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Record W4206434940 · doi:10.7202/1084065ar

Entre épreuve et enquête : recherches narratives à partir des microrécits d’enfants en milieu hospitalier au Brésil

2021· article· fr· W4206434940 on OpenAlexvenueno aff
Hervé Breton, Maria da Conceição Passeggi

Bibliographic record

VenueRecherches qualitatives · 2021
Typearticle
Languagefr
FieldSocial Sciences
TopicQualitative research in health
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPhilosophyArt

Abstract

fetched live from OpenAlex

La recherche qualitative en sciences de l’éducation, dans la pluralité de ses approches théoriques et méthodologiques, met l’accent sur la manière dont les agents sociaux pensent, perçoivent et ressentent les phénomènes qu’ils éprouvent. À la croisée des approches quantitatives et compréhensives, l’enquête narrative mobilise le récit pour appréhender par le langage l’expérience vécue. Les données qui en résultent ont la particularité d’être temporalisées, processuelles et expérientielles. L’accomplissement du récit est cependant régi par un champ de contraintes qui le constitue en épreuve : mise en mots de l’expérience, temporalisation et configuration du récit, format narratif qui s’impose lors de l’expression. L’enjeu de cet article est de spécifier les dimensions de l’épreuve pour le sujet qui porte son vécu au langage et le configure en récit, puis d’en montrer concrètement les effets à partir d’une des formes possibles de cette approche de l’enquête, celle des micro-récits d’enfants recueillis en milieu hospitalier au Brésil.

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)0.011
metaresearch head score (Gemma)0.022
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 score0.055
Threshold uncertainty score0.109

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.022
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0140.018
Scholarly communication0.0120.008
Open science0.0020.010
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0090.001

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 head0.391
GPT teacher head0.528
Teacher spread0.137 · 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

Citations4
Published2021
Admission routes1
Has abstractyes

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