Bibliographic record
Abstract
The article addresses the relationship between the Extraordinary Chambers in the Courts of Cambodia (ECCC) and the supposed constituents of that transitional justice institution. The article sets out to offer a sociological methodology that TJ mechanism could contemplate in the process of enabling victims/witnesses to narrate justice and transition in their own terms and using Cambodia as a case study. It offers a theoretical and methodological approach to be reflected upon by transitional justice scholars and practitioners, which may enable a more victim-centered attitude in practical interactions with atrocity survivors (not a cure-all policy solution). My own research has actively used this methodology to serve this task. This article draws on 70 in-depth oral histories taken from regime survivors, former Khmer Rouge, religious leaders, international and domestic jurists at the ECCC ,witnesses, civil parties, historical and cultural figures from multiple communities in 10 provinces in Cambodia. I have established some basis for situating individual voices into a specifically Cambodian intellectual context. In discussing the Cambodian case from the position of those outside the ECCC (but whom that institution serves) the article engages with the normative assumptions of transitional justice praxis and broader thematic problems such as bridging local and global conceptions of justice.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.017 |
| Scholarly communication | 0.007 | 0.012 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".