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Record W4391301025 · doi:10.18192/olbij.v13i1.6619

L’enseignement de la variation phonétique du français au Cameroun : dérives et conséquences en termes d’insécurité linguistique chez les élèves

2024· article· fr· W4391301025 on OpenAlexvenueno aff
Gilbert Daouaga Samari

Bibliographic record

VenueOLBI Journal · 2024
Typearticle
Languagefr
FieldSocial Sciences
TopicLinguistic and Sociocultural Studies
Canadian institutionsnot available
Fundersnot available
KeywordsconsComputer science

Abstract

fetched live from OpenAlex

Conformément aux recommandations des États généraux de l’enseignement du français en Afrique subsaharienne francophone tenus en 2003, le Cameroun vient de décider d’enseigner la variation du français. L’objectif de cet article est de montrer que les pratiques didactiques actuellement en oeuvre pour transmettre la variation phonétique sont susceptibles d’installer des apprenants dans l’insécurité linguistique. En effet, au lieu de les initier à décrypter les accents de leur interlocuteur pour une meilleure communication, les pratiques analysées semblent plus focalisées sur l’identification de ces accents et leur description linguistique. Ces pratiques tendent davantage à transmettre aux élèves des stéréotypes teintés de jugement axiologique des locuteurs du français, ce qui pourrait entraîner des conséquences négatives sur la sécurité linguistique des apprenants. S’inscrivant dans la perspective didactique, cet article analyse, dans une approche qualitative, le manuel de langue française au second cycle au Cameroun et une leçon dispensée à l’attention des élèves de Terminale.

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)0.003
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.270
Threshold uncertainty score0.536

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0030.003
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.010
GPT teacher head0.306
Teacher spread0.297 · 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 designObservational
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

Citations1
Published2024
Admission routes1
Has abstractyes

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