Beyond Repair?: Collective and Moral Reparations at the Khmer Rouge Tribunal
Bibliographic record
Abstract
Instituted to try serious crimes committed during the Khmer Rouge period, including genocide, crimes against humanity, and war crimes, the Extraordinary Chambers in the Courts of Cambodia (ECCC) has been heralded as an historic opportunity for the Court to develop international jurisprudence on reparations and to provide a workable model for how best to address victims’ rights in international criminal trials. At the end of Case 001, however, the Court seems to have fallen well short of those expectations. This article examines how and why the ECCC failed to live up to the high expectations that accompanied its institution. It argues that political pressure, financial constraints, and the absence of a clear understanding of what “collective and moral reparations” entail have all contributed to the Court's failure to realize its original intention to advance the international reparations agenda.
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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 | 0.006 | 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 | 0.022 | 0.027 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.012 | 0.010 |
| Insufficient payload (model declined to judge) | 0.005 | 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".