Multilateralism and Management of Public Health Emergencies: A Case Study of the Africa Joint Continental Strategy for COVID-19 Outbreak
Bibliographic record
Abstract
As the world continues to grapple with a pandemic that struck in January 2020, the responses of governments and international organisations to control and combat it varied albeit with different levels of success. Some responses gave rise to nationalist as well as anti-multilateral and -international sentiments and actions, including the politicisation of the pandemic and a retreat from multilateral and international institutions of cooperation. However, the African Union’s response was a beacon of multilateralism as manifested by the adoption of an Africa Joint Continental Strategy for COVID-19 Outbreak. This instrument is a coherent and pervasive framework for combatting the pandemic and forms the basis of the continent’s response by informing the responses of the regional economic communities and member states. Despite this important outline of policy articulation that is geared towards informing policy convergence, the Africa Joint Continental Strategy remains under-analysed and under-appreciated as an example of agency, effectiveness, leadership, multilateralism and indeed sagacity.
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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 | 0.018 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.015 | 0.010 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.006 | 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".