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Record W2234052534 · doi:10.1080/00210862.2015.1047644

Compound Verb Processing in Second Language Speakers of Persian

2015· article· en· W2234052534 on OpenAlex
Pouneh Shabani-Jadidi

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

VenueIranian Studies · 2015
Typearticle
Languageen
FieldNeuroscience
TopicNeurobiology of Language and Bilingualism
Canadian institutionsMcGill University
Fundersnot available
KeywordsPersianPriming (agriculture)VerbLinguisticsDual (grammatical number)ParsingComputer sciencePsychologyNatural language processingArtificial intelligencePhilosophyBiology

Abstract

fetched live from OpenAlex

This study investigates compound verb processing in second language speakers (L2) of Persian. Forty-six near-native L2 speakers of Persian were tested to examine the processing of transparent (non-idiomatic) and opaque (idiomatic) compound verbs, under masked priming paradigm. The results revealed a significant nominal priming effect in the opaque condition, and a numerically stronger nominal priming effect in the transparent condition. There was also an increase in the processing load on the parser when the target was an opaque compound. The results of this study seem to be compatible with the dual access or dual route hypothesis, yet with the version that assumes the two routes are activated in parallel rather than the version that assumes high frequency words are represented lexically but low frequency words are decomposed.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.084
Threshold uncertainty score0.374

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.118
GPT teacher head0.360
Teacher spread0.242 · 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