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Record W2808151667

Impuissance et contre-transfert culturel

2018· article· fr· W2808151667 on OpenAlexaboutno aff
Marie-Laure Daxhelet, Janique Johnson‐Lafleur, Garine Papazian-Zohrabian, Cécile Rousseau

Bibliographic record

VenueL Autre · 2018
Typearticle
Languagefr
FieldSocial Sciences
TopicEducation, sociology, and vocational training
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophySociology
DOInot available

Abstract

fetched live from OpenAlex

Le contre-transfert culturel est un concept qui souligne la dimension socioculturelle, et donc collective, du contre-transfert. Dans ce texte, nous analysons, au moyen de cinq histoires cliniques presentees dans le cadre de seminaires de discussion de cas transculturels et interinstitutionnels menes a Montreal, Canada, les diverses formes que peut prendre le contre-transfert culturel pour des cliniciens en situation d’impasse therapeutique face a la prise en charge de familles migrantes. Nous examinons ensuite le role eventuel de ces seminaires dans la transformation de ce contre-transfert et dans la formulation de pistes permettant de relancer ou de soutenir le processus therapeutique. Les resultats indiquent que les seminaires transculturels et interinstitutionnels de discussion de cas facilitent un travail d’elaboration sur les representations collectives des cliniciens et que ce travail groupal permet de contenir et parfois de depasser certaines situations d’echec therapeutique.

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)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.214
Threshold uncertainty score0.425

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0150.054
Scholarly communication0.0110.006
Open science0.0020.008
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0060.000

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 head0.152
GPT teacher head0.467
Teacher spread0.315 · 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 designNot applicable
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
Published2018
Admission routes1
Has abstractyes

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