Pre-prints and the Citation Cycle
MethodologyComments
You mention these networks are built on unvetted foundations, but many pre-prints are simply the early versions of papers that eventually pass review. We need to distinguish between permanent pre-prints and those in transit to see if the fragility is actually systemic.
This isn't just a theoretical cycle. I've seen local policy briefs cite pre-prints as cutting edge research before the authors even had a chance to correct basic methodology errors.
The risk is amplified now that LLMs are being used for peer review. If a viral pre-print influences the model's training data or the reviewer's prompt, the rubber stamp effect becomes an automated feedback loop.
We should also consider that pre-prints allow for crowd-sourced review in real time via platforms like PubPeer. This often catches errors faster than the traditional six-month review cycle.
If AI reviewers could actually analyze the raw data of a pre-print instantly, would that eliminate the lag and the fragility described? Or would that just accelerate the cycle of errors?