Misuse of Coauthorship in Medical Theses in Sweden
Bibliographic record
Abstract
The aim of this study was to explore experiences of authorship issues among persons who have recently received their doctoral degree in medicine in Sweden. A survey was mailed to all who received their PhD at a medical faculty at a Swedish university the first half of 2016. Questions concerned experiences of violations of the first three authorship criteria in the Vancouver rules and of misuse of authorship order in the articles of their thesis, and the respondents' attitudes to these matters. The questionnaire was returned by 285 respondents (68%). According to the majority (53%), the Vancouver rules were not fully respected in the articles of their thesis. A vast majority (97%) found it important that authorship issues are handled correctly, but only 19% responded that their department has a clear and consistently applied policy. We conclude that authorship guidelines are frequently disrespected at medical faculties in Sweden. The universities seem to provide limited support on authorship issues.
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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 | 0.341 | 0.707 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.000 | 0.011 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.073 |
| Insufficient payload (model declined to judge) | 0.002 | 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".