The Church and Peer Review: Was 'Peer' Review Fairer, More Honest Then Than Now?
Bibliographic record
Abstract
The traditional thought regarding peer review tends to be that it started with the establishment of the academy, sometime around 1650. It is a reasonable presumption that to have peer review one needs first to have peers. However, the actual review of works certainly occurred long before 1650. Of some importance is the nature of that review that took place prior to the appearance of universities in Bologna and Paris. The standard (and misapplied) logic is that the Church wielded a heavy hand on all publishing, acting as a restraint on inappropriate works prior to their publication. This is not wholly true, however. The Church is best known for its suppression of works post-publication. In a way, it acted as a critic, offering its advice to authors who it found proposed errant ideas and suggesting they might wish to recant and return to good standing. This is interesting when cast in today's peer-review environment. The author suggests that much can be learned from the Church's method of dealing with scholarship, especially in a world of e-reserves. Should we ditch the traditional peer-review method and go back to a publish-then-evaluate system used by the Holy See? In large part, the author argues that unless the academy is willing to cure the perceived ills of peer review and do so soon, the question will be answered in the affirmative, with or without our agreement.
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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 | 0.139 | 0.330 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.014 | 0.075 |
| Scholarly communication | 0.048 | 0.035 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.014 | 0.023 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".