Total Assimilation in Persian Phonology: A Modified Contrastive Specification Account
Bibliographic record
Abstract
Nowadays the main stream in the most fields of linguistics including phonology is minimalism and redundancy removing, which derives from the principle of the economy of language. The advent of under specification theory in the late 19th century can be considered as the beginning of redundancy removing in the domain of phonology. During recent decades different versions of under specification such as Radical Under specification, Contrastive Specification and Modified Contrastive Specification (MCS) have been presented. Modified Contrastive Specification (MCS), which is the finding of Toronto Phonology School is based on Contrastive Hypothesis in which a contrastive hierarchy is applied to specify the contrastive features. It is believed that only contrastive features are specified in phonological representations and redundant values never exist in underlying representations. This paper aims to present a novel analysis of total assimilation process in terms of the manner of articulation in consonant clusters having the structures of –st and –zd in Persian which is an active process in phonology of Persian. Working within the framework of the MCS, through drawing a contrastive hierarchy for phonological features, this paper leads to this conclusion that the feature [continuant] in Persian consonants is a contrastive feature so by spreading this feature, the coronal stops /t/, /d/ assimilate to fricatives /s/ and /z/ respectively. To represent contrast and markedness in this system, we have proposed a contrastive hierarchy of [son] > [lab] > [cont]> [voiced] for consonants involved in the process of total assimilation in Persian.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| 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".