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Record W2075578827 · doi:10.1080/13691050600888434

Community preparedness for HIV vaccine trials in the Democratic Republic of Congo

2006· article· en· W2075578827 on OpenAlexaff
John Olin, Jacques Kokolamami, François Bompeka Lepira, Kashamuka Mwandagalirwa, Bavon Mupenda, Michel L. Ndongala, Suzanne Maman, Robert C. Bollinger, Jean B. Nachega, John L. Mokili

Bibliographic record

VenueCulture Health & Sexuality · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicVaccine Coverage and Hesitancy
Canadian institutionsMcGill University
FundersU.S. Public Health ServiceJohns Hopkins University
KeywordsPreparednessHIV vaccineMedicineVaccine trialClinical trialFocus groupVaccinationHuman immunodeficiency virus (HIV)Family medicineEnvironmental healthPolitical scienceImmunologySociology

Abstract

fetched live from OpenAlex

This paper reports on an assessment of community preparedness for HIV vaccine trials in the Democratic Republic of Congo. Formative research was conducted in the capital city of Kinshasa during the period October 2003 to March 2004 to answer questions pertinent to planning trials of a preventive HIV vaccine and to identify related issues. Twenty-seven in-depth interviews and two focus groups were held with potential trial participants and community leaders. Data was collected on the subjects of vaccines, HIV/AIDS and sexual behaviour, and an HIV vaccine. The study also sought to identify factors that motivate a person to volunteer for a vaccine trial or which are disincentives to participation, along with preparedness of the larger community for trials. Personal concerns for health and for the impact of the epidemic on families and country were common motivations for participation. The danger of an experimental vaccine and the stigma of a positive HIV antibody test as the result of vaccination are major concerns and disincentives. The health, educational, and local non-governmental sectors are identified as having important roles to play in assuring preparedness for trials, although significant challenges exist to achieving community preparedness.

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 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)0.024
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.234
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0240.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.126
GPT teacher head0.440
Teacher spread0.315 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations27
Published2006
Admission routes1
Has abstractyes

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