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Record W2010001830 · doi:10.7202/1024013ar

Victimisation : réalité préoccupante pour les jeunes pris en charge par la DPJ

2014· article· fr· W2010001830 on OpenAlexaffvenueabout
Katie Cyr, Claire Chamberland, Marie‐Ève Clément, Geneviève Lessard

Bibliographic record

VenueCriminologie · 2014
Typearticle
Languagefr
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsUniversité LavalUniversité du Québec en OutaouaisUniversité de Montréal
Fundersnot available
KeywordsVictimisationHumanitiesPolitical sciencePoison controlPsychologySuicide preventionMedicineArtMedical emergency

Abstract

fetched live from OpenAlex

Cet article compare la violence annuellement vécue par un échantillon de jeunes (2 à 17 ans) Québécois pris en charge par la Direction de la protection de la jeunesse (DPJ) et celle subie par les jeunes de la population générale. Les résultats démontrent que les jeunes pris en charge vivent significativement plus de violence et qu’une grande partie d’entre eux font face à de la violence chronique dans plusieurs sphères de leur vie. Les trajectoires susceptibles d’expliquer leur risque accru de victimisation et les implications pour l’intervention sont discutées. Les besoins multiples de ces jeunes soulignent l’importance de développer une vision plus holistique de leur vécu de victimisation et de leurs problèmes. Une plus grande collaboration des divers intervenants et organismes impliqués auprès des jeunes est susceptible de favoriser une approche moins fragmentée et une intervention mieux adaptée.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.226
Threshold uncertainty score0.449

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.002
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.002
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 head0.212
GPT teacher head0.377
Teacher spread0.166 · 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

Citations6
Published2014
Admission routes3
Has abstractyes

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