Bibliographic record
Abstract
Although several studies have described the use of discourse markers (DMs) from a syntagmatic point of view, the possible reduplication of some DMs has never been studied in detail (ex. in French : bon bon, tiens tiens, voyons voyons, là là, bien bien and in English, OK OK, all right all right...). The present article has two aims. First, it seeks to analyze the role of the pragmatic reduplication (PR) of the là marker in Quebec French. It then aims to discover whether the PR of DMs is similar to the PR of other grammatical classes, such as that of adjectives, where the reduplication is generally considered to be an intensification process. The working hypothesis is that, if “intensification” is defined as a semantic category equivalent to “very X” or “really X”, the notion of “intensification” is not adequate to describe the PR of DMs. Intensification is only possible with words on a scale and DMs are not scalar. This being the case, it is proposed that the PR of DM is essentially related to the speaker’s commitment to his message and that the use of a reduplication device allows him to add an emphatic modal quality to the performance of an illocutionary act.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".