Preregistration might help, but it doesn't really address the misaligned incentives that are at the heart of academic fraud.
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.
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?
This is in addition to wasting a big chunk of the billions spent each year on Alzheimer's research on false leads (see https://www.alz.org/news/2024/congress-bipartisan-funding-al... for a source on the billions).
Yes, very serious consequences indeed. (Note, I did my best to back up my statements with high quality unbiased factual references. Please read them before disagreeing with my description of the result.)
But, for completeness, paper retractions can happen for many reasons, not all of them nefarious, though it could be that most retractions are from authors trying to game the system and getting called out. For example, if the terms of using a certain data set change, you could be required to retract your paper and remove that data from the analysis.