Relationality, Culpability and Consent in Wartime: Men’s Experiences of Forced Marriage
Bibliographic record
Abstract
Rights-based approaches to forced marriage in wartime document forms of harm women experience, to the exclusion of men’s experiences. Such framing problematically reiterates a binary of women/men, victim/perpetrator and consent/coercion. Arguably, this delineation is useful in supporting projects of culpability and legal redress. However, what does such vocabulary obfuscate or render invisible? We draw from the experiences of men demobilized from the Lord’s Resistance Army (LRA) and presently living in northern Uganda to consider how relationships and social accountabilities are governed in settings of coercion. We argue that forced marriage in wartime cannot be understood without examining the multiple relationalities on which it is contingent. We broaden the remit of men’s relationships to women in the LRA to consider how men’s relations to each other and to their children shaped their experiences of marriage during the war. We conclude by reflecting on concepts of consent and culpability in coercive settings.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.026 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".