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Record W1696347710 · doi:10.22111/ijals.2012.63

Natural Phonological Processes in Sistani Persian of Iran

2012· article· en· W1696347710 on OpenAlexaff
Farideh Okati, Abbas Ali Ahangar, Erik Anonby, Carina Jahani

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2012
Typearticle
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsCarleton University
Fundersnot available
KeywordsSonority hierarchyLinguisticsPersianSyllableContext (archaeology)Natural (archaeology)Natural languagePhonological ruleNatural language processingPhonologyGeneralizationComputer scienceArtificial intelligenceHistorySpeech recognitionMathematics

Abstract

fetched live from OpenAlex

This article provides an overview of natural phonological processes in the dialect of Sistani Persian spoken in Iranian Sistan, and reviews theoretical implications of these processes. A representative selection of processes in the language is examined in reference to conditioning by surrounding segments and conditioning in reference to syllable structure. While assimilation and dissimilation are tied to segmental context, deletion, epenthesis and metathesis are considered in light of syllable structure requirements. Synchronically, natural processes include those that are of an allophonic nature as well as those which involve morphophonological alternation. The description of these phenomena is corroborated by a discussion of the application of natural processes in diachronic changes. The authors show that, in some cases, the Sonority Sequencing Principle (SSP) is violated in Sistani Persian. This phenomenon is attributed not to language-internal factors, but rather to the generalization of marked structures as a result of interference from Standard Persian.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.392
GPT teacher head0.609
Teacher spread0.217 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2012
Admission routes1
Has abstractyes

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