The UN at war: examining the consequences of peace-enforcement mandates for the UN peacekeeping operations in the CAR, the DRC and Mali
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The UN peacekeeping operations in the Central African Republic (CAR), Democratic Republic of Congo (DRC) and Mali were in 2013 given peace enforcement mandates, ordering them to use all necessary measures to ‘neutralise’ and ‘disarm’ identified groups in the eastern DRC and to ‘stabilise’ CAR and northern Mali. It is not new that UN missions have mandates authorising the use of force, but these have normally not specified enemies and have been of short duration. This article investigates these missions to better understand the short- and long-term consequences, in terms of the willingness of traditional as well as Western troop contributors to provide troops, and of the perception of the missions by host states, neighbouring states, rebel groups, and humanitarian and human rights actors. The paper explores normative, security and legitimacy implications of the expanded will of the UN to use force in peacekeeping operations. It argues that the urge to equip UN peacekeeping operations with enforcement mandates that target particular groups has significant long-term implications for the UN and its role as an impartial arbitrator in post-conflict countries.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 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 | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 it