MétaCan
Menu
Back to cohort
Record W2884221379 · doi:10.1515/ijld-2018-2005

The stories we tell victims: Victim participation and outreach programs at the extraordinary chambers in the courts of Cambodia

2018· article· en· W2884221379 on OpenAlexfundno aff
Tine Destrooper

Bibliographic record

VenueInternational Journal of Legal Discourse · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicCambodian History and Society
Canadian institutionsnot available
FundersEnvironment and Climate Change Canada
KeywordsOutreachEconomic JusticePrioritizationPublic relationsBridging (networking)Political scienceRestorative justiceWork (physics)Relevance (law)NarrativeSociologyCriminologyLawBusinessEngineeringComputer security

Abstract

fetched live from OpenAlex

Abstract Victim participation and elaborate outreach programs are becoming increasingly important features of international and hybrid criminal courts. The aspiration is that these programs will increase the local relevance of these courts' work, enhance the sustainability of justice processes after international actors leave, and empower victims en passant. In the last decade, considerable attention and resources have been dedicated to the development of state-of-the-art outreach and participation programs, resulting in exciting new engagement models that are then, on average, evaluated in legal and technical terms. So far, however, little attention has been paid to the more long-term and indirect effects of exposure to certain – unidimensional and hierarchically organized – narratives about justice. In a first step to systematically analyze this question, this article maps the discursive priorities and structure of one of the tribunals (Cambodia) where victim participation and outreach played a central role. The article uses innovative large-n qualitative computational text analysis methods and raises critical questions about (a) the disconnect between prosecutorial prioritization strategies and popular priorities for the justice process, (b) the success of outreach programs in bringing a locally relevant message, and (c) the extent to which outreach and victim participation succeeded in bridging the gap between the work of the ECCC and the realities of people on the ground.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.697
Threshold uncertainty score0.734

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 studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.025
GPT teacher head0.368
Teacher spread0.343 · 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

Citations3
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Legal DiscourseSame topicCambodian History and SocietyFrench-language works237,207