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Record W2023582820 · doi:10.1525/jer.2009.4.2.65

Inclusion of Women, Minorities, and Children in Clinical Trials: Opinions of Research Ethics Board Administrators

2009· article· en· W2023582820 on OpenAlexaboutno aff
Holly A. Taylor

Bibliographic record

VenueJournal of Empirical Research on Human Research Ethics · 2009
Typearticle
Languageen
FieldMedicine
TopicEthics in Clinical Research
Canadian institutionsnot available
FundersNational Institute of Allergy and Infectious DiseasesNational Institutes of Health
KeywordsInclusion (mineral)Ethics committeeInstitutional review boardResearch ethicsClinical trialMedical educationFamily medicineQuarter (Canadian coin)Alternative medicineMedicinePolitical sciencePsychologyPublic relationsPublic administrationPsychiatrySocial psychologyInternal medicinePathology

Abstract

fetched live from OpenAlex

IN AN ATTEMPT TO ENCOURAGE INCLUSION of women, minorities, and children in clinical trials, the U.S. National Institutes of Health (NIH) requires investigators conducting NIH-sponsored research to adequately address NIH inclusion guidelines concerning recruitment of women, minorities, and children. A survey of U.S. Research Ethics Board (REB) administrators at institutions receiving NIH funding indicated awareness and implementation of the inclusion guidelines. According to the administrators, investigators and REBs address inclusion in more than half of the relevant protocols. About half of the REB administrators consider the guidelines partly responsible for increased attention to inclusion, but only about a quarter believe that there is greater inclusion as a result.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaMetaresearch
Domain: Methods · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Qualitativelow
gptMetaresearch
Domain: Methods · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationalhigh
models splitAgreement compares identical category sets and study designs across arms.

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)0.756
metaresearch head score (Gemma)0.843
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesMetaresearch, Science and technology studies, Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.468
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.7560.843
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0070.006
Science and technology studies0.0020.014
Scholarly communication0.0000.000
Open science0.0030.004
Research integrity0.0050.128
Insufficient payload (model declined to judge)0.0000.000

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 head0.943
GPT teacher head0.802
Teacher spread0.141 · 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

Labeled directly by 2 models reading the full record.

Metaresearch

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designQualitative · Observational
DomainMethods
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

Citations23
Published2009
Admission routes1
Has abstractyes

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