This is Goodhart's law at scale. Number of released papers/number of citations is a target. Correctness of those papers/citations is much more difficult so is not being used as a measure.

With that said, due to the apparent sizes of the fraud networks I'm not sure this will be easy to address. Having some kind of kill flag for individuals found to have committed fraud will be needed, but with nation state backing and the size of the groups this may quickly turn into a tit for tat where fraud accusations may not end up being an accurate signal.

May you live in interesting times.

The future of science, the Internet, and all things: The Library of Babel by Jorge Luis Borges.

Some things should not have been democratized. Silicon Valley assumes that removing restrictions on information brings freedom, but reality shows that was naïve.

It kinda skips over how large mainstream journals, with their restrictive and often arbitrary standards, have contributed to this. Most will refuse to publish replications, negative studies, or anything they deem unimportant, even if the study was conducted correctly.

My wife completed her PhD two years ago and she put a LOT of work into it. Many sleepless nights, and it almost destroyed our marriage. It took her about 6 years of non-stop madness and she didn’t even work during that time. She said that many of her colleagues engaged in fraudulent data generation and sometimes just complete forgery of anything and everything. It was obvious some people were barely capable of putting together coherent sentences in posts, but somehow they generated a perfect dissertation in the end. It was common knowledge that candidates often hired writers and even experts like statisticians to do most of the heavy lifting. I don’t know if this is the norm now, but I simultaneously have more respect and less respect for those doctoral degrees, knowing that some poured their heart and soul into it, while others essentially cheated their way through. OTOH, I also understand that there may be a lot of grey area.

My eyes have been opened!

It is useful to distinguish between "effective" scientific fraud, where some set of fraudulent papers are published that drive a discipline in an unproductive direction, and "administrative" scientific fraud, where individuals use pseudo-scientific measures (H-index, rankings, etc) to make allocation decisions (grants, tenure, etc). This article suggests that administrative scientific fraud has become more accessible, but it is very unclear whether this is having a major impact on science as it is practiced.

Non-scientists often seem to think that if a paper is published, it is likely to be true. Most practicing scientists are much more skeptical. When I read a that paper sounds interesting in a high impact journal, I am constantly trying to figure out whether I should believe it. If it goes against a vast amount of science (e.g. bacteria that use arsenic rather than phosphorus in their DNA), I don't believe it (and can think of lots of ways to show that it is wrong). In lower impact journals, papers make claims that are not very surprising, so if they are fraudulent in some way, I don't care.

Science has to be reproducible, but more importantly, it must be possible to build on a set of results to extend them. Some results are hard to reproduce because the methods are technically challenging. But if results cannot be extended, they have little effect. Science really is self-correcting, and correction happens faster for results that matter. Not all fraud has the same impact. Most fraud is unfortunate, and should be reduced, but has a short lived impact.