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Record W2891389826

Out of the Shadows: A Comparative Assessment of the Role of Victims at the International Criminal Court and in Canada

2015· article· en· W2891389826 on OpenAlexaboutno aff
Benjamin Perrin

Bibliographic record

VenueeYLS (Yale Law School) · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Law and Human Rights
Canadian institutionsnot available
Fundersnot available
KeywordsAdversarial systemPolitical scienceCriminal courtJurisdictionLawCompensation (psychology)InstitutionCriminologyCriminal jurisdictionCriminal procedureInternational lawSociologyPsychologySocial psychology
DOInot available

Abstract

fetched live from OpenAlex

The International Criminal Court (ICC) has emerged as a unique institution for infusing victims in all phases of its proceedings. However, it has faced challenges in doing so and is still grappling with how to achieve meaningful participation and reparations for victims in a sustainable way. Comparative analysis can be valuable in addressing shared concerns, including the role of victims in criminal proceedings. This article provides the first comparative legal analysis of an adversarial common law jurisdiction (Canada) and the ICC with respect to the role of victims. It concludes that the ICC could enhance victim reparations by considering domestic models that provide victims with compensation much earlier in the process and re-focus victim participation in areas that do not overlap with the role of the prosecutor. Countries like Canada, which have been reticent to enhance victim participation, could consider some of the measures adopted for victims at the ICC.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.157
Threshold uncertainty score0.978

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0090.013
Science and technology studies0.0280.011
Scholarly communication0.0080.003
Open science0.0040.008
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.030
GPT teacher head0.306
Teacher spread0.276 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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
Published2015
Admission routes1
Has abstractyes

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