Conflicts of Interest Arising from Simultaneous Service by Editors of Competing Journals or Publishers
Bibliographic record
Abstract
In this day and age of challenging post-publication peer review and heightened academic scrutiny, editors serve an increasingly important role in screening submissions and managing the quality of information that is published in scholarly journals. Publishers compete for an intellectual market while commercial publishers compete for a commercial share of the market. The assumption argued in this perspective is that having editorial positions in competing journals or publishers (CJPs) may represent competing intellectual, professional and/or financial interests. Thus, based on this assumption, an editor would be expected to show loyalty to a single entity (journal or publisher). Editorial positions on the editorial boards of CJPs, as well as conflicts, financial or other, should be clearly indicated for all editors on the editorial board page of a journal’s website, for transparency. In science and academia, based on these arguments, the author is of the belief that editors should thus generally not serve on the editorial boards of CJPs, or only under limited and fully transparent conditions, even if they serve as editors voluntarily. The author recognizes that not all academics, including editors, might agree with this perspective, so a wider debate is encouraged.
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 | 0.064 | 0.381 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.013 | 0.007 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.012 | 0.012 |
| Insufficient payload (model declined to judge) | 0.015 | 0.008 |
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".