Bibliographic record
Abstract
This paper critically examines landmark precedents set by the International Criminal Tribunals for Rwanda (ICTR) and the former Yugoslavia (ICTY) in prosecuting sexual violence as a means of genocide. Under statutory international humanitarian law, sexual violence is not explicitly listed as a means of genocide, leaving the chambers of these aforementioned tribunals to interpret various legal instruments in order to prosecute the perpetrators of sexual violence during the armed conflicts. In this context, the ICTR set a groundbreaking precedent in the Akayesu case by recognizing sexual violence as a means of committing genocide, thereby elevating the status of these sexual crimes to one of the gravest violations under international law. By contrast, the ICTY was notably reluctant to rule sexual violence and rape as a charge of genocide, electing instead to prosecute it solely as a crime against humanity. By analyzing key cases such as Akayesu at the ICTR and Kunarac et al. and Kristic at the ICTY, this paper argues that the latter’s reluctance to recognize sexual violence as a genocidal act has influenced the International Criminal Court’s (ICC) limited application of genocide charges in contemporary cases involving sexual violence. Consequently, victims of gender-based violence during armed conflict continue to face challenges in securing proper justice and accountability. As such, this analysis highlights the need for a re-evaluation of both the existing statutory and judicial understanding of genocide under international law to reflect the ICTR’s broader recognition of the relationship between gender-based sexual violence, armed conflict, and genocidal intent.
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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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.012 | 0.008 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.148 | 0.052 |
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".