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Record W2212156694

Récits oraux, interventions dialogiques et leur lien avec les compétences en lecture et écriture chez l'enfant français de 5 à 8 ans.

2011· article· fr· W2212156694 on OpenAlexaff
Hélène Makdissi, Edy Veneziano, Laetitia Albert, Marie Baron, Andrée Boisclair, Chantal Caracci-Simon, Juliette Elie-Deschamps, Emilie Hébert, Christian Hudelot, Marie‐Thérèse Le Normand, Marie‐Hélène Plumet, Serge Poncin, Nathalie Salagnac, Pauline Sirois

Bibliographic record

VenueHAL (Le Centre pour la Communication Scientifique Directe) · 2011
Typearticle
Languagefr
FieldSocial Sciences
TopicFrench Language Learning Methods
Canadian institutionsCanadian Linguistic AssociationUniversité Laval
Fundersnot available
KeywordsHumanitiesPsychologyArt
DOInot available

Abstract

fetched live from OpenAlex

Previous studies have shown that children produce more coherently structured and mind-oriented narratives after participating in conversations that solicit children's attention on the reasons of the story events. We believe that promoting narrative skills is not only an important achievement in itself but also a useful approach for improving children's reading comprehension. This study presents the progression of children's oral narratives in the construction of a story based on pictures and in the recall of a story read by the experimenter, and how such a progression relates to measures of emergent reading and writing skills and to two theory of mind tasks. To this effect, 100 children between 5 and 8 years (25 per age group) participated in the different phases of the study. Preliminary results confirm that the dialogical procedure promotes in some children more structured and evaluative narratives, a progression that correlates with children's emergent reading and writing skills.

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)0.002
metaresearch head score (Gemma)0.007
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 score0.069
Threshold uncertainty score0.137

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.034
GPT teacher head0.302
Teacher spread0.268 · 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
Published2011
Admission routes1
Has abstractyes

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