Clan Cleansing in Somalia: Reflections on the Role of Somali Customary Law in Transitional Justice
Bibliographic record
Abstract
Somalia has been overwhelmed by protracted violent conflicts for more than two decades, resulting in clan cleansing, massive human rights violations, and the total collapse of the state. Building on the conceptual approaches to critical memory work and moral repair in Somalia proposed in Kapteijns’ “Clan Cleansing in Somalia” (2013) and drawing on the ongoing joint research I am conducting with R. Abdulkadir of New York University (“Reconstructing Somalia’s Failed Nation State: Paths to Peace Building”), this paper analyzes how Somalis might find transitional justice mechanisms that address the numerous and enormous human rights violations that have been committed by many different Somali actors. In particular, this paper will explore what role the Somali “xeer” (customary law) may play in the search for appropriate transitional justice mechanisms for Somalia.
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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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.034 | 0.068 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.009 | 0.010 |
| Insufficient payload (model declined to judge) | 0.003 | 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".