MétaCan
Menu
Back to cohort
Record W3120365255 · doi:10.21248/zaspil.19.2000.70

word is a phrase, phonologically : evidence from Persian stress

2000· article· en· W3120365255 on OpenAlex
Arsalan Kahnemuyipour

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueZAS Papers in Linguistics · 2000
Typearticle
Languageen
FieldArts and Humanities
TopicLinguistics and language evolution
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPhraseStress (linguistics)GeneralizationSection (typography)PersianNatural language processingComputer scienceLinguisticsWord (group theory)Artificial intelligenceNounPart of speechMathematicsPhilosophy

Abstract

fetched live from OpenAlex

The purpose of this paper is to provide a unified (i.e. independent of lexical categories) account of Persian stress. I show that by differentiating word- and phrase-level stress rules, one can account for the superficial differences exemplified in (1) above and many of the stipulations suggested by previous scholars. The paper is organized as follows. In section 1, I look at nouns and adjectives and propose a rule that would account for their stress pattern. In section 2, I extend the stress rule to verbs and show the problem this category poses to our generalization. The main proposal of this paper is discussed in section 3. I introduce the phrasal stress rule in Persian and show that by differentiating word-level and phrase-level stress rules, one can come to a unified account of Persian stress. Section 4 deals with some problematic eases for the proposed generalization and discusses some tentative solutions and their theoretical consequences. Section 5 concludes the paper.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.957
Threshold uncertainty score0.968

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0330.000

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 head0.027
GPT teacher head0.246
Teacher spread0.220 · 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