Bibliographic record
Abstract
Abstract Diola-Fogny is a well-known example of a tongue root harmony language with assimilatory dominance of [+ATR] vowels. Less well known, however, are some asymmetries involving the frequency and distribution of [+ATR] and [-ATR] vowels. In addition to being dominant, [+ATR] vowels are subject to restrictions on their occurrence in certain classes of function words and affixes and occur with far lower overall frequency than [-ATR] vowels. In essence, they pattern like a marked sound class. This paper focuses on some implications of these findings for a theoretical topic of interest: markedness relations involving tongue root features. The Diola-Fogny patterns conform quite well to the expectations of a traditional understanding of featural markedness, which equates the dominant value of a feature with the marked one. They are problematic, however, for a widely assumed view of tongue root markedness relations that treats [-ATR] as universally marked in high vowels. Under this view, marked patterning of all [+ATR] vowels (including high [+ATR] [ i ], [ u ]) is unexpected. I show that such patterning is intelligible in a framework in which markedness has a representational basis and in which [+ATR] quality is represented by a privative feature [ATR].
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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 | 0.001 | 0.000 |
| 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) | 0.000 | 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".