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Record W2787937732 · doi:10.7202/1058315ar

Consent Documentation and the Accessibility of Research Results in International Development Research

2019· article· en· W2787937732 on OpenAlexaffvenue
Erika Malich

Bibliographic record

VenueCanadian Journal of Bioethics · 2019
Typearticle
Languageen
FieldHealth Professions
TopicInterpreting and Communication in Healthcare
Canadian institutionsInternational Development Research Centre
Fundersnot available
KeywordsDocumentationInformed consentProcess (computing)Engineering ethicsPsychologyComputer scienceMedicineEngineeringAlternative medicinePathology

Abstract

fetched live from OpenAlex

This case study touches on issues that may arise in international development research, with reflections based on experiences conducting research in Peru. The two issues to be discussed are that of cultural differences in the consent documentation process, and ensuring that the benefits of research flow back to research participants.

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 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)0.390
metaresearch head score (Gemma)0.529
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Reproducibility · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.610
Threshold uncertainty score0.753

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.3900.529
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.004
Science and technology studies0.0140.033
Scholarly communication0.0170.019
Open science0.0040.017
Research integrity0.0090.010
Insufficient payload (model declined to judge)0.0090.002

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 head0.485
GPT teacher head0.622
Teacher spread0.137 · 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 designNot applicable
DomainReproducibility
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

Citations2
Published2019
Admission routes2
Has abstractyes

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