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Record W4390033783 · doi:10.7202/1108159ar

Les francophones canadiens gesticulent‑ils fréquemment ?

2023· article· fr· W4390033783 on OpenAlexaffvenueabout
Elena Nicoladis, Nicol G. Garzon

Bibliographic record

VenueFrancophonies d Amérique · 2023
Typearticle
Languagefr
FieldPsychology
TopicHearing Impairment and Communication
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPolitical science

Abstract

fetched live from OpenAlex

Selon les stéréotypes, les francophones font plus de gestes en parlant que les anglophones. L’objectif principal de cette étude est de vérifier cette hypothèse en comparant la fréquence des gestes entre des francophones et des anglophones monolingues au Canada. Le second objectif est lié au bilinguisme : la majorité des francophones au Canada parlent aussi anglais. Comme des études ont montré que les locuteurs bilingues font plus de gestes que les locuteurs monolingues, l’objectif secondaire de la recherche est donc de comparer la fréquence des gestes entre des personnes monolingues et des personnes bilingues (français et anglais). Les participantes et les participants ont visionné un dessin animé dont ils devaient ensuite narrer l’histoire. Les gestes qu’ils ont produits en racontant l’histoire ont été codés (tant les gestes représentatifs que les bâtons , soit des gestes répétitifs qui mettent l’accent sur l’importance du langage parlé). Aucune différence importante entre les deux groupes monolingues n’a été notée. Cependant, les personnes bilingues avaient tendance à effectuer plus de gestes que les personnes monolingues, et ce, dans les deux langues. Ces résultats renforcent quelque peu le stéréotype selon lequel les francophones, en particulier les personnes bilingues, gesticulent beaucoup.

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)0.001
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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.187
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.027

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 head0.044
GPT teacher head0.330
Teacher spread0.286 · 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; both teacher heads agree on what is shown here.

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

Citations2
Published2023
Admission routes3
Has abstractyes

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