The Geopolitics of Humanitarian Intervention: The Responsibility to Protect in Libya
Bibliographic record
Abstract
This article analyzes the geopolitical narratives produced by France, the United Kingdom, and the United States from 15 February through 18 March 2011 as a humanitarian intervention in Libya was debated. We analyzed 146 statements and press releases, as well as official documents including the United Nations Charter, the Genocide Convention, and the doctrine of Responsibility to Protect (R2P), to gauge how the intervention was justified and how it was situated within the broader framework of humanitarianism. We argue that the thresholds for intervention are not well articulated and that the differences between the situation in Libya, which required an intervention, and others such as Bahrain, Darfur, or Syria that did not are unclear. The lack of thresholds and consistency creates a situation in which particular countries can use the cover of humanitarianism to legitimate an effort to remove a troublesome regime.
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How this classification was reachedexpand
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".