Community Security and Justice under United Nations Governance: Lessons from Chiefs’ Courts in South Sudan’s Protection of Civilians Sites
Bibliographic record
Abstract
This article examines the public authority of chiefs’ courts within the United Nations Mission in South Sudan (UNMISS) Protection of Civilians Sites (PoCs). After December 2013, UNMISS peacekeepers opened the gates of their bases to around 200,000 civilians fleeing war. This unintentionally created a legal and political anomaly. Over time, conflicts and crimes rose within the sites, and UNMISS improvised a form of administration. But while the internationals sought technical solutions, people displaced within the sites turned to familiar ‘customary’ methods to manage problems of insecurity, establishing chiefs’ courts. The PoC sites became an arena of plural authorities, with chiefs working alongside camp administrators, peacekeepers and humanitarian actors. We explore how and why the chiefs responded to insecurity within the sites and whether they engaged with, or diverged from United Nations actors and international norms. We demonstrate that justice remains central to the provision of security in contexts of war and displacement. International peace interventions are rightly wary of ‘customary’ justice processes that prioritise communities and families at the expense of individual rights, but this unique case shows that they are sources of trust and consistency that are resilient, adaptable and can contribute to human security.
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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 | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.029 | 0.021 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.004 | 0.006 |
| 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".