The African Union’s Response to the Libyan Crisis: A Plea for Objectivity
Bibliographic record
Abstract
Abstract The African Union (au)’s role in the Libyan crisis drew opprobrium from many observers. To some, the Union’s response to the Libyan debacle – which was no response in terms of military engagement – came as no surprise. Gaddafi was one of the biggest funders of the continental organization. For others, the au’s poor showing is confirmatory that African regional organizations may have the legal competence to take enforcement action against erring Member States but they have neither the resources nor the political will required to effectuate such measures. While these factors count in any reckoning of the au’s handling of the Libyan crisis, this author argues that most analysts fail to account for the bewildering legal complexities the Union found itself in Libya. A closer look at the majority of existing analyses of the au’s response to the Libyan crisis reveals a widely unbalanced picture painted mostly by the legal analysts’ account of the organization performance and by the au’s evaluation of its own performance. The consequence of either approach is often too lopsided to inform a prudent outcome.
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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 | 0.021 | 0.047 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.012 | 0.025 |
| Scholarly communication | 0.021 | 0.012 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.011 | 0.010 |
| Insufficient payload (model declined to judge) | 0.008 | 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".