Expanding research on ʔayʔajuθəm interrogative intonation
Bibliographic record
Abstract
Relatively little research has been done on ʔayʔaǰuθəm prosody. This lack of research is due in part to the idea that stress and tone are not distinctive features in the language. However, recent studies have found evidence of suprasegmental features in ʔayʔaǰuθəm interrogatives. Additionally, previous work indicates that—as has been reported with other Salishan languages—there is no significant rise in fundamental frequency at the end of ʔayʔaǰuθəm interrogatives, though the mean vowel fundamental frequency is higher in interrogative than in declarative sentences. These findings are not unique to ʔayʔaǰuθəm, but they do contribute to growing evidence that a final rise in fundamental frequency in interrogative sentences is not universal. In the present study, we aim to address the limitations of our previous work by expanding on the amount of data used, incorporating methods for analyzing the entire fundamental frequency contour, and measuring the mean fundamental frequency of vowels from more balanced stimuli. Although we do not expect different results from the present study, it is our hope that the methodologies used will increase the validity of our findings on ʔayʔaǰuθəm interrogative intonation.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.008 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".