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Record W4285750747 · doi:10.4000/dse.4240

La littératie. Un espace conceptuel pour l’enseignement et l’éducation

2020· paratext· fr· W4285750747 on OpenAlexaff
Pascal Dupont, Olivier Dezutter

Bibliographic record

VenueLes dossiers des sciences de l éducation · 2020
Typeparatext
Languagefr
FieldSocial Sciences
TopicFrench Language Learning Methods
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsChemistry

Abstract

fetched live from OpenAlex

À un moment où de nombreux domaines affichent des préoccupations relatives à la littératie, il paraît utile de s’attacher à la constitution et à la réinterprétation de son espace conceptuel dans le champ de l’enseignement et de l’éducation. Plutôt que de se focaliser sur les différentes tentatives définitoires qui ont pu en être proposées, les contributions de ce volume tendent à explorer la plasticité de cet espace à partir de ses racines épistémologiques et scientifiques afin de le rendre plus opératoire pour les chercheurs et les praticiens. Il s’agit de voir en quoi il conduit à penser autrement le développement des activités langagières : le continuum de leurs apprentissages, leurs interactions, leurs usages dans différentes institutions sociales, leurs fonctionnalités pour l’individu et la société. Le tissage des points de vue des auteurs francophones, de différentes nationalités, permet d’envisager les apports potentiels de cet espace conceptuel et renouvelle le regard porté sur les questions d’enseignement et sur les interventions éducatives.

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)0.005
metaresearch head score (Gemma)0.010
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: Other
Teacher disagreement score0.018
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0030.007
Scholarly communication0.0100.008
Open science0.0010.004
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0180.004

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 head0.217
GPT teacher head0.448
Teacher spread0.231 · 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".

Quick stats

Citations1
Published2020
Admission routes1
Has abstractyes

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