Bibliographic record
Abstract
Research and ethics are inseparable. Based on abhorrent research abuses under the cloak of scientific enquiry, development of the process for the ethical overview of research on/with humans was undertaken. By the end of the twentieth century, sufficient and extensive local and international principles, guidelines, legislations, and treaties about research on humans were in place, with all human-based research requiring review by independent research ethics committees (RECs). With so much established knowledge and legislation about the ethical management of the research process and REC oversight, is there a role for journal editorial boards in ethical oversight? Recommendations from the International Committee of Medical Journal Editors, the basis of the editorial policies of the IJTMB, include the requirement that research must be approved by an REC, and documentation of that review should be included in each article. Thus, as a minimum, journals must ensure that any research submitted for publication has had appropriate ethical review. But journals receive manuscripts after research is done. Journals, therefore, have a duty to ensure that received manuscripts meet expected standards for the publication of research and, for nonresearch situations, that appropriate protections of the research participants were in place even though REC review was not involved.
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 | 0.157 | 0.492 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.011 | 0.027 |
| Scholarly communication | 0.033 | 0.035 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.039 | 0.030 |
| Insufficient payload (model declined to judge) | 0.010 | 0.012 |
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".