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Record W2000617126 · doi:10.7202/1005796ar

La justice réparatrice et les crimes graves

2011· article· fr· W2000617126 on OpenAlexaffvenue
Tinneke Van Camp, Jo-Anne Wemmers

Bibliographic record

VenueCriminologie · 2011
Typearticle
Languagefr
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsUniversité de MontréalInternational Centre for Comparative Criminology
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Les besoins des victimes d’actes criminels violents sont multiples. Les victimes ont, entre autres, besoin de se sentir soutenues et reconnues en tant que victimes et de participer aux procédures judiciaires. Plusieurs études scientifiques révèlent que les interventions réparatrices ont la capacité de répondre à ces besoins. Bien que les victimes ne soient pas toujours intéressées par une telle approche, celles qui acceptent d’y participer sont effectivement satisfaites de l’offre réparatrice. On pourrait dépasser l’interrogation sur la pertinence d’offrir des mesures réparatrices aux victimes de crimes violents et plutôt se demander quel est le meilleur moment pour le faire. Dans cet article, nous comparons les expériences des victimes de crimes violents qui ont participé à une intervention réparatrice soit avant, soit après qu’une décision judiciaire a été prise. Nous voulions savoir notamment quel est l’impact d’une réponse judiciaire sur l’appréciation de l’approche réparatrice et si la disponibilité d’une décision judiciaire est une condition pour l’appréciation de l’approche bilatérale de la justice réparatrice. Cette étude illustre aussi comment les victimes situent l’approche réparatrice par rapport au système judiciaire.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.691
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

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.

Opus teacher head0.489
GPT teacher head0.430
Teacher spread0.059 · 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; both teacher heads agree on what is shown here.

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

Citations11
Published2011
Admission routes2
Has abstractyes

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