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Record W2118561003 · doi:10.7202/1031475ar

Quelles prises de responsabilités ? Recherche comparative entre élèves scolarisés à l’hôpital et élèves scolarisés hors contexte hospitalier

2015· article· fr· W2118561003 on OpenAlexvenueno aff
Séverine Colinet

Bibliographic record

VenueRevue des sciences de l éducation · 2015
Typearticle
Languagefr
FieldHealth Professions
TopicHealth, Medicine and Society
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Cette recherche a pour objectif de comprendre comment les prises de responsabilité s’exercent chez les élèves scolarisés dans le contexte de l’école à l’hôpital et chez ceux qui sont scolarisés à l’école. Afin de concourir à la mise en oeuvre d’une normalisation de la scolarité à l’hôpital, les prises de responsabilité doivent se décentrer du soin et s’inscrire en continuum sur l’ensemble des activités scolaires et non scolaires, au sein ou hors du contexte hospitalier. Notre enquête qualitative s’est fondée sur des entretiens exploratoires, des observations, des entretiens semi-directifs auprès d’élèves hospitalisés et non hospitalisés, d’enseignants et des parents. Un mini-journal a été rédigé par les élèves. Les résultats portent sur une analyse des formes de responsabilités qui ont été dégagées des types de perceptions issus des discours. Il existe différentes formes de prises de responsabilité, plus ou moins en adéquation avec le cadre législatif prônant l’éducation à la responsabilité.

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)0.007
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0060.006
Scholarly communication0.0070.004
Open science0.0010.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0110.001

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 head0.712
GPT teacher head0.571
Teacher spread0.141 · 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 designObservational
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

Citations0
Published2015
Admission routes1
Has abstractyes

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