The “secret war”: Silence, testimony, and wartime sexual violence
Bibliographic record
Abstract
Breaking the silence around wartime sexual violence is often understood as paramount to ending it. Many survivors feel compelled to publicly testify to prevent future harms, contest denial, and hold perpetrators to account. Yet, testimony is not always spoken, and silence should not be elided with powerlessness. In this article, we conceptualize the space in-between silence and voice as a form of multi-modal testimony that is given to protect, sustain, and reimagine relationships. We consider this in relation to the efforts of Adok, a woman abducted and forced into marriage by a rebel group in northern Uganda. Following her escape and return home with two children, Adok faced what is described as the “secret war”: ongoing structural and lateral violence. Her efforts to hold the father of her children to account attests to the “secret war,” and calls for a collective response to protect the future of her children.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".