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Record W2123438626 · doi:10.1136/jme.26.1.37

Ethical considerations in international HIV vaccine trials: summary of a consultative process conducted by the Joint United Nations Programme on HIV/AIDS (UNAIDS)

2000· article· en· W2123438626 on OpenAlexaff
Dale Guenter, José Esparza, Ruth Macklin

Bibliographic record

VenueJournal of Medical Ethics · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicVaccine Coverage and Hesitancy
Canadian institutionsMcMaster University
FundersJoint United Nations Programme on HIV/AIDS
KeywordsSafeguardingHIV vaccineDeveloping countryMedicineClinical trialHuman immunodeficiency virus (HIV)AIDS VaccinesEconomic growthInformed consentDeveloped countryPolitical scienceEnvironmental healthFamily medicineAlternative medicineNursingVaccine trialPopulation

Abstract

fetched live from OpenAlex

Research that is initiated, designed or funded by sponsor agencies based in countries with relatively high social and economic development, and conducted in countries that are relatively less developed, gives rise to many important ethical challenges. Although clinical trials of HIV vaccines began ten years ago in the US and Europe, an increasing number of trials are now being conducted or planned in other countries, including several that are considered "developing" countries. Safeguarding the rights and welfare of individuals participating as research subjects in developing countries is a priority. In September, 1997, the Joint United Nations Programme on HIV/AIDS (UNAIDS) embarked on a process of international consultation; its purpose was further to define the important ethical issues and to formulate guidance that might facilitate the ethical design and conduct of HIV vaccine trials in international contexts. This paper summarises the major outcomes of the UNAIDS consultative process.

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)0.229
metaresearch head score (Gemma)0.209
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.985
Threshold uncertainty score0.951

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2290.209
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.006
Science and technology studies0.0090.010
Scholarly communication0.0160.009
Open science0.0020.007
Research integrity0.0150.019
Insufficient payload (model declined to judge)0.0010.000

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 head0.129
GPT teacher head0.431
Teacher spread0.302 · 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 designQualitative
Domainnot available
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

Citations109
Published2000
Admission routes1
Has abstractyes

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