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Record W2151547430 · doi:10.7202/1016885ar

Éduquer l’enfant à la mort en utilisant des ouvrages pédagogiques

2013· article· fr· W2151547430 on OpenAlexvenueno aff
Marie-Ange Abras

Bibliographic record

VenueNouveaux cahiers de la recherche en éducation · 2013
Typearticle
Languagefr
FieldPsychology
TopicGrief, Bereavement, and Mental Health
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPhilosophyArtPolitical science

Abstract

fetched live from OpenAlex

La mort est invoquée à l’occasion de divers enseignements. Nombre de livres existent pour que l’enfant puisse en parler. Elle ne fait pas pour autant l’objet d’une réflexion. L’enfant aurait besoin d’un accompagnement pour lire avec profit ces ouvrages, besoin aussi d’être écouté, guidé et stimulé dans le questionnement qui est le sien à propos de la mort. En accord avec les professionnels de l’éducation, nous avons pu mettre en place des groupes d’enfants âgés de 6 à 12 ans. La méthode de la recherche-formation existentielle a été utilisée pour aborder de front cette question devenue « taboue » dans notre société et permettre aux enfants de s’exprimer. Cet article, après avoir établi l’état de la question, présente cette méthode et en montre l’intérêt pédagogique.

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)0.008
metaresearch head score (Gemma)0.017
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 score0.015
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.017
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0060.007
Scholarly communication0.0050.005
Open science0.0010.007
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0150.004

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 head0.124
GPT teacher head0.469
Teacher spread0.346 · 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
Published2013
Admission routes1
Has abstractyes

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