Prosecuting the Nexus between Terrorism, Conflict-Related Sexual Violence and Trafficking in Human Beings Before National Legal Mechanisms: Case Studies of Boko Haram and Al-Shabaab
Bibliographic record
Abstract
UN Security Council Resolution 2331 (2016) recognizes that ‘acts of sexual and gender-based violence, including when associated to trafficking in persons, are known to be part of the strategic objectives and ideology of certain terrorist groups, used as a tactic of terrorism and an instrument to increase their finances and their power through recruitment and the destruction of communities.’ In the same resolution, the Council noted that such trafficking, particularly of women and girls, ‘remains a critical component of the financial flows to certain terrorist groups’ and is ‘used by these groups as a driver for recruitment’. Boko Haram and Al Shabaab are among the main terrorist groups that have used human trafficking (including for sexual exploitation) and conflict-related sexual violence as tactics of terrorism, also called ‘sexual terrorism’. This article will: 1) explain the nexus between these three crimes; 2) focus on its different manifestations in the context of these terrorist organizations; and 3) reflect on the possibilities for national criminal prosecution. To assist in the fight against impunity and increase accountability, this article provides suggestions to facilitate the successful prosecution of sexual terrorism in a more survivor-centric way. This article is a working draft, the final version of which will be included in the Special Issue on Justice and Accountability for Sexual Violence in Conflict: Progress and Challenges in National Efforts to Address Impunity, being edited by both the Journal of International Criminal Justice and the UN Team of Experts on the Rule of Law and Sexual Violence in Conflict.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".