Du modalisateur au marqueur de ponctuation des actions : le cas de bon
Bibliographic record
Abstract
Bon, est un mot du discours qui reçoit des interprétations variées suivant le contexte conversationnel. Nous tentons de décrire les propriétés associées aux différents emplois de bon sur les plans syntagmatique, pragmatique et structurel du discours. L’analyse fait ressortir deux fonctions discursives principales : le modalisateur et le marqueur de structuration de la conversation (MSC) (Roulet & al., 1985). L’examen du fonctionnement de ce marqueur discursif révèle qu’il est possible de rassembler autour d’une même valeur sémantico-pragmatique l’ensemble de ces emplois : le marqueur de ponctuation oral qui scande et délimite les activités verbales et non verbales (cognitive, énonciative ou physique) des participants à la conversation.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.010 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".