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Record W2554423785 · doi:10.17118/11143/9703

Étudiants et apprenants de catalan en Catalogne du nord: écho du conflit diglossique espagnol

2016· article· fr· W2554423785 on OpenAlexvenueno aff
Thierry Tréfault

Bibliographic record

VenueCircula · 2016
Typearticle
Languagefr
FieldArts and Humanities
TopicSpanish Linguistics and Language Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCatalanHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

Dans le département des Pyrénées orientales, nombreux sont ceux qui apprennent le catalan, langue régionale aux côtés du français.Cet espace géographique plurilingue se rattache à l'entité plus vaste de la Catalogne, berceau de conflits diglossique virulents, au cœur de revendications d'autonomie qui secouent le climat politique actuel en Espagne.Cet article rend compte d'une enquête réalisée dans le cadre du projet « Représentations des langues et des identités en Méditerranée en contexte plurilingue » (EA 739 Dipralang).Il s'agit de mettre en évidence les représentations du catalan et du français chez les apprenants de catalan, qu'ils soient locuteurs natifs, étudiants à l'université, dans les filières spécifiques ou comme option, ou encore qu'ils se destinent à l'enseigner dans les classes bilingues.Nous faisons l'hypothèse que ces représentations diffèrent en fonction de l'implication dans la diglossie français-catalan et qu'elles sont un écho au conflit linguistique propre à la Catalogne.Pour la vérifier, nous utilisons la méthode d'analyse combinée mise au point par Bruno Maurer.

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)0.003
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 score0.504
Threshold uncertainty score0.998

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0080.005
Scholarly communication0.0070.002
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.013
GPT teacher head0.240
Teacher spread0.227 · 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

Citations1
Published2016
Admission routes1
Has abstractyes

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