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Record W4290975602 · doi:10.1007/s10805-022-09455-3

Ethical Issues in Research: Perceptions of Researchers, Research Ethics Board Members and Research Ethics Experts

2022· review· en· W4290975602 on OpenAlexafffund
Marie-Josée Drolet, Eugénie Rose-Derouin, Julie-Claude Leblanc, Mélanie Ruest, Bryn Williams–Jones

Bibliographic record

VenueJournal of Academic Ethics · 2022
Typereview
Languageen
FieldHealth Professions
TopicEthics in medical practice
Canadian institutionsUniversité de MontréalUniversité du Québec à Trois-Rivières
FundersSocial Sciences and Humanities Research Council of CanadaUniversité du Québec à Trois-Rivières
KeywordsResearch ethicsEngineering ethicsContext (archaeology)PsychologySociology

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.331
metaresearch head score (Gemma)0.473
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: Methods
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.992
Threshold uncertainty score0.825

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.3310.473
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0050.006
Science and technology studies0.0110.011
Scholarly communication0.0150.011
Open science0.0030.015
Research integrity0.0080.016
Insufficient payload (model declined to judge)0.0030.001

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 head0.925
GPT teacher head0.787
Teacher spread0.138 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designQualitative
DomainMethods
GenreReview

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

Citations94
Published2022
Admission routes2
Has abstractno

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