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Record W2469882448 · doi:10.7146/torture.v25i2.109667

Elusive retributive justice in post-Khmer Rouge Cambodia: Challenges of using ECCC Victim Information Forms as a victim participatory rights mechanism

2018· article· en· W2469882448 on OpenAlexfundno aff
Leakhena Nou

Bibliographic record

VenueTorture Journal · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicCambodian History and Society
Canadian institutionsnot available
FundersEnvironment and Climate Change Canada
KeywordsTortureTribunalEconomic JusticeCitizen journalismRetributive justiceCriminologySociologyRelocationHuman rightsLawPolitical science

Abstract

fetched live from OpenAlex

This paper focuses on the procedural challenges of using the Victim Information Forms (VIFs) to analyze survivors' experiences with the Extraordinary Chambers in the Courts of Cambodia (ECCC), commonly known as the Khmer Rouge Tribunal. The paper takes a systematic public/medical sociology approach to examining the VIF as a participatory rights mechanism for victims wishing to pursue justice for themselves and their loved ones who experienced the Khmer Rouge atrocities, torture, forced relocation, starvation, forced labor, rape, robbery, and other physical and psychological torment, firsthand. It provides the first comparative, critical analysis of both the original VIF and the revised form issued midway through the submission period; both forms appear as appendices to the paper. Conclusions are drawn and suggestions made by the researcher based on the firsthand collection and submission of the largest group of VIFs from any single source around the world (outside of Cambodia itself), as well as on support work with victims/survivors during the ECCC proceedings in Phnom Penh, Cambodia in 2013.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.257
Threshold uncertainty score0.865

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.032
GPT teacher head0.325
Teacher spread0.292 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2018
Admission routes1
Has abstractyes

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