[marginalia_nu]

Not everything gets retracted either. There's a surprisingly deep rot in many parts of science. There are strong incentives to publish, and a lot of the methods you can use to inflate statistical significance (i.e. p-hacking) are hard to distinguish from publication bias and other innocent explanations for falling outside of statistical expectations.

Preregistration might help, but it doesn't really address the misaligned incentives that are at the heart of academic fraud.

[nextos]

Even articles that publish legit findings tend to embellish data. I do this for a living, I often try to reproduce prominent results, and I regularly see things that are too good to be true. This is bad because it pushes everyone to do the same, as reviewers are now used to seeing perfect and pristine data.

I have been asked to manipulate data a few times in my career. I have always refused, but this came at the cost of internal fights, getting excluded from other projects for being "too idealistic", or missed promotions. Incentives are just perverse. Fraud and dishonesty are rewarded, pretty depressing.

[thwarted]

Tragedy of the Commons Ruins Everything Around Me.

Everyone wants answers, so anyone that provides an answer is elevated, independent of if the answer is right or not. To wit: the current AI push.

Clips from The Big Short surfaced in my YouTube feed recently, and they way you worded this reminded me of the scene with the rating agency.

Is scientific research and publishing headed for it's own CDS/MBS-esque implosion?

[nextos]

I think academic research is becoming very inefficient, and traditional Academia might eventually become stagnant. If you don't play the game I described above, it is really hard to stay afloat. I guess industrial labs, where incentives are better aligned, might become more attractive. I have seen lots of prominent scientists moving into industrial labs recently, which would be something hard to imagine even a few years back.

[RicoElectrico]

Thank you for doing the right thing.

[schmidtleonard]

Yep. Worse, p-hacking can be done by accident. I mean, the term implies intent, but a dogshit null hypothesis is problematic regardless of whether it is dogshit on purpose or merely due to lack of skill on the part of the researcher. Either way, it pumps publication numbers and dumps publication quality. If 100% of researchers were 100% honest, we would still see this effect boost low-quality research.