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Record W39177662 · doi:10.2196/52017

DES ENFANTS DU PRIMAIRE PARLENT DES LANGUES ET DE LA DIVERSITÉ LINGUISTIQUE

2006· article· en· W39177662 on OpenAlexvenueno aff
Érica Maraillet, Françoise Armand

Bibliographic record

VenueJMIR Serious Games · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicFrench Language Learning Methods
Canadian institutionsnot available
Fundersnot available
KeywordsLinguistic diversityContext (archaeology)Diversity (politics)SociologyImmigrationGlobalizationFrenchLinguisticsPolitical scienceHumanitiesHistoryArtAnthropologyPhilosophy

Abstract

fetched live from OpenAlex

In the midst of globalisation, and in the context of certain new ideas about the linguistic future of Quebec, Stefanescu and Georgeault’s recent book, Le francais au Quebec, les nouveaux defis, notes that linguistic diversity has recently attracted wide attention. Indeed, this book reveals the need to articulate the promotion and protection of the French language, with the recognition and valorisation of linguistic diversity on the international scene as well as in Quebec. In Montreal as elsewhere in Quebec, languages and linguistic diversity are being examined at all levels of the public sphere. This article attempts to shed some light on what children of immigrant origin, in the fifth and sixth grades of a multiethnic primary school, perceive regarding the debates around this topic. This study took place in the context of a language awareness project (ELODiL) oriented to fostering a thought provoking and trusting environment for pupils and researchers.

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)0.001
metaresearch head score (Gemma)0.005
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 score0.064
Threshold uncertainty score0.128

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.010
GPT teacher head0.341
Teacher spread0.331 · 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
Published2006
Admission routes1
Has abstractyes

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Same venueJMIR Serious GamesSame topicFrench Language Learning MethodsFrench-language works237,207