An international survey and modified Delphi process revealed editors’ perceptions, training needs, and ratings of competency-related statements for the development of core competencies for scientific editors of biomedical journals
Why this work is in the frame
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Bibliographic record
Abstract
<ns4:p> <ns4:bold>Background:</ns4:bold> Scientific editors (i.e., those who make decisions on the content and policies of a journal) have a central role in the editorial process at biomedical journals. However, very little is known about the training needs of these editors or what competencies are required to perform effectively in this role. </ns4:p> <ns4:p> <ns4:bold>Methods:</ns4:bold> We conducted a survey of perceptions and training needs among scientific editors from major editorial organizations around the world, followed by a modified Delphi process in which we invited the same scientific editors to rate the importance of competency-related statements obtained from a previous scoping review. </ns4:p> <ns4:p> <ns4:bold>Results:</ns4:bold> A total of 148 participants completed the survey of perceptions and training needs. At least 80% of participants agreed on six of the 38 skill and expertise-related statements presented to them as being important or very important to their role as scientific editors. At least 80% agreed on three of the 38 statements as necessary skills they perceived themselves as possessing (well or very well). The top five items on participants’ list of top training needs were training in statistics, research methods, publication ethics, recruiting and dealing with peer reviewers, and indexing of journals. The three rounds of the Delphi were completed by 83, 83, and 73 participants, respectively, which ultimately produced a list of 23 “highly rated” competency-related statements and another 86 “included” items. </ns4:p> <ns4:p> <ns4:bold>Conclusion:</ns4:bold> Both the survey and the modified Delphi process will be critical for understanding knowledge and training gaps among scientific editors when designing curriculum around core competencies in the future. </ns4:p>
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.029 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it