State Cooperation with Respect to National Proceedings
Bibliographic record
Abstract
Building on the success of previous editions (Cryer et al.), this popular textbook is now expanded and updated in a 5th edition featuring two new co-authors, Elies van Sliedregt and Valerie Oosterveld. A market leader and one of the most globally trusted textbooks on international criminal law, it is known for its accessible and engaging tone and for an even-handed approach that is both critical and constructive. Comprehensively updated and rewritten, this new edition introduces readers to the main concepts of international criminal law, as well as the domestic and international institutions that enforce it, and addresses the latest challenges and controversies surrounding the International Criminal Court. Written by a team of international criminal lawyers who have extensive academic and practical experience in the field, the book engages with critical questions, political and moral challenges, and alternatives to international justice. It contains helpful references to other literature, making it a valuable research resource.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.086 | 0.030 |
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".