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Record W3029960608

L’enseignement et l’apprentissage de la lecture aux différents niveaux de la scolarité

2017· preprint· fr· W3029960608 on OpenAlexaboutno aff
Magali Brunel, Judith Émery-­Bruneau, Jean‐Louis Dufays, Olivier Dezutter, Érick Falardeau

Bibliographic record

VenueHAL (Le Centre pour la Communication Scientifique Directe) · 2017
Typepreprint
Languagefr
FieldSocial Sciences
TopicFrench Language Learning Methods
Canadian institutionsnot available
Fundersnot available
KeywordsPhilosophyPolitical science
DOInot available

Abstract

fetched live from OpenAlex

Cet ouvrage rassemble des travaux empiriques récents menés dans les différents pays francophones à propos des pratiques d’enseignement, des capacités et des difficultés des élèves et des étudiants en lecture, du primaire à l’université, en associant différentes dimensions. Il présente une dimension curriculaire dans sa structure même, puisqu’il envisage toute la scolarité obligatoire, du primaire jusqu’au lycée/Cégep/Secondaire II, au sein même de plusieurs articles. Il offre également une vision de l’enseignement de la lecture qui ne se limite pas à la lecture littéraire, mais s’étend aussi à celle des textes informatifs puisqu’au-delà de leurs spécificités, l’une et l’autre sollicitent des processus de compréhension et des composantes communs. Le livre propose enfin des comparaisons internationales entre les quatre pays francophones qui ont intégré l’approche par compétences à leurs curriculums : la Belgique, la France, le Québec et la Suisse.

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)0.017
metaresearch head score (Gemma)0.030
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: Other · Consensus signal: none
Teacher disagreement score0.119
Threshold uncertainty score0.237

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.030
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
Science and technology studies0.0060.005
Scholarly communication0.0120.005
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0200.003

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 head0.019
GPT teacher head0.311
Teacher spread0.292 · 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
GenreOther

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".

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Citations0
Published2017
Admission routes1
Has abstractyes

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