Bibliographic record
Abstract
The one quality claimed universally by all forms of scholarly publishing, and that distinguishes this form of publishing from all others, is the practice of assuring some means of prior review and critique of proposed publications by readers qualified to make informed judgments of a work's credibility and contribution to a field or discipline. Peer review—the shorthand way of describing this practice—has long been simply assumed by readers and claimed by scholarly publishers, without any means of disclosing to readers the nature of the review undertaken or the specific object that was reviewed. This article examines why this long-standing modesty among scholarly publishers is now contributing to the challenges faced by scholarly publishing in asserting its distinct authority as a source of knowledge; describes ways in which definitions of peer review could be made clear and public, and proposes a system for signalling to readers (and capturing in metadata associated with individual scholarly works) the nature of the peer review to which a work has been subjected; and explores a range of approaches to how such a system of signalling could be implemented and policed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.191 | 0.538 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.022 | 0.091 |
| Scholarly communication | 0.057 | 0.052 |
| Open science | 0.006 | 0.025 |
| Research integrity | 0.014 | 0.022 |
| Insufficient payload (model declined to judge) | 0.007 | 0.004 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".