Shifting Alliances: The role of non-regional powers in sahel security after ECOWAS departures
Bibliographic record
Abstract
The security landscape of the Sahel region is undergoing a profound transformation following the withdrawal of the Economic Community of West African States (ECOWAS) from several member states. This shift has created a power vacuum, prompting non-regional actors—most notably Russia, France, and China—to redefine their roles in regional stability and governance. These external powers leverage military, economic, and diplomatic strategies to secure influence, often pursuing competing agendas that reshape security dynamics and political alignments in the region. Russia has expanded its footprint through military cooperation and security agreements, capitalizing on rising anti-Western sentiments and disillusionment with traditional partners. The Wagner Group, a Russian paramilitary force, has played an increasing role in counterterrorism operations and regime protection, particularly in Mali and Burkina Faso. Meanwhile, France, historically entrenched in the Sahel through Operation Barkhane and bilateral security agreements, faces diminishing influence as local governments pivot toward alternative partnerships. French disengagement has sparked new geopolitical realignments, with some states actively seeking security support beyond their former colonial ties. China's involvement, while less overtly military, focuses on economic statecraft and infrastructure investments under the Belt and Road Initiative (BRI). Through financial aid, arms sales, and economic diplomacy, China seeks to maintain strategic relationships while avoiding direct military entanglement. As competition among these actors intensifies, the Sahel’s security trajectory remains uncertain, with implications for regional stability, counterterrorism efforts, and governance. This study examines the evolving role of non-regional powers in Sahel security post-ECOWAS, analyzing their strategic interests, engagement tactics, and the broader geopolitical consequences of their involvement.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".