Bibliographic record
Abstract
This study describes declination and discourse-sized intonation contours in Nehiyawewin, an Algonquian language whose pitch and intonation systems have not been previously studied. The study draws on 270 min of recordings of two female Nehiyaw elders telling their life stories to another Nehiyawewin native speaker. Data is analyzed by using Praat’s default algorithm to generate f0 curves for each breath group. Preliminary results indicate: (1) When breath-group internal pitch peaks are considered, an obvious downward trend of f0 occurred in fewer than half the breath groups analyzed (about 40% or 37/90). This raises questions about the role of classical declination in natural discourse [Umeda, Journal of Phonetics 10 (1982)]. (2) When we abstract away from declination within a breath group by computing mean f0 and mean pitch peak for each breath group and tracking trends for these means, larger patterns seem to emerge; breath groups can be grouped into larger units based on raising and lowering trends. These units have a mean peak range of 150 Hz with a 30 Hz change from one breath group to the next and correspond to a domain of around five clauses (about 3–4 breath groups, about 45 syllables).
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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 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".