The Congo Trap: MONUSCO Islands of Stability in the Sea of Instability
Bibliographic record
Abstract
2014 was a hopeful year for the Democratic Republic of Congo (DRC). The M23 movement had been defeated in military operations in which one of the last peacekeeping experiments, the UN Force Intervention Brigade, had played a decisive role. A third UN stabilization plan, the ‘islands of stability’ was proposed to continue the stabilization of a country considered in a post-conflict phase. However, the number of internally displaced persons (IDPs) has almost tripled in the country since 2007. This article will argue that DRC is still immersed into an old social conflict that existed before the Congo Wars and the roots of which are not being addressed. It will argue that the United Nations Organization Stabilization Mission in the Democratic Republic of the Congo (MONUSCO) and the ‘islands of stability’ strategy can address some of the secondary causes of the Congo conflict, such as its internationalization, the presence in DRC of foreign armed groups or the ‘blood minerals’, but cannot address its primary causes: land struggles, an old cycle of violence and the fragmentation of the Congolese society and political elite that is jeopardizing the restoration of the state authority. The huge dimensions of each of these factors make the Congo conflict ‘one of the most complex and intricate environments ever faced by a peacekeeping mission’, for which MONUSCO’s mandate, resources and stabilization strategy do not seem powerful enough. When the UN organized the 2006 elections legitimized a ‘spoiler state’, the bottleneck of all the reforms needed to stabilize the country. The UN fell thus into a trap and became part of the conflict. Lessons learned should be taken for future UN operations.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".