The Curious Visibility of Wartime Rape: Gender and Ethnicity in International Criminal Law
Bibliographic record
Abstract
Wartime sexual violence against women has become a clearly visible and established issue of concern in the emerging international criminal apparatus. But what is it that we see when we make violence against women visible as an international criminal law issue? Are there limits to the strategy of seeing women, and the human rights abuses they suffer, within the work of war crimes tribunals? In this paper, I focus on the Yugoslav and Rwandan Tribunals as venues at which violence against women has been remarkably visible. I consider two decisions, Gacumbitsi and Krstic, one from each of the Tribunals, that reveal the ways in which sexual violence and inequality are both seen and unseen in the Tribunals' analyses. I focus, in particular, on the intersection of gender and ethnicity in the work of the Tribunals, and question if ethnicity may be emerging as a meta-narrative within which sexual violence against women materializes in constrained and limited ways.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.028 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".