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Record W4293141907 · doi:10.7202/1088306ar

La prise en compte des émotions en contexte de collaboration interprofessionnelle : perception de professionnels en travail social

2021· article· fr· W4293141907 on OpenAlexaffabout
Penelopia Iancu, Isabel Lanteigne, Hélène Albert, Elda Savoie

Bibliographic record

VenueIntervention · 2021
Typearticle
Languagefr
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsUniversité de Moncton
Fundersnot available
KeywordsPolitical scienceHumanitiesPsychologySociologyPhilosophy

Abstract

fetched live from OpenAlex

Dans cet article, nous présentons des résultats d’une recherche portant sur l’expérience de collaboration interprofessionnelle (IP) de travailleurs sociaux (TS) au Nouveau-Brunswick (N.-B.). Cette recherche qualitative se situe dans un paradigme interprétatif-compréhensif et cherche à saisir, entre autres, la prise en compte des émotions lors de la collaboration IP. Les participantes sont des travailleuses sociales (n=21) oeuvrant dans plusieurs milieux de pratique. La collecte des données a été réalisée par le biais d’entrevues semi-dirigées et de notes de terrain. Les résultats présentés portent sur des thèmes émergeant de cette étude, soit les émotions ressenties par les TS en contexte d’intervention collaborative (liées aux situations de personnes accompagnées, au processus d’intervention et à l’expérience collaborative), ainsi que sur des stratégies mises en place pour gérer ces émotions. En conclusion, nous présentons quelques pistes de réflexion portant notamment sur la prise en compte des émotions en intervention collaborative et la formation de futurs professionnels à la collaboration IP.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.219
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0140.001

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 head0.025
GPT teacher head0.425
Teacher spread0.400 · 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; both teacher heads agree on what is shown here.

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
Published2021
Admission routes2
Has abstractyes

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