Bibliographic record
Abstract
Multiple authorship is becoming increasingly common in bioethics research. There are well-established criteria for authorship in empirical bioethics research but not for conceptual research. It is important to develop criteria for authorship in conceptual publications to prevent undeserved authorship and uphold standards of fairness and accountability. This article explores the issue of multiple authorship in bioethics and develops criteria for determining who should be an author on a conceptual publication in bioethics. Authorship in conceptual research should be based on contributing substantially to: (1) identifying a topic, problem, or issue to study; (2) reviewing and interpreting the relevant literature; (3) formulating, analyzing, and evaluating arguments that support one or more theses; (4) responding to objections and counterarguments; and (5) drafting the manuscript. Authors of conceptual publications should participate substantially in at least two of areas (1)-(5) and also approve the final version. [corrected].
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 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 | 0.186 | 0.475 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.017 | 0.057 |
| Scholarly communication | 0.030 | 0.020 |
| Open science | 0.007 | 0.014 |
| Research integrity | 0.022 | 0.028 |
| Insufficient payload (model declined to judge) | 0.015 | 0.007 |
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 source (direct Gemma or distilled Codex), 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".