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Record W2078887650 · doi:10.7202/017948ar

Les besoins d’apprentissage des bénévoles en contexte de soins palliatifs pédiatriques

2008· article· fr· W2078887650 on OpenAlexaffvenue
Manon Champagne

Bibliographic record

VenueFrontières · 2008
Typearticle
Languagefr
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsMinistère de l’Emploi et de la Solidarité Sociale (Québec)Université du Québec à Montréal
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

Le but de la recherche-action dont les résultats sont ici partiellement rapportés consistait à améliorer la formation de bénévoles s’apprêtant à oeuvrer dans un programme de répit à domicile offert à des familles d’enfants atteints d’une maladie à issue fatale. Elle visait notamment à mieux connaître les besoins de formation de ces bénévoles et à cerner les principales composantes d’un programme de formation initiale leur étant destiné. Cet article présente une synthèse des besoins d’apprentissage qui ont été déterminés avec la participation de parents, de bénévoles, de formatrices et d’employées, à l’aide de diverses méthodes de collecte de données. Cette synthèse comprend 27 grands thèmes présentés sous neuf rubriques. En outre, l’auteure discute brièvement ce qui, relativement aux besoins d’apprentissage des bénévoles, caractérise le bénévolat en contexte de soins palliatifs pédiatriques par rapport au bénévolat effectué auprès d’adultes en fin de vie.

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)0.024
metaresearch head score (Gemma)0.041
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 score0.024
Threshold uncertainty score0.127

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.041
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0040.005
Scholarly communication0.0060.005
Open science0.0010.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.039
GPT teacher head0.316
Teacher spread0.277 · 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

Citations1
Published2008
Admission routes2
Has abstractyes

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