Peer review after the fact, or a falsifier fixed in advance
Preprint servers made research fast and open, and they carry vastly more rigour than anything here. The difference is when the test is defined.
The short answer
Pre-registration exists in science precisely because defining the test after seeing the data is how honest people fool themselves. It is standard in clinical trials and still uncommon elsewhere.
Here it is the only mode. A model's claims carry resolution criteria and a date, and whether they were committed before that date is proven from the repo's git history — not asserted. A model whose criteria arrived late is visibly not criteria-frozen, and the card says so.
The obvious trade: no peer review, no methods section, no data, no replication. This is a much lighter instrument aimed at everyday questions rather than research claims — the kind of thinking that never gets written up at all, and so never gets checked.
Side by side
| arXiv and preprint servers | Model Meets Reality |
|---|---|
| Test defined when reporting | Falsifier defined before the outcome |
| Peer review after posting | No review of quality — only of format |
| Methods, data, replication | One document; no data pipeline |
| Withdrawal is rare and awkward | A deletion clause is written in from the start |
| Rigorous and slow | Light and fast, with far less rigour |
What arXiv and preprint servers does better
Rigour, depth, methods, data, and actual peer review by people who know the field. A preprint can support a claim that a one-page model cannot begin to. Nothing here is a substitute for research — it is a way to make ordinary, unpublished thinking checkable.
Where this stands today
https://github.com/someone/their-model Help me use this
Paste that into any assistant. It reads the model — premises, falsifiers, deletion clause — and reasons through it.
The difference that is not on the table
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