The Role of Transnational Actors in African Social Policy
Bibliographic record
Abstract
Abstract How did transnational actors interact with social policy in Africa before and during the pandemic? How should they interact with social policy in Africa in the post-pandemic era? This chapter examines these broad questions from a perspective that recognises that transnational actors, just like other non-state actors, are significant policy players in African social policy as they deploy material and ideational mechanisms in their interaction with domestic players. The COVID-19 pandemic affected the regular ways of doing things and impacted the relationship between transnational actors and African countries. How were transnational actors involved in the management of the COVID-19 pandemic in Africa? What should be the roles of transnational actors in a post-COVID Africa? Will it be just business as usual again? The chapter addresses these specific questions through the lens of institutional theory. We argue that the pandemic and related changes affecting multinational and bilateral organizations point to the need for institutional reform.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".