Bibliographic record
Abstract
Abstract This corpus‐based research examines a downstepped boundary tone in Persian spontaneous declaratives and yes/no questions (YNQs), by looking at 318 minutes of spontaneous phone conversations of 21 female and 21 male speakers in three age groups, 20s, 30s, and 40s. The downsteppedYNQs lack the final rise typically found in read utterances, which is associated with the non‐genuineness of the interrogative and a lowered degree of the hearer's commitment to provide a reply. The downstep in declaratives, accompanied by a following pause, creates functions such as topicalization and facilitates the cognitive pre‐planning of speech. There is no effect of sex and age on the production of this tone. The specific functions of this tone and its independence of adjacent tones argue for its inclusion in the grammar of Persian intonation. Additionally, this research is in itself a first‐time investigation of the intonation of Persian spontaneousYNQs and shows that the majority of them share the same intonation pattern with lab producedYNQs.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".