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Record W2994736951 · doi:10.7202/1066524ar

La hiérarchisation des accents en français, entre représentations et réalité : étude de perception d’accents natifs et non natifs en Suisse romande

2019· article· fr· W2994736951 on OpenAlexvenueno aff
Marion Didelot

Bibliographic record

VenueMinorités linguistiques et société · 2019
Typearticle
Languagefr
FieldSocial Sciences
TopicLinguistic Variation and Morphology
Canadian institutionsnot available
FundersUniversité de PoitiersUniversité de NeuchâtelSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

La parole accentuée a toujours suscité des réactions plus ou moins vives. La mondialisation actuelle favorise les échanges intergroupes et multiplie les situations de communication exolingue, confrontant les auditeurs à une multitude d’accents, natifs ou non. Dans ce travail, nous présentons une étude de perception de différents accents natifs et non natifs en français menée auprès de trois groupes d’auditeurs francophones natifs qui devaient évaluer la convenance des locuteurs pour trois postes différents sur la base d’une écoute à l’aveugle d’extraits de parole spontanée. Nos résultats montrent une importante hiérarchisation des accents en français, qui n’oppose pas accent natif et accent non natif, mais qui semble indiquer qu’il existe une évaluation des accents en fonction de leur valeur sociale et des représentations auxquelles les auditeurs tendent à les associer.

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)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.662
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.023
GPT teacher head0.401
Teacher spread0.378 · 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

Citations41
Published2019
Admission routes1
Has abstractyes

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