scattered mess: it's almost like they don't want you to understand papers or break into advanced topics that are the subject of research. Whenever I understand such a topic, I find myself able to explain it in much shorter time than experts in the field in explained it to me. This creates a fog over research, allowing big mistakes to last for years, with no one ever noticing it because too few eyeballs are on it. (This explanation barrier is the topic of my ever-upcoming article "Explain yourself!")
As an example of what a mess it is (and at risk of provoking emotions that aren't relevant to my point), consider climate science. This is an issue where they have to convince LOTS of people, most of whom aren't as smart. You would think that in documenting the evidence supporting their case, scientists would establish a solid walkthrough: a runnable, editable model with every assumption traceable to its source and all inputs traceable to the appropriate databases.
Yet when climate scientists were in the hot seat last fall and wanted to reaffirm the strength of their case, they had no such site to point anyone to. RealClimate.org made a post saying basically, "Um, anyone who's got the links to the public data, it'd be nice if you could post them here..."
To clarify, I'm NOT trying to raise the issue about AGW being a scam, etc. I'm saying that no matter how good the science is, here we have a case where it's of utmost important to explain research to the masses, and so it would have the most thorough documentation and traceability. Yet here, at the top of the hill, no one bothered to trace out the case from start to finish, fully connecting this domain to the rest of collective scientific knowledge.
I think you've got an example of generalizing from one example, and perhaps the habit of thinking of oneself as typical-- you're unusually good at finding clear explanations, and you think that other people could be about as good if they'd just try a little.
I suspect they'd have to try a lot.
As far as I can tell, most people find it very hard to imagine what it's like to not understand knowledge they've assimilated, which is another example of the same mistake.
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