Community stakeholder engagement during a vaccine demonstration project in Nigeria: lessons on implementation of the good participatory practice guidelines
Bibliographic record
Abstract
INTRODUCTION: To report on the successes and challenges with implementing the good participatory practice guidelines for the Nigerian Canadian Collaboration on AIDS Vaccine (NICCAV) project. METHODS: An open and close ended questionnaire was administered to 25 randomly selected community stakeholders on the project. The questions sought information on perception about the community entry, constitution and function of the community advisory board (CAB) and community based organization (CBO), media engagement process, and research literacy programmes. The quantitative and qualitative data were analysed and findings triangulated. RESULTS: The project exceeded its targets on CBO engagement and community members reached. Stakeholders had significant improvement in knowledge about HIV vaccine research design and implementation (p=0.004). All respondents felt satisfied with the community entry, CAB constitution process, function and level of media engagement; 40% were satisfied with the financial support provided; 70% felt the community awareness and education coverage was satisfactory; and 40% raised concerns about the study site selection with implications for study participants' recruitment. CONCLUSION: The NICCAV community stakeholder engagement model produced satisfactory outcomes for both researchers and community stakeholders. The inclusion of an advocacy and monitoring plan enabled it to identify important challenges that were of ethical concerns for the study.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.237 | 0.142 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.010 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.004 | 0.014 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".