Contemporary authorship guidelines fail to recognize diverse contributions in conservation science research
Bibliographic record
Abstract
Abstract Authorship should acknowledge and reward those deserving of such credit. Moreover, being an author on a paper also means that one assumes ownership of the content. Journals are increasingly requiring author roles to be specified at time of submission using schemes such as the contributor roles taxonomy (CRediT) system, which relies on 14 different roles. Yet, there are many other aspects of research that are not adequately captured by the list of roles, particularly in applied environmental disciplines such as conservation science, environmental science and applied ecology. The growing recognition that authorship should reflect contributions that extend beyond the usual data collection, analysis and writing provides the ideal backdrop for rethinking contributions in conservation science. Here we propose a more inclusive approach to authorship that recognizes and values diverse contributions and contributors using an expanded list of CRediT roles.
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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 | 0.272 | 0.512 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.015 | 0.025 |
| Scholarly communication | 0.019 | 0.020 |
| Open science | 0.008 | 0.015 |
| Research integrity | 0.014 | 0.020 |
| Insufficient payload (model declined to judge) | 0.009 | 0.009 |
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; the direct Gemma label and the distilled Codex classifier 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".