Strengthening climate research capacity in Africa: lessons from the ‘Climate impact research capacity leadership enhancement’ project
Bibliographic record
Abstract
Abstract Climate Change research plays a pivotal role in Africa’s sustainable development by providing the required scientific evidence to inform the design of Africa’s development priorities. The need for enhanced climate research is heightened by the fact that Africa is one of the regions likely to be most affected by the impacts of global warming and climate change. This paper highlights some key lessons learnt from the provision of climate research support in Africa under the Climate Impact Research Capacity Leadership Enhancement (CIRCLE) project implemented by the African Academy of Sciences and the Association of Commonwealth Universities in partnership with the United Kingdom’s Foreign, Commonwealth, and Development Office, Vitae, and the University of Greenwich’s Natural Resources Institute. The paper discusses the early-career research support landscape in Africa, the place of institutional strengthening in climate research programming, and the need for a well-coordinated community and public engagement in the climate research projects. Lessons from the CIRCLE programme provide useful insights for future climate research programme design and early-career research support initiatives in Africa.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".