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Comment by qqj | Hacker News Reader

this is incredible. And I thought I had it bad with politics in tech companies... this is some next level not giving a fuck right there - people who cheat like that should be punished severely, and work as supermarket cashiers, not become fricking professors. Unfortunately, I too, were I in your shoes, wouldn't pursue it much further past filing a formal complaint or two: the game is asymmetrical, it's much harder to nail someone for wrongdoing than it is for them to fudge up some lab results. Not to mention the emotional toil and waste of time and potential political blowback the would be whistle blower would suffer...

Pretty depressing stuff.

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About half of my friends in grad school have had their careers damaged to varying extent by academic fraud, some have wasted lives chasing bad results (one friend lost several years chasing a bad result by Homme Hellinga), some have had bad stuff perpetrated upon them by bad actors with big names (one had her result we suspect - stolen by Carolyn Bertozzi via the review process, luckily her boss was a member of NAS and PNAS track-III'd the paper ahead of Bertozzi's publication).

Just be aware that it's not always like this, and that some fields are less prone to it than others.

In my 8 years in research mathematics, I didn't see a single case that would come close to this horror show (not that mathematics is free of unethical behavior, of course). Collaborating with biologists, however, I got exposed to a world far more backstabby than I've since experienced in the corporate world.

I think this is largely because results in math are easily verifiable compared to chemistry, or as an even worse example, the social sciences. The latter are also suffering from the replication crisis the most.

Math has a different problem. Because of the wide breadth of the field, and highly specialized nature of problems, it can take a very long time for anyone to actually verify a result with confidence. If ever. Unless you’re doing something famous like P!=NP, there might not be many people capable of checking your work in a reasonable amount of time.

The story of Fermat’s Last is a great example, what would have happened if that wasn’t a famous problem?

I agree, even proofs are wrong more often than you’d think, but I’m not sure whether math is actually so uniquely broad that other fields don’t suffer from this problem.

Maybe it's not its breadth, but its depth. That isn't to say that other fields aren't deep, don't get me wrong. But the more tightly coupled with the high-level physical world a field is (think for example medicine or biology), the more it is prone to having technologoical advances from the outside make new sub-fields crop up and old ones die. Think of for example the multitude of research areas made possible by gene editing, or high-resolution NMR imaging.

Of course this happens to some extent in math too, but a lot of subfields aren't killed or born due to outside technological changes. Number theory remains number theory, and still builds directly on centuries of work, even if computer verification has helped in some cases (disclaimer: I'm not a number theorist).

For most subfields of mathematics, you have a lot of depth to cover before you get to the forefront of research. That isn't to say that it's by any means easy to get to the forefront of more high-level physical sciences, but there are certainly subfields in biology or medicine that didn't exist a mere 40 years ago (also true in math, but in general far more rare there).

Also math can hinge on small technicalities. Like Andrew Wiles got a pre review for the proof of fermat conjecture and all was well. I depth review later found a serious gap/flaw which fortunately with hard work and luck he could plug. In contrast if you invent the electron microskop and you get images, you still made the invention (even if small or even big details might be wrong, and the result could be better). In other science often the gist is not effected.

I moved from Physics to Biology. It was quite a culture shock and I ended up leaving after a few years. The amount of shady practices, outright data manipulation, PIs ignoring students just making up stuff was just hard to be in on.

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