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Record W7163530504 · doi:10.3406/verbu.2025.2045

Locutions verbales usuelles examinées par des natifs de France et du Canada : uniformité et variation

2025· article· fr· W7163530504 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueVerbum · 2025
Typearticle
Languagefr
FieldPsychology
TopicCategorization, perception, and language
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)LimitingValue (mathematics)

Abstract

fetched live from OpenAlex

En nous basant sur des études psycholinguistiques consacrées aux locutions et en menant des recherches de fréquence dans Eureka.cc, nous avons choisi 34 locutions «très connues» des locuteurs français. Afin de vérifier dans quelle mesure des locuteurs natifs provenant de France et du Canada partagent les mêmes connaissances phraséologiques, nous avons proposé un test à choix multiples sur les locutions aux deux groupes, France et Canada (n=33). Les participants ont aussi noté les scores sur leurs perceptions de la connaissance, familiarité et usage des locutions et proposé des expressions qui, selon eux, étaient régionales. La connaissance de la plupart des locutions est «partagée» par les deux communautés, ce qui confirme l’uniformité des connaissances phraséologiques des natifs par rapport aux items choisis, alors qu’un petit nombre de locutions démontre une variation diatopique significative. La portée de ces résultats pour la phraséodidactique est discutée.

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.

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)0.000
metaresearch head score (Gemma)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.654
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.008
GPT teacher head0.278
Teacher spread0.270 · 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