Assessing the African Union Concerns about Article 16 of the Rome Statute of the International Criminal Court
Bibliographic record
Abstract
Abstract This article assesses the African Union’s (AU) concerns about Article 16 of the Rome Statute of the International Criminal Court (ICC). It seeks to articulate a clearer picture of the law and politics of deferrals within the context of the AU’s repeated calls to the United Nations Security Council (UNSC, or the Council) to invoke Article 16 to suspend the processes initiated by the ICC against President Omar Al Bashir of Sudan. The Council’s failure to accede to the AU request led African States to formally withhold cooperation from the ICC in respect to the arrest and surrender of the Sudanese leader. Given the AU’s continued concerns, and the current impasse, fundamental questions have arisen about the Council’s authority to exercise, or not exercise, its deferral power. This culminated into a November 2009 African proposal for an amendment to the Rome Statute to empower the UN General Assembly to act should the UNSC fail to act on a deferral request after six months. Although ICC States Parties have so far shown limited public support for the AU’s proposed amendment to the deferral provision, this article examines its merits because a failure to engage the “Article 16 problem” could impact international accountability efforts in the Sudan, and further damage the ICC’s credibility in Africa. This unresolved issue also has wider significance given that the matters underlying the tension ‐ how ICC prosecutions may be reconciled with peacemaking initiatives and the role and power of the Council in ICC business ‐ will likely arise in future situations from around the world.
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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 | 0.059 | 0.112 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.008 | 0.012 |
| Scholarly communication | 0.017 | 0.008 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".