P06-05. Building capacity for HIV/AIDS prevention trials in Africa: Evidence from three projects supported by the Global Health Research Initiative
Bibliographic record
Abstract
In 2006 the Canadian Global Health Research Initiative launched, a CAD$ 3 million program designed to strengthen the capacity for clinical trials of HIV vaccines and other prevention technologies in Africa. Three teams comprised of both African and Canadian HIV researchers received two-year HIV/AIDS Prevention Trials Capacity Building grants. The three teams are using diverse but complementary capacity building approaches with a mix of African-Canadian and African-African research partnerships. In West Africa, a Benin-Canada partnership is strengthening capacity for clinical trials by: 1) training African investigators; 2) supporting the creation of the national Ethics Committee for health research in Benin; and 3) supporting the creation of a HIV/STI Prevention Research Unit within the Faculty of Health Sciences in Benin. A second Africa-Canada team created and supported the Canada-Africa Prevention Trials (CAPT) network which facilitates north-south and south-south research partnerships in this domain. The third team used the grant to build the African Development of AIDS Prevention Trial (ADAPT) capacity program. This program is strengthening the capacities of local health systems to design, conduct, and use the evidence from large-scale AIDS prevention trials in southern Africa. These three projects are helping to build African capacity to undertake HIV/AIDS clinical trials in Africa by: 1) combining capacity building strategies both at the individual institutional levels and 2) strengthening a range of skills and knowledge that includes epidemiology, community and stakeholder engagement, research management, research ethics and grant writing. These projects have created an important foundation that is strengthening individual and institutional capacities and helping African HIV investigators gain more autonomy, initiate and conduct research projects and obtain grants. However, capacity building needs longer-term funding to stimulate real advancements in the field of HIV prevention. The early results of this program persuaded funders to offer a new program with longer term grants.
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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 | 0.118 | 0.383 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.069 | 0.011 |
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".