The typology of the distributional restrictions of a feature: occlusion and bipositionality
Bibliographic record
Abstract
Abstract In some languages, the distribution of occlusion is highly restricted and interacts with bipositionality. Ulfsbjorninn and Lahrouchi, henceforth UL, (Ulfsbjorninn, Shanti & Mohamed Lahrouchi. 2016. The typology of the distribution of Edge: The propensity for bipositionality. Papers in Historical Phonology 1. 109–129) present a typology of this distributional restriction. UL demonstrated that in order to capture the typology of the feature restrictions, one requires Melody-to-Structure Licensing Constraints (MSLCs). These are a ‘prosodic licensing’-type mechanism that express grammatical statements dictating the distributional co-occurrence of a feature/melody <M>, against a certain state of syllable structure <S>. Crucially, to get the typology right, MSLCs must be stated bidirectionally: Bottom up (M must be contained by S), or Top down (S must contain M). This is theoretically significant because it excludes any analysis where occlusion and bipositionality are simply equated. We note, however, that the typology proposed by UL looks more symmetrical than it is; only two of the four predicted possibilities are discussed. Here we will fully expand the MSLC analysis, showing that each predicted type is attested. The bidirectional nature of MSLCs is critical since a simpler statement such as: ‘feature sharing is strength’ is not elaborate enough to account for the typology. We will also show that a completely unattested system, where the occlusion feature is systematically restricted to monopositional structures is excluded. This is because (a) MSLCs cannot formulate the statement, and (b) there is no other contributor to phonological strength that will generate it either, since bipositional structures are always positionally strong (Ségéral, Philippe & Tobias Scheer. 2001. La Coda-Miroir. Bulletin de la Société de Linguistique de Paris 96. 107–152) and sharing-strong (Honeybone, Patrick. 2002. Germanic obstruent lenition: Some mutual implications of theoretical and historical phonology. University of Newcastle upon Tyne. PhD thesis).
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".