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Record W2767772608 · doi:10.7202/1041704ar

Les femmes victimes de violence conjugale à la marge du système pénal : l’engagement 810 du Code criminel

2017· article· fr· W2767772608 on OpenAlexaffvenue
Adriana Bungardean, Jo-Anne Wemmers

Bibliographic record

VenueCriminologie · 2017
Typearticle
Languagefr
FieldSocial Sciences
TopicIntimate Partner and Family Violence
Canadian institutionsInternational Centre for Comparative CriminologyUniversité de Montréal
Fundersnot available
KeywordsHumanitiesPolitical sciencePoison controlArtMedical emergencyMedicine

Abstract

fetched live from OpenAlex

L’engagement 810 du Code criminel est une mesure couramment utilisée comme aboutissement du processus judiciaire dans les cas de violence conjugale. Au cours des dernières années, nous avons observé une augmentation du nombre d’engagements émis dans ces cas. À la fois mesure judiciaire et extrajudiciaire, le « 810 » est une mesure préventive et non punitive, ainsi elle n’occasionne pas de casier judiciaire pour le défendeur. Malgré son utilisation fréquente, peu d’études se sont penchées à savoir si l’engagement 810 est une mesure appréciée par les victimes et si on a répondu à leur besoin de sécurité. Nous examinons le contexte dans lequel l’engagement est appliqué pour les causes pénales en violence conjugale et les raisons que les femmes victimes évoquent pour avoir accepté ledit engagement. Nos résultats montrent que l’utilisation de l’engagement 810 dans les poursuites en violence conjugale contribue à maintenir les femmes victimes de violence conjugale à la marge de la justice.

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)0.002
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0010.001
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 head0.387
GPT teacher head0.429
Teacher spread0.042 · 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 designObservational
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
Published2017
Admission routes2
Has abstractyes

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