The (D)evolution of a Norm: R2P, the Bosnia Generation and Humanitarian Intervention in Libya
Bibliographic record
Abstract
The March 2011 NATO intervention in Libya has been widely touted as evidence of a new international norm that has come about as a result of advocacy of the Responsibility to Protect (R2P) principle (Ban 2011; Gerber, 2011; Adams, 2011). Likewise, the Libya intervention has been characterized as an ‘unprecedented moment’ that is indicative of a new commitment and consensus by states that they have an obligation — indeed, a responsibility — to protect people who are being grossly abused by their own government (Williams 2011: 249). In contrast to the position that the Libya intervention is somehow groundbreaking or indicates the emergence of a new norm of humanitarian intervention that has been empowered by R2P advocacy, we argue that what enabled the Libya intervention is essentially an international normative environment that was brought about by precedents set during humanitarian interventions in the 1990s, while its proximate causes were the unique political and empirical circumstances that surrounded the Libya crisis. What supplemented this similarity in normative environments and confluence of political factors was a generation of policy analysts, advocates and practitioners who used the failures of the 1990s as a set of formative experiences that provided shortcut comparisons to springboard the Libya intervention.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.021 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| 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".