Some Lessons on Complementarity for the International Criminal Court Review Conference
Bibliographic record
Abstract
The ICC practice in the last seven years disclosed a number of contentious issues within the legal and practical parameters of complementarity. The complementarity regime serves as a system to encourage and facilitate the compliance of states with their responsibility to investigate and prosecute international crimes. However, this has not been materialized in practice. The ipso facto admissibility of cases of inactions proved to be damaging to positive complementarity. It opens the door widely for overloading the ICC with many cases of no added value for the ICC and for ending impunity. Article 17 has been interpreted narrowly by the Prosecutor and the Chambers, and this interpretation and policy needs to be amended. In this regard, some amendments to Article 17 could be suggested; mainly to correlate explicitly Article 17 to preambler paragraph six of the Statute, and to use judicial and non-judicial tools to encourage national jurisdictions to prosecute. There are number of challenges that are awaiting the ICC Review Conference in Uganda in 2010. It will be a huge missed opportunity if complementarity is not discussed and addressed in this Conference. The hope is that the Review Conference will courageously address this vital issue to revive the path of the ICC in the direction of encouraging national jurisdictions to contribute to ending impunity, while the ICC remains vigilant to ensure justice is done in conformity with the ICC Statute.
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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 | 0.160 | 0.269 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.021 | 0.030 |
| Scholarly communication | 0.041 | 0.032 |
| Open science | 0.006 | 0.019 |
| Research integrity | 0.036 | 0.037 |
| Insufficient payload (model declined to judge) | 0.015 | 0.004 |
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".