Which discursive role to give to a fuzzy reference marker? Analysis of the pronoun "on" in a corpus of oral narratives
Bibliographic record
Abstract
Dans un corpus de dialogues narratifs, nous montrons que l’utilisation de « on » ne vise pas à définir une référence claire et précise, mais plutôt à partager un point de vue et à introduire des entités sur la scène verbale : « on » sert à rendre saillants les entités et les événements narrés tout en effaçant la source narrative, créant ainsi un flou référentiel dynamique et évolutif. Cette observation relativise la catégorisation habituelle de « on » comme « indéfini », et souligne plutôt son rôle essentiel dans la structuration de la narration dans un contexte de dialogue direct. Nos résultats révèlent ainsi la contribution de « on » à la cohérence et la cohésion du discours.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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 teacher head, 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".