The Responsibility To Protect and the Conflict in Darfur: The Big Let-Down
Bibliographic record
Abstract
Abstract This article discusses the international response to the conflict in Darfur from 2003 onwards in order to explore some of the key challenges related to implementing the responsibility to protect (R2P). First, we show that the debates on R2P in connection to Darfur translated into little more substantive action than the pragmatic decision to deploy peace operations with mandates that included civilian protection, as suggested by the African Union (AU) Mission in Sudan (AMIS), and later by the hybrid UN—AU Mission in Darfur (UNAMID). Second, we argue that the international response to Darfur illustrates three major challenges to R2P implementation. These are: political limitations inherent in the R2P framework; moral dilemmas emerging from military action; and tactical challenges, as exemplified by the struggles faced by the AU and the UN in Darfur. We conclude that the international failure to offer meaningful protection in Darfur highlights the need for continued caution and critical analysis of the ways in which R2P is conceptualized and implemented.
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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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.030 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".