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Record W4407794689 · doi:10.1093/pch/pxae086

L’alphabétisation chez les enfants d’âge scolaire : une approche pédiatrique des prises de position et de l’évaluation

2024· article· fr· W4407794689 on OpenAlexaffabout
Anne Kawamura, Angela Orsino, Scott McLeod, Mark Handley‐Derry, Linda S. Siegel, Jocelyn Vine, Nicola Jones-Stokreef

Bibliographic record

VenuePaediatrics & Child Health · 2024
Typearticle
Languagefr
FieldMedicine
TopicChild Nutrition and Feeding Issues
Canadian institutionsCanadian Paediatric Society
Fundersnot available
KeywordsPolitical scienceHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

Résumé L’alphabétisation est un important déterminant social de la santé qui influe sur la vie socioaffective quotidienne des enfants et sur leurs perspectives économiques plus tard dans la vie. Il est essentiel de pouvoir lire, écrire et comprendre le texte écrit pour participer à la société, atteindre ses objectifs, acquérir des connaissances et réaliser son potentiel. Pourtant, une forte proportion d’adultes du Canada ne possède pas les compétences nécessaires en alphabétisation pour satisfaire aux exigences de plus en plus complexes du milieu du travail et les gérer. Les professionnels de la santé qui s’occupent d’enfants jouent un rôle essentiel pour détecter les enfants et les familles à risque de faible alphabétisation. Le présent document de principes propose des approches pour évaluer les enfants et conseiller les familles afin qu’elles améliorent leurs compétences en lecture, tout en préconisant leur droit à l’enseignement de la lecture fondé sur des données probantes.

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)0.035
metaresearch head score (Gemma)0.067
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.060
Threshold uncertainty score0.184

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0350.067
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.003
Science and technology studies0.0030.002
Scholarly communication0.0060.003
Open science0.0020.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0060.001

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 head0.029
GPT teacher head0.338
Teacher spread0.309 · 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 designNot applicable
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
Published2024
Admission routes2
Has abstractyes

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