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Record W2952358446 · doi:10.3917/vsoc.191.0193

L’apport du savoir expérientiel des personnes usagères des services sociaux au sein de la formation en travail social

2019· article· fr· W2952358446 on OpenAlexaffabout
Paul Morin, Annie Lambert

Bibliographic record

VenueVie sociale · 2019
Typearticle
Languagefr
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-MontréalHealth and Social Services Centre University Institute of Geriatrics of Sherbrooke
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Ce texte a pour objectif de démontrer la pertinence du savoir expérientiel des usagers dans le cadre de la formation académique des futurs travailleurs sociaux en regard de la mise en œuvre de l’alliance avec la personne accompagnée. L’intégration des usagers dans la formation permet de réduire la distance sociale tout en réfléchissant aux inégalités structurelles. Ce texte s’appuie sur le modèle suédois du « gap mending » en travail social de l’université de Lund. Les auteurs présentent plus particulièrement les aspects clés de la dimension relationnelle ciblés par des usagers lors d’une recherche norvégienne inspirée par l’approche anti-oppressive, tout en la reliant à la recension des écrits sur l’apport du savoir expérientiel dans le cadre de travaux menés à l’école de travail social de l’université de Sherbrooke et visant la participation des usagers dans la formation.

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)0.004
metaresearch head score (Gemma)0.010
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 score0.013
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0040.005
Scholarly communication0.0060.004
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0130.001

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 head0.051
GPT teacher head0.348
Teacher spread0.298 · 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

Citations2
Published2019
Admission routes2
Has abstractyes

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