The evolution of peer review as a basis for scientific publication: directional selection towards a robust discipline?
Bibliographic record
Abstract
Peer review is pivotal to science and academia, as it represents a widely accepted strategy for ensuring quality control in scientific research. Yet, the peer-review system is poorly adapted to recent changes in the discipline and current societal needs. We provide historical context for the cultural lag that governs peer review that has eventually led to the system's current structural weaknesses (voluntary review, unstandardized review criteria, decentralized process). We argue that some current attempts to upgrade or otherwise modify the peer-review system are merely sticking-plaster solutions to these fundamental flaws, and therefore are unlikely to resolve them in the long term. We claim that for peer review to be relevant, effective, and contemporary with today's publishing demands across scientific disciplines, its main components need to be redesigned. We propose directional changes that are likely to improve the quality, rigour, and timeliness of peer review, and thereby ensure that this critical process serves the community it was created for.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.119 | 0.223 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.002 | 0.012 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".