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Record W3042630323 · doi:10.7202/1069983ar

ALLIANCE THÉRAPEUTIQUE ET SERVICES DE PROTECTION DE LA JEUNESSE : POINTS DE VUE ET EXPÉRIENCES DE JEUNES ISSUS DE MINORITÉS ETHNOCULTURELLES ET DE LEURS INTERVENANTS

2020· article· fr· W3042630323 on OpenAlexvenueaboutno aff
Gary Saint-Jean, Sarah Dufour

Bibliographic record

VenueCanadian social work review · 2020
Typearticle
Languagefr
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesAlliancePolitical scienceArt

Abstract

fetched live from OpenAlex

La surreprésentation de certains groupes de jeunes de minorités ethnoculturelles (MEC) dans le système de protection de la jeunesse est bien documentée au Québec. Parmi les solutions relevées pour y pallier, la relation intervenant-receveur de services a été identifiée comme un des meilleurs moteurs de changement. La présente étude qualitative phénoménologique vise à (1) comprendre davantage l’influence perçue de l’appartenance ethnoculturelle sur l’établissement de l’alliance thérapeutique entre des jeunes de MEC et leurs intervenants en protection; et (2) à comprendre, dans une perspective dyadique, les ressemblances, les différences, les points d’entente et les points de désaccord dans la dyade jeune-intervenant. Quinze jeunes de MEC âgés entre 12 et 17 ans et leurs treize intervenants ont été rencontrés lors d’entrevues semi-structurées. Les résultats permettent d’identifier des facteurs qui viennent influencer des paramètres de l’alliance de manière plus précise, notamment le lien affectif et l’accord sur les buts et les moyens. Ces influences semblent toutefois dépendre de l’importance relative du paramètre culturel dans la relation, mettant en lumière l’importance de l’évaluation préalable de cette dimension. Les implications pour la pratique clinique, la formation et la recherche sont discutées.

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)0.005
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.244
Threshold uncertainty score0.485

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0160.012
Scholarly communication0.0050.003
Open science0.0010.006
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.111
GPT teacher head0.436
Teacher spread0.324 · 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 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

Citations0
Published2020
Admission routes2
Has abstractyes

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