Crimes of Sexual Violence within International Criminal Law: A Historical Outline
Bibliographic record
Abstract
This article will provide a synoptic historical outline of international criminal law (ICL) from a gender perspective. An effort is made to highlight the landmark stages in the evolution of the ICL, particularly in its treatment of rape and other sexual crimes perpetrated against women during armed conflict. For this purpose, a critical examination of Nuremberg and Tokyo tribunals, criminal tribunals for Yugoslavia and Rwanda as well as Special Court for Sierra Leone, and the International Criminal Court is attempted. Endeavour is to outline the gender and sexual crimes jurisprudence developed by the above mentioned international criminal tribunals as well as courts, and then to examine its effectiveness in prosecuting crimes of rape and sexual violence carried out against women. An analysis of what might have gone wrong within the ICL in dealing with rape and crimes of sexual nature is also attempted.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.006 | 0.016 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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".