Prosecuting Gendered Violence in International Law: The Paradox of Wartime Violence
Bibliographic record
Abstract
By an examination of the judgments of the International Criminal Tribunals, this essay reflects upon the feminist discourse of rape as an instrument of genocide, which has been invoked to call for invervention in conflict zones. I argue that the construction in International law of sexual violence as a 'weapon' that'one side' picks up to harm the other, paradoxically makes the victims of violence largley invisible. This process of invisibility occursin international law when victims of wartime sexual violence, in order to have their experiences represented and recognized at trial, are expected to speak of the violence in a way that weaves fact into a community’s identity. International Criminal Tribunals offer a uniform narrative with distinct language, by which witnesses are permitted to testify to, their stories of violence. Consequently a victim’s individual memory is rendered invisible and transformed in international law as collective memory. This uniform narrative of rape fits well into the memory of collective suffering of a group, however it prevents nuanced understandings of wartime violence, found in the individual memory of victims, from being comprehended.
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 | 0.015 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.021 | 0.079 |
| Scholarly communication | 0.024 | 0.018 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.009 | 0.011 |
| Insufficient payload (model declined to judge) | 0.005 | 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".