MétaCan
Menu
Back to cohort
Record W2052739954 · doi:10.1007/s11673-014-9604-6

Making a Commitment to Ethics in Global Health Research Partnerships: A Practical Tool to Support Ethical Practice

2015· article· en· W2052739954 on OpenAlexaff
Jill Murphy, Jennifer Hatfield, Kaosar Afsana, Vic Neufeld

Bibliographic record

VenueJournal of Bioethical Inquiry · 2015
Typearticle
Languageen
FieldMedicine
TopicGlobal Health and Surgery
Canadian institutionsCanadian Coalition for Global Health ResearchSimon Fraser University
Fundersnot available
KeywordsGeneral partnershipGlobal healthAccountabilityPublic relationsPolitical scienceScholarshipEthical codeResearch ethicsEquity (law)Engineering ethicsHealth careSociologyLaw

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)0.247
metaresearch head score (Gemma)0.332
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.977
Threshold uncertainty score0.928

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2470.332
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.003
Science and technology studies0.0250.049
Scholarly communication0.0310.043
Open science0.0060.043
Research integrity0.0230.034
Insufficient payload (model declined to judge)0.0120.003

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 head0.781
GPT teacher head0.658
Teacher spread0.123 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreMethods

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

Citations63
Published2015
Admission routes1
Has abstractno

Explore more

Same venueJournal of Bioethical InquirySame topicGlobal Health and SurgeryFrench-language works237,207