Looking for ‘Justice’ in All the Wrong Places: An International Mechanism or Multidimensional Domestic Strategy for Mass Human Rights Violations in Sri Lanka?
Bibliographic record
Abstract
I use the United Nations Panel of Experts on Accountability in Sri Lanka’s recommendation to create an international mechanism and recent demands for justice as a springboard to argue that the creation of a new ad hoc international or hybrid criminal tribunal for Sri Lanka may not produce the expected results of prosecuting those responsible for mass human rights violations. I argue that such an initiative will not heal the ruptures and cleavages among the different ethnic communities in Sri Lanka. By teasing out the political nature of international criminal law and the embedded nature of the history of international law, this chapter suggests that the creation of an international institution may not bring to justice the divergent perpetrators of war crimes. Rather, the politics of international institutions and the history of international law may allow for ‘regulatory capture’ and the continuing rise of international experts as seen through the illustrative history of the International Criminal Tribunal for Rwanda.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.033 |
| Scholarly communication | 0.013 | 0.010 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.004 | 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".