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Record W7114778104 · doi:10.7202/1121527ar

Les formes verbales surcomposées à valeur expérientielle en Suisse romande

2025· article· fr· W7114778104 on OpenAlexvenueno aff

Bibliographic record

VenueMinorités linguistiques et société · 2025
Typearticle
Languagefr
FieldSocial Sciences
TopicLinguistic and Sociocultural Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPopulationValue (mathematics)Statistical analysis

Abstract

fetched live from OpenAlex

Le français de Suisse romande présente de nombreuses particularités, qui concernent tous les niveaux de la langue. Parmi celles-ci figure un paradigme de temps verbaux surcomposés traditionnellement qualifiés de régionaux , qui se distinguent du type standard , à sens résultatif, à la fois sémantiquement et morphologiquement. Sur le plan sémantique, les surcomposés régionaux produisent un sens particulier que l’on appelle, depuis Zandvoort (1932), parfait d’expérience ( perfect of experience ). Sur le plan morphologique, ces temps verbaux se construisent par insertion du morphème eu dans le syntagme verbal composé (alors que les surcomposés standards se construisent par composition de l’auxiliaire). L’article discute le statut sociolinguistique des surcomposés expérientiels en Suisse romande. Il dément quelques idées reçues concernant l’âge et le statut socioprofessionnel des usagers de ces formes, et mentionne divers textes et anecdotes montrant la diversité des attitudes que la population romande peut avoir vis-à-vis de celles-ci.

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)0.002
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 score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.014
Scholarly communication0.0030.003
Open science0.0000.002
Research integrity0.0010.002
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 head0.036
GPT teacher head0.393
Teacher spread0.357 · 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
Published2025
Admission routes1
Has abstractyes

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