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Record W3213085190 · doi:10.3390/philosophies6040093

International Coordination of Research Ethics Review: An Adequacy Model

2021· article· en· W3213085190 on OpenAlexaff
Adrian Thorogood, Michael J. S. Beauvais

Bibliographic record

VenuePhilosophies · 2021
Typearticle
Languageen
FieldMedicine
TopicEthics in Clinical Research
Canadian institutionsMcGill University
FundersNational Human Genome Research InstituteNational Institutes of Health
KeywordsResearch ethicsJurisdictionBioethicsPolitical scienceSovereigntyPublic relationsBureaucracyBusinessEngineering ethicsLawLaw and economicsSociologyEngineering

Abstract

fetched live from OpenAlex

International direct-to-participant (DTP) genomics research involves the use of mobile technology to recruit, consent, and study participants remotely. This model can facilitate research across broad geographies and many countries, but must also comply with the norms of multiple recruitment jurisdictions, with each jurisdiction typically requiring at least one local research ethics review. Each additional research ethics review increases bureaucratic hurdles without necessarily strengthening the protection of participants’ rights and interests. For DTP genomic research, obtaining a review may in fact be impossible in the absence of a local research partner. This paper proposes an “adequacy” approach, inspired by data protection law, to coordinate the regulation and oversight of international DTP genomics research. This involves one country voluntarily assessing whether another country’s research ethics reviews are equivalent to its own, in terms of objectives and effectiveness. Ethics-approved projects led by researchers from countries recognized as adequate are deemed to comply with local norms, eliminating the need for a duplicative local review. Adequacy preserves the sovereignty of countries to determine their own regulatory aims and which other countries to trust. It therefore provides a voluntary, incremental path towards greater global coordination of health research oversight.

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)0.321
metaresearch head score (Gemma)0.281
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.988
Threshold uncertainty score0.838

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.3210.281
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0050.004
Science and technology studies0.0100.048
Scholarly communication0.0170.017
Open science0.0050.016
Research integrity0.0120.010
Insufficient payload (model declined to judge)0.0070.002

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 head0.858
GPT teacher head0.699
Teacher spread0.159 · 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 designTheoretical or conceptual
DomainMethods
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

Citations4
Published2021
Admission routes1
Has abstractyes

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