Bibliographic record
Abstract
There are multiple competing demands made of the international criminal justice project. It must be at once effective, just in terms of outcome, and fair towards defendants. Two sets of tensions created by these demands are discussed in this chapter. The first is the tension between efficacy and symbolism; the desire for an efficient system of prosecutions requires a clarity of goals, yet there are numerous and competing goals asserted by those with different interests, including victims, defendants, and transitional justice advocates. An overarching central goal of ‘increasing the public sense of accountability for mass atrocity’ is identified, coupled with the symbolic function of ICL as norm expression and history writing. Identifying leaders as independent actors in relation to mass atrocity crimes is more effective both with respect to the central goal and with respect to the expressive function of trials. The second set of tensions has to do with balancing fairness and justice, two core requirements of any criminal law system. The outcome of a trial must be fair to the defendant and just with respect to the victims’ interests and the crimes committed. Linked to these two notions are the limiting principles of legality and culpability. Their application lead to the conclusion that no-one should be held liable for actions over which they have no control, and that those with more control should be held to a higher standard of responsibility. Thus in ICL, focusing upon the leaders of mass atrocity as especially responsible is both warranted and necessary.
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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 | 0.010 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.038 |
| Scholarly communication | 0.018 | 0.015 |
| Open science | 0.001 | 0.014 |
| Research integrity | 0.004 | 0.012 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".