MétaCan
Menu
Back to cohort
Record W3040561312 · doi:10.7202/1070090ar

Étude comparative des programmes canadiens de mesures de rechange ou comment favoriser le désengorgement des tribunaux

2020· article· fr· W3040561312 on OpenAlexaffvenueabout
Julie Desrosiers, Catherine Rossi, Maude Cloutier, Vicky Brassard, Alexandre Béland-Ouellette

Bibliographic record

VenueRevue générale de droit · 2020
Typearticle
Languagefr
FieldSocial Sciences
TopicCriminal Law and Evidence
Canadian institutionsMinistère de l’Emploi et de la Solidarité Sociale (Québec)Université Laval
Fundersnot available
KeywordsHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

Les mesures de rechange permettent de répondre à la commission d’une infraction sans recourir au système de justice criminelle. Dès 1996, le législateur fédéral a autorisé les provinces à adopter des programmes de mesures de rechange, dans le but de réserver le recours au système judiciaire aux infractions sérieuses et de désengorger les tribunaux. Pourtant, certains des programmes mis en place sont très restrictifs et rendent difficile l’atteinte de cet objectif. La présente étude dresse un portrait rigoureux et systématique des programmes de mesures de rechange offerts dans les différentes provinces canadiennes et analyse leur capacité à réduire le volume du contentieux judiciaire. Le législateur fédéral a conféré une marge de manoeuvre importante aux provinces à cet égard. En comparant les conditions d’admissibilité à ces programmes au regard des infractions commises, des caractéristiques des contrevenants et des procédures utilisées, l’étude met en lumière la timidité du Programme de mesures de rechange général récemment instauré par le législateur québécois.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.729
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.120
GPT teacher head0.351
Teacher spread0.232 · 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.

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

Citations2
Published2020
Admission routes3
Has abstractyes

Explore more

Same venueRevue générale de droitSame topicCriminal Law and EvidenceFrench-language works237,207