AFRICAN REGIONAL AND INTERNATIONAL COORDINATION: HOW COVID-19 ADVANCED INTEGRATION TRENDS AND SOUTH-SOUTH COOPERATION
Bibliographic record
Abstract
Africa is one of the world's forerunners in terms of political integration. Already in the 1960s, the Organisation of African Unity had 32 states united under a common charter. Moreover, through joint projects with Latin American and Asian partners, African states have joined some of the primary experiences of South-South Cooperation, particularly in the areas of healthcare and infrastructure. Taking this historical context into account, this paper examines how the highly competitive reality of the COVID-19 pandemic has impacted the continent. We argue that the constraints imposed by the new coronavirus outbreak have strengthened the African Union's role in advancing collective action and encouraged self-sufficiency. Furthermore, we analyse how South-South Cooperation offered a platform for immediate response when access to disputed medical supplies in the world market was difficult. We conclude that the COVID-19 crisis has contributed to consolidating African regional integration in the long-term, as well as its coordination with partner emerging countries, with consequences for the African Union’s priorities in terms of foreign affairs in the future.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".