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Record W2586665595 · doi:10.7202/1038704ar

Quelle place pour la connaissance de soi dans la formation en travail social?

2017· article· fr· W2586665595 on OpenAlexvenueno aff
Marie Noëlle Beauchesne

Bibliographic record

VenueCanadian social work review · 2017
Typearticle
Languagefr
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceSociologyPhilosophy

Abstract

fetched live from OpenAlex

Le développement de compétences basées sur les meilleures connaissances scientifiques, l’efficacité de la pratique et l’adoption de standards éthiques ont guidé l’évolution des programmes de formation en travail social. Pour certains enseignants, la prégnance de plus en plus forte de la perspective scientifique a impacté significativement la formation, au détriment d’approches éducatives postmodernes, qui seraient plus cohérentes avec les valeurs fondatrices du travail social. Les enjeux inhérents à la profession influencent en effet les manières dont sont pensés, conçus et enseignés les cursus de formation. Certains enseignants misent sur des stratégies pédagogiques favorisant le développement de la connaissance de soi chez leurs étudiants, afin, notamment, de les préparer à une utilisation judicieuse de soi dans la pratique. Cet article s’intéresse à ces pratiques pédagogiques émergentes, orientées vers le développement de la connaissance de soi, et cherche à déterminer dans quelles perspectives pédagogiques elles sont ancrées. Pour y arriver, nous proposons une exploration des différentes conceptions philosophiques de l’éducation, parfois contradictoires, qui ont forgé la pédagogie du travail social, ainsi qu’un examen des principaux courants pédagogiques l’ayant influencée. Une réflexion est aussi amorcée autour des concepts de soi et d’utilisation de soi dans la formation en travail social.

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)0.010
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0110.060
Scholarly communication0.0150.014
Open science0.0010.010
Research integrity0.0040.008
Insufficient payload (model declined to judge)0.0090.001

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 head0.053
GPT teacher head0.369
Teacher spread0.316 · 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

Citations3
Published2017
Admission routes1
Has abstractyes

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