The Tribunals and the Renaissance of International Criminal Law: Three Themes
Bibliographic record
Abstract
We are delighted to participate in this symposium on the legacy of the International Criminal Tribunals for the Former Yugoslavia and for Rwanda (Tribunals; respectively, ICTY and ICTR). We have been asked to offer reflections on the Tribunals’ impact on substantive international criminal law (ICL)—in particular, the definitions of crimes and the modes of liability. Given the enormity of the topic, we can offer only a cursory and impressionist sketch of the terrain, and draw attention to a few intriguing features along the way. We will not attempt to survey the Tribunals’ jurisprudence or the related academic literature. Instead, our aim is simply to highlight three themes underlying the Tribunals’ elaboration of substantive legal standards. For the nonspecialist, this sketch may provide a helpful overview of the evolution of ICL. For the specialist, this sketch may bring into slightly sharper relief some underlying patterns in the Tribunals’ work. We will also offer some broader thoughts about the Tribunals in the overall arc of ICL, and how their structure and priorities have left a lasting, distinctive imprimatur on ICL.
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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 | 0.012 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.023 | 0.070 |
| Scholarly communication | 0.027 | 0.012 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.005 | 0.012 |
| Insufficient payload (model declined to judge) | 0.004 | 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".