Bibliographic record
Abstract
In comparison to sentences meted out by international tribunals at Nuremberg, Tokyo and Arusha, and by domestic courts, sentences handed down at the International Criminal Tribunal for the former Yugoslavia (ICTY) have been inexplicably lenient. Factors that may have contributed to the high proportion of low sentences at the ICTY include undue emphasis on mitigating factors, particularly those of particular importance to the Tribunal, the use of plea agreements, the absence of a separate sentencing hearing following conviction and the practice of using global (rather than separate) sentences. To make sentences more proportionate to the crimes committed, the objectives of sentencing should be clarified and re-evaluated. Greater weight should be given to deterrence. In assessing the gravity of the offence, the quantum of harm caused to and suffering experienced by direct and indirect victims of the crime merits more detailed evaluation. The importance of mitigating circumstances (such as combating historical revisionism, pleading guilty, expressing remorse and voluntary surrender) should continue to be fully recognized but those factors should not attract excessive weight. Plea bargaining and plea agreements should be encouraged because they are indispensable to the Tribunal, an institution with significant temporal, practical and resource limitations. The sentencing process should take place after conviction. A sentencing Chamber should be obliged to state the starting point of the sentence which it deems appropriate and then quantify the discounts it gives to each mitigating factor. Greater consideration should be given to imposing consecutive rather than concurrent sentences. The decision not to adopt sentencing guidelines represents a missed opportunity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.067 | 0.021 |
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".