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Record W2122515369 · doi:10.1136/jme.2010.040675

Authorship policies of bioethics journals: Table 1

2011· article· en· W2122515369 on OpenAlexaff
David B. Resnik, Zubin Master

Bibliographic record

VenueJournal of Medical Ethics · 2011
Typearticle
Languageen
FieldMedicine
TopicEthics in Clinical Research
Canadian institutionsOttawa HospitalUniversity of AlbertaUniversity of Ottawa
FundersNational Institutes of Health
KeywordsBioethicsAcknowledgementEngineering ethicsEmpirical researchSociologyPolitical scienceComputer scienceEpistemologyLawPhilosophyEngineering

Abstract

fetched live from OpenAlex

Inappropriate authorship is a common problem in biomedical research and may be becoming one in bioethics, due to the increase in multiple authorship. This paper investigates the authorship policies of bioethics journals to determine whether they provide adequate guidance for researchers who submit articles for publication, which can help deter inappropriate authorship. It was found that 63.3% of bioethics journals provide no guidance on authorship; 36.7% provide guidance on which contributions merit authorship, 23.3% provide guidance on which contributions do not merit authorship, 23.3% require authors to take responsibility for their contributions or for the article as a whole, 20% provide guidance on which contributions merit an acknowledgement but not authorship, 6.7% require authors to describe their contributions, and only 3.3% distinguish between authorship in empirical and conceptual research. To provide authors with effective guidance and promote integrity in bioethics research, bioethics journals should adopt authorship policies that address several important topics, such as the qualifications for authorship, describing authorship contributions, taking responsibility for the research and the difference between authorship in empirical and conceptual research.

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 imitation

Not 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.

metaresearch head score (Codex)0.122
metaresearch head score (Gemma)0.507
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch, Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.711
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1220.507
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0060.044
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.882
GPT teacher head0.681
Teacher spread0.201 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations35
Published2011
Admission routes1
Has abstractyes

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