Bibliographic record
Abstract
This article contributes to the understanding of gradient phonological patterns by investigating graded vowel co-occurrence in Oceanic languages. In particular, vowel co-occurrence patterns in disyllabic stems are investigated in four languages: Samoan, Tongan, Hawaiian, and Fijian, as well as reconstructed forms in Proto-Oceanic and Proto-Malayo-Polynesian. With some variation in degree, all languages exhibit an over-representation of identical vowel pairs (e.g. i–i), an under-representation of similar vowel pairs (i–e), and no special restrictions on dissimilar vowel pairs (e.g. i–o). These graded restrictions are also subject to order effects in all languages because the dissimilar > similar inequality in frequency is only found in certain orders. Our focus is on documenting the patterns supporting these generalizations so that future theoretical analysis will rest on strong empirical ground. In addition, we propose one such analysis using gradient constraints on parasitic vowel harmony.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 teacher head, 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".