Victim Participation at the Extraordinary Chambers in the Courts of Cambodia: Challenges to the Civil Party Framework and Lessons for the Future
Bibliographic record
Abstract
This paper examines the victim participation framework at the Extraordinary Chambers in the Courts of Cambodia (ECCC or Court), established to deal with crimes during the Khmer Rouge regime. The background which has led to the creation of the ECCC will be explained, before the paper will look at the way the Court is structured to include civil parties. The Court has consistently limited the civil parties’ role since its establishment and these limitations and the justifications are outlined in the paper. Solutions in the context of the ECCC are then considered, although due to the political environment, no changes in favour of victim rights are likely. Future models are considered, with the benefits of a Truth and Conciliation Commission’s analysed by looking at Sierra Leone and East Timor, as examples of successful frameworks where both a Court and a Truth and Reconciliation Commission proceeded simultaneously. This paper concludes that although every situation requiring a judicial response will be different, the option of having both a Court and a Truth and Reconciliation Commission can fulfil multiple victim needs.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.023 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 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".