Laryngeal co-occurrence restrictions in Aymara: contrastive representations and constraint interaction
Bibliographic record
Abstract
Through analyses of laryngeal co-occurrence restrictions in two varieties of Aymara, this article shows that contrastively specified representations are crucial in shaping phonological patterning. The article argues for a model of contrastive specifications in which features are hierarchically ordered (Dresher 2009). This results in asymmetries between features such that, for a given inventory, some features are contrastively specified in a greater number of segments than others. This asymmetry between features plays a central role in accounting for the interaction of place of articulation features and laryngeal features in Bolivian Aymara. The article also demonstrates that contrastive representations can be achieved as output forms in Optimality Theory and that the constraints which determine contrastive representations can be integrated with constraints which motivate restrictions on the co-occurrence, ordering and location of laryngeal features in Peruvian and Bolivian Aymara.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".