Coauthorship in Pathology, a Comparison With Physics and a Survey-Generated and Member-Preferred Authorship Guideline
Bibliographic record
Abstract
In a large and detailed survey of scientific coauthorship in pathology, 3500 members of the US and Canadian Academy of Pathology (USCAP) were surveyed via the Internet with a final response rate of 22.5%. The results were compared with a previous survey of members of the American Physical Society (APS). The fields are found to be very similar. For example, there is no well-defined way to determine coauthorship: the byline is arrived at without the use of public coauthorship standards according to 90% of respondents (92% in physics). A substantial amount of inappropriate authorship is present in both fields using a variety of authorship guidelines. For example, using the guideline of the International Committee of Medical Journal Editors (the "Uniform Requirements for Manuscripts Submitted to Biomedical Journals" [ICMJE]), the average number of coauthors judged to be inappropriate in pathology on papers with 4 coauthors is 1.0 (1.2 in physics), and using the guideline requiring "direct contributions to scientific discovery or invention," we find 1.6 (1.5 in physics). Finally, it is suggested that authorship guidelines should be constructed by public surveys rather than closed-door committees: an authorship guideline constructed from previous survey feedback (from APS members) was found to be preferable to USCAP members (it received 40% of the vote, the ICMJE received 24% of the vote).
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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; a candidate call from one teacher head, 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".