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Record W3033536419 · doi:10.4000/communiquer.5921

Les émoticônes : de la signification des affects aux stratégies conversationnelles

2020· article· fr· W3033536419 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.

venuePublished in a venue whose home country is Canada.
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

VenueCommuniquer Revue de communication sociale et publique · 2020
Typearticle
Languagefr
FieldComputer Science
TopicDigital Communication and Language
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

Les émoticônes sont des pictogrammes qui indiquent les affects du locuteur. Notre hypothèse est que cette caractéristique fait des émoticônes un outil privilégié pour organiser certaines stratégies conversationnelles (accord, désaccord, explicitation…). Cet article montre d’abord que les émoticônes, parce qu’elles sont avant tout des indices d’affect, sont un support de calcul de la modalité. Ainsi, certaines caractéristiques sémiotiques des émoticônes font qu’elles permettent de comprendre comment se positionne le locuteur par rapport à ce qu’il dit. Cela permet de lier les émoticônes à une prise en charge énonciative modulable : le degré de responsabilité que le locuteur engage, vis-à-vis de ce qu’il dit, et son interprétation par l’interlocuteur varient selon l’émoticône employée. Cet article montre enfin comment cette modulation de la prise en charge permet de mettre en place de véritables stratégies conversationnelles destinées à orienter et à cadrer les échanges.

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)0.004
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.896
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0030.003
Open science0.0050.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.090
GPT teacher head0.338
Teacher spread0.247 · 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