Productive failure, African agency, and security cooperation in West Africa: The case of the G5 Sahel
Bibliographic record
Abstract
Abstract This paper examines South–South security cooperation and regional organisations (ROs) in Africa. Much of the literature on peace and conflict in Africa has focused on ROs and the African Peace and Security Architecture (APSA). Guided by the mantra ‘African solutions to African problems’, these organisations have facilitated several instances of African-led security cooperation. Yet ROs have limited agency and capacity, are institutionally rigid, and are often donor-dependent. As a result, ad hoc security initiatives such as the G5 Sahel and Accra Initiative – our case studies – are on the rise. While such initiatives are better adapted to local context and feature higher levels of autonomy (relative to APSA), we critique this view by showing how donors pressure and trap African governments facing transnational security threats into ad hoc initiatives. These initiatives transform into ‘zombified’ security institutions that rarely live up to the elevated expectations of African and Western stakeholders. This creates a paradox for debates around African agency in security affairs: ad hoc initiatives lock African states into security frameworks that do not respond to their needs but also facilitate the pursuit of donor funding, reassert the national scale of sovereignty, and incentivise new forms of bilateral security cooperation.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.021 | 0.020 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".