Too Little, Too Late: The Constraining Effect of Traditional Peacekeeping Norms On the UN Protection Forces and its Consequences
Bibliographic record
Abstract
During the Bosnian War (1992-1995), despite the efforts of the United Nations Protection Force (UNPROFOR), thousands of lives were lost in heinous attacks on Bosnian Muslims, perpetrated mostly by Bosnian Serbs. Using a constructivist approach, this paper investigates why the United Nations (UN) failed in their mandate to protect the Bosnian people. To do so, it examines the deeply entrenched norms that have traditionally guided UN peacekeeping – namely, impartiality and non-use of force. By tracing the key events that defined the UN’s involvement in this conflict in relation to existing theoretical models of norm emergence and evolution, the paper finds that the UN’s strict adherence to these principles significantly contributed to their failure to achieve their objectives. This is evidenced by the limited capacity of the UN peacekeepers during the conflict, the swift improvement of conditions following the replacement of UNPROFOR with the NATO-led Implementation Force, and the developments within the UN that ensued in the following years. The paper concludes with potential implications of these findings and suggestions for further research.
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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 | 0.009 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.010 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".