Low vowels and transparency in Kinande vowel harmony
Bibliographic record
Abstract
Transparency—in which a harmony effect passes over a segment without affecting it phonetically or phonologically—has been a controversial concept in previous literature on harmony systems. A typical case of so-called transparency involves cross-height vowel harmony in Kinande, a Bantu language (J.40). Previous accounts have analyzed low vowels in this system as being transparent to harmony [Schlindwein, NELS 17, 551–567 (1987)]. Further, some analysts have considered low vowels theoretically incapable of undergoing tongue root harmony. These claims were tested in a single-subject field study using ultrasound imaging to measure tongue root position in low vowels. Results indicate that (a) advanced versus retracted tongue root position (ATR) is a viable feature for describing the phonological distinction in the vowel system; (b) there is a phonetic difference between low vowels when adjacent to ATR triggering vowels; (c) this distinction in low vowels does not decrease with distance from trigger vowels, suggesting that these vowels are undergoing phonological harmony rather than phonetic assimilation; and finally, (d) the ATR distinction is phonetically categorical in high vowels, but shows crossover in mid and low vowels. Implications for phonological theory and phonetics-phonology interface will be discussed. [Work supported by NSERC and SSHRC.]
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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 | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".