sC Clusters are (almost always) coda-initial
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This article defends the position that syllables have internal structure, through an examination of sC clusters. Although perceptual factors will be shown to account for why it is sibilants that pattern in unexpected ways in clusters, it will be argued that the behavior of sC clusters cannot be explained solely by functional considerations. Among structural approaches to the syllable, it is argued that sC clusters are best analyzed as coda+onset, not as appendix+onset. The typological patterns of sC cluster well-formedness on the sonority dimension and sC cluster repair are shown to follow only from a coda analysis of s: the patterns follow from constraints on syllable contact. In view of this, it will be shown that the two most commonly defended options for the organization of s as an appendix, the syllable and the prosodic word, can be straightforwardly captured under a coda approach, through a comparative examination of English and Italian. It will further be shown that the distribution of aspiration in English is amenable to a coda analysis of s. Finally, it is argued that some languages require an analysis of sC other than coda+onset. This situation holds in Acoma: an empty nucleus interrupts putative sC clusters in this language.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.007 |
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 it