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Record W2930956435

Pourquoi les enseignants de français ne se parlent pas le français entre eux? Une question d’identité ou maitrise du français?

2019· article· fr· W2930956435 on OpenAlexaff
Monica Tang

Bibliographic record

Venue2019 Conference of the Canadian Society for the Study of Education · 2019
Typearticle
Languagefr
FieldSocial Sciences
TopicFrench Language Learning Methods
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsHumanitiesPolitical scienceFrenchArt
DOInot available

Abstract

fetched live from OpenAlex

Quand j’ai commence a travailler en formation continue, j’ai remarque que des enseignants du francais inscrits dans un programme donne en francais ne se parlaient pas toujours entre eux en francais. Si des professionnels competents, interesses par leur propre developpement continu, devoues a l’enseignement du francais ne reussisaient pas a se parler en francais, y a-t-il la un probleme qu’on n’a pas saisi? Apres tout, ce ne sont pas de jeunes adolescents mis dans le programme d’immersion par leurs parents sans leur consentement. Qu’arrivera-t-il au programme d’immersion si les enseignants ne sont pas passionnes de leur metier? Ma recherche s’est attardee a mieux comprendre, initialement, cette absence du francais en milieu professionnel. Plus tard, ma question de recherche a change quand j’ai compris que des dynamiques de pouvoir existaient qui pouvaient rendre le choix de langue une decision plus complexe qu’elle en a l’air. C’est en egalisant les ecarts de pouvoir que j’ai compris comment l’identite linguistique et donc, professionnelle, peut affecter l’usage et le desir de prendre des risques en francais. Ces decouvertes auront des repercussions importantes pour nos jeunes et futurs enseignants bilingues.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.250
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.032
GPT teacher head0.296
Teacher spread0.264 · 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 teacher head, not a consensus.

Study designQualitative
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
Published2019
Admission routes1
Has abstractyes

Explore more

Same venue2019 Conference of the Canadian Society for the Study of EducationSame topicFrench Language Learning MethodsFrench-language works237,207