Les émoticônes : de la signification des affects aux stratégies conversationnelles
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".