An end to ‘God-like’ scientific knowledge? How non-anonymous referees and open review alter meanings for scientific knowledge
Bibliographic record
Abstract
In this paper I reflect on changing journal peer review practices and relations, and more particularly, on anonymity for referees and openness of review practices and relations. I explore how non-anonymity for referees and open access to journal peer review editorial judgements and decisions contribute to reshaping meanings for scientific knowledge. Anonymous referees and closed access to editorial documents had, until now, helped shape a meaning of objective and ‘God-like’ absolute knowledge. In contrast, more recent non-anonymous referee and open access dynamics have contributed to a new meaning of situated and partial scientific knowledge. I draw from scholarship on peer review, in legal studies, in the sociology of secrecy, and in the sociology of knowledge. I conclude that non-anonymous referees and open review practices and relations challenge ‘God-like’ scientific knowledge in secretive pre-publication journal peer review that, until now, has been instrumental for natural scientific and medical journal publication models that mostly sell scientific knowledge as news.
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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 | 0.143 | 0.321 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.015 | 0.110 |
| Scholarly communication | 0.041 | 0.042 |
| Open science | 0.003 | 0.019 |
| Research integrity | 0.010 | 0.012 |
| Insufficient payload (model declined to judge) | 0.005 | 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".