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Record W3021436531 · doi:10.1163/15718123-bja10004

Messages from the Expressive Nature of icc Reparations: Complex-victims in Complex Contexts and the Trust Fund for Victims

2020· article· en· W3021436531 on OpenAlexaff
Kirsten J. Fisher

Bibliographic record

VenueInternational Criminal Law Review · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Peace and Security Dynamics
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsRetributive justiceValue (mathematics)Criminal courtLawRestorative justiceEconomic JusticeHuman rightsPolitical scienceInternational lawInternational courtSociologyLaw and economicsPublic international lawComputer science

Abstract

fetched live from OpenAlex

There are great hopes for the International Criminal Court’s ( icc ’s) reparative aspirations, which are regarded as an answer to demands for more victim-centric approaches to the pursuit of justice for atrocity crimes. Reparations are recognised as a right of victims, and it seems appropriate that the icc should attempt to combine reparations with its retributive approach to addressing grave human right abuses. However, the potential negative communicative value of icc reparations must not be overlooked. For one, icc reparations have the potential to relieve some suffering but also the potential to exacerbate tensions and compound the challenges of reintegration and acceptance of complex-victims because of their expressive nature. This article argues that it is precisely because of the unique nature of the Court as retributive, as a voice of international condemnation, and as an intervener in complex contexts that the expressive value of its reparations may make it ill-suited to award reparations tied to convictions.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.963
Threshold uncertainty score0.495

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.084
GPT teacher head0.392
Teacher spread0.308 · 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 designTheoretical or conceptual
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

Citations6
Published2020
Admission routes1
Has abstractyes

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