Bibliographic record
Abstract
Abstract The position that languages require both coda and onset options for the syllabification of word-final consonants is adopted. The latter option is further divided into languages where final consonants are onsets of empty-headed syllables and those where final consonants are syllabified through onset-nuclear (ON) sharing. ON sharing is reserved for languages where final consonants display fortition (overt release): the nucleus hosts the release of the consonant. Empirical evidence from across populations demonstrates that ON sharing is unmarked. It is favoured among the outputs of first and second language learners and individuals with Specific Language Impairment. It is further argued that final onsets are optimal for parsing in end-state grammars, as they demarcate the right word-edge more effectively than codas. Among the two types of onsets, ON sharing is preferred: through the nuclear release, it is better able to host the range of contrasts that right-edge onsets display. The parsing argument serves to illustrate how ON sharing provides an advantage to end-state grammars, beyond being an emergent property from acquisition.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".