A scoping review of competencies for scientific editors of biomedical journals
Bibliographic record
Abstract
BACKGROUND: Biomedical journals are the main route for disseminating the results of health-related research. Despite this, their editors operate largely without formal training or certification. To our knowledge, no body of literature systematically identifying core competencies for scientific editors of biomedical journals exists. Therefore, we aimed to conduct a scoping review to determine what is known on the competency requirements for scientific editors of biomedical journals. METHODS: We searched the MEDLINE®, Cochrane Library, Embase®, CINAHL, PsycINFO, and ERIC databases (from inception to November 2014) and conducted a grey literature search for research and non-research articles with competency-related statements (i.e. competencies, knowledge, skills, behaviors, and tasks) pertaining to the role of scientific editors of peer-reviewed health-related journals. We also conducted an environmental scan, searched the results of a previous environmental scan, and searched the websites of existing networks, major biomedical journal publishers, and organizations that offer resources for editors. RESULTS: A total of 225 full-text publications were included, 25 of which were research articles. We extracted a total of 1,566 statements possibly related to core competencies for scientific editors of biomedical journals from these publications. We then collated overlapping or duplicate statements which produced a list of 203 unique statements. Finally, we grouped these statements into seven emergent themes: (1) dealing with authors, (2) dealing with peer reviewers, (3) journal publishing, (4) journal promotion, (5) editing, (6) ethics and integrity, and (7) qualities and characteristics of editors. DISCUSSION: To our knowledge, this scoping review is the first attempt to systematically identify possible competencies of editors. Limitations are that (1) we may not have captured all aspects of a biomedical editor's work in our searches, (2) removing redundant and overlapping items may have led to the elimination of some nuances between items, (3) restricting to certain databases, and only French and English publications, may have excluded relevant publications, and (4) some statements may not necessarily be competencies. CONCLUSION: This scoping review is the first step of a program to develop a minimum set of core competencies for scientific editors of biomedical journals which will be followed by a training needs assessment, a Delphi exercise, and a consensus meeting.
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 | 0.097 | 0.347 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.041 | 0.028 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".