Africa and the Kigali Amendment
Bibliographic record
Abstract
The Kigali Amendment to the Montreal Protocol was adopted in Rwanda by 197 nations in October 2016. Building on 30 years of the successful elimination of ozone-depleting substances, the amended Montreal Protocol now aims for a worldwide phase down of the potent greenhouse gases, HFCs, thereby preventing the direst consequences of climate change. African countries are among those already hit hardest by the growing consumption of high Global Warming Potential (GWP) substances, which impact human health, security and economic growth. However, African countries also face a unique opportunity to directly switch to solutions that do not harm the environment, and to help move towards a sustainable economic transition and positive societal change. This report summarizes current needs, concerns and challenges faced by African nations in making the Kigali Amendment a success. It also provides general guidance on the Amendment's major obligations, deadlines and opportunities. Finally, the report suggests possible sets of activities to be adopted for a smooth and effective KA ratification, implementation and enforcement.
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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 | 0.008 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.014 | 0.006 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.036 | 0.010 |
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".