Intonation and Particles as Speech Act Modifiers: A Syntactic Analysis
Bibliographic record
Abstract
Abstract This study investigates how discourse particles and intonation contribute to the modification of speech act. In particular, it focuses on the interplay between the speaker’s and the addressee’s commitment toward the proposition in assertions, biased questions, and requests for confirmation. A syntactic analysis is proposed, in which speaker commitment and call on addressee are represented as two functional projections of the speech act structure. Data from nontonal (Canadian English) and tonal languages (Cantonese and Medumba) are analyzed for cross-linguistic comparison. In Canadian English, the particle “ eh ” and rising intonation are associated with speaker commitment and call on addressee, respectively. In Cantonese, a single particle associates with these. In Medumba, the two positions are occupied by two distinct particles. This neo-performative approach toward speech act structure differs from Ross’s 1970 original insight by positing a high functional layer called grounding , rather than a higher matrix clause of the familiar type.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".