Knowledge and motivations of training in peer review: An international cross-sectional survey
Bibliographic record
Abstract
BACKGROUND: Despite having a crucial role in scholarly publishing, peer reviewers do not typically require any training. The purpose of this study was to conduct an international survey on the current perceptions and motivations of researchers regarding peer review training. METHODS: A cross-sectional online survey was conducted of biomedical researchers. A total of 2000 corresponding authors from 100 randomly selected medical journals were invited via email. Quantitative items were reported using frequencies and percentages or means and SE, as appropriate. A thematic content analysis was conducted for qualitative items in which two researchers independently assigned codes to the responses for each written-text question, and subsequently grouped the codes into themes. A descriptive definition of each category was then created and unique themes-as well as the number and frequency of codes within each theme-were reported. RESULTS: A total of 186 participants completed the survey of which 14 were excluded. The majority of participants indicated they were men (n = 97 of 170, 57.1%), independent researchers (n = 108 of 172, 62.8%), and primarily affiliated with an academic organization (n = 103 of 170, 62.8%). A total of 144 of 171 participants (84.2%) indicated they had never received formal training in peer review. Most participants (n = 128, 75.7%) agreed-of which 41 (32.0%) agreed strongly-that peer reviewers should receive formal training in peer review prior to acting as a peer reviewer. The most preferred training formats were online courses, online lectures, and online modules. Most respondents (n = 111 of 147, 75.5%) stated that difficulty finding and/or accessing training was a barrier to completing training in peer review. CONCLUSION: Despite being desired, most biomedical researchers have not received formal training in peer review and indicated that training was difficult to access or not available.
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 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 | 0.034 | 0.121 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.023 | 0.085 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".