Entities enabling scientific fraud at scale (2025)

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.

I ran into an interesting incident of this recently. I got a Google Scholar alert about a paper with some experiments related to a paper I had published a while ago, by one "N. Tvlg". I read the paper with interest but I started noticing that although the arguments sounded good, they didn't really make sense, and also the descriptions of the results didn't really match the figures. Eventually I came across a cluster of citations to completely unrelated papers---my field is computational linguistics and these were citations to, like, studies of battery technologies for electric cars. I looked up "N Tvlg" on Google Scholar and they had "published" several articles very recently in totally divergent fields, and upon inspection, all of them had citations back to this materials science research buried deeply somewhere. Clearly these were LLM generated papers trying to build up citation count and h-rank for someone's career.

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.

Perhaps relevant to this - if you go to this global ranking of publications:

  https://traditional.leidenranking.com/ranking/2025/list

and select "Mathematics and Computer Science", you'll find the top-ranked university is the University of Electronic Science and Technology of China.

My Chinese colleagues have heard of it, but never considered it a top-ranked school, and a quick inspection of their CS faculty pages shows a distinct lack of PhDs from top-ranked Chinese or US schools. It's possible their math faculty is amazing, but I think it's more likely that something underhanded is going on...

It's strange to me that in places full of smart people, it seems to be well understood that this happens and there are lots of anecdotes relating to it; yet the same people will be confused that their political adversaries don't trust "the science" on one issue or another.

Maybe it's the scientists they don't trust?

This is the part that feels hardest to fix: once a system starts rewarding throughput over scrutiny, fraud stops looking like individual misconduct and starts looking like a supply chain problem.

More broadly, an incredible amount of our society's systems are built around actors being uncoordinated. Redesigning institutions to resist networks of coordinated action between seemingly unlinked individuals will, in my opinion, be one of the great social challenges of this era.

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.

This is what happens when people argue past each other on "Trust the science".

Science is good, but it's mediated via corruptible humans.

It always comes back to Goodhart's Law and our apparent inability to create sustainable incentive structures.

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!

One approach is more integration of researchers with businesses. Fraud (or simple incompetence) by researchers negatively affects businesses, as they expend effort on things that aren't real. I understand this is a constant problem in the pharmaceutical industry.

If you get paid by the government to do research you should make all your raw data, code, results etc, accessible to the public.

If it then turns out any of it is fabricated, you should be personally liable for paying it back

the problem is two-fold in my opinion.

firstly, there are basically no legal repercussions for scientific misconduct (e.g. falsifying data, fake images, etc.). most individuals who are caught doing this get either 1) a slap on the wrist if they are too big to fail or in the employ of those who are too big to fail or 2) disbarred, banned, and lose their jobs. i don't see why you can go to jail for lying to investors about the number of users in your app but don't go to jail for lying to the public, government, and members of the scientific community about your results.

secondly, due to the over production of PhD's and limited number of professorship slots competition has become so incredibly intense that in order to even be considered for these jobs you must have Nature, Cell, and Science papers (or the field equivalent). for those desperate for the job their academic career is over either way if they caught falsifying data or if they don't get the professorship. so if your project is not going the way you want it to then...

sad state of things all around. i've personally witnessed enough misconduct that i have made the decision to leave the field entirely and go do something else.

Are these "entities" named and shamed somewhere? I just scanned the paper but couldn't find explicit mentions.

why would anyone actually interested in scientific research come to this, since it literally undermines the whole practice of science?

[dead]

[dead]

[flagged]

Almost as if capitalism makes everything into a market, and the profits make it self sustaining.

How many will see the connections between this and our capitalist mode of production? Probably few since modern lit/news is allergic to systemic analysis.

The blatant flaws of capitalism can't be ignored for much longer.

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.

Industry >> Academia

Profits are the deciding factor, not honor.