Tone, stress, quantity, and quality: prosodic patterns and tonal wug-tests in Žiri Slovenian
Bibliographic record
Abstract
In this paper, we report on the prosodic system of Žiri Slovenian, which displays an intricate set of interactions between tone, stress, quantity, and vowel quality. The prosodic restrictions are complex, exceeding the patterns observed in most other pitch-accented languages. Some of the patterns are well-motivated (e.g. the preference of High tone syllables to be stressed; the requirement for long vowels to have High tone) while others lack phonetic or phonological motivation (e.g. the requirement of long vowels to be footed). Žiri also displays a rare case of interaction of prosody with vowel quality: long [ɛɛ] must always be stressed and prefers the High tone on the second mora, which is not the case for any other vowel. To confirm the productivity of the observed patterns, we conduct a tonal wug experiment that tests the dependence of stress on vowel quality, word length, and tone. This paper brings forth a new instance of a phonetically unmotivated phonological process at the suprasegmental level, which appears to be less discussed than at the segmental level. We also discuss methodological issues arising from artificial experiments on tonal processes.
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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 | 0.002 |
| 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 | 0.000 |
| 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".