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Onset‐Nucleus Sharing and the Acquisition of Second Language Codas: A Stochastic Optimality Theoretic Account*

2011· article· en· W1604832119 on OpenAlex

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

VenueStudia Linguistica · 2011
Typearticle
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsConcordia University
Fundersnot available
KeywordsSyllableLinguisticsGrammarWord orderComputer scienceSecond-language acquisitionBrazilian PortugueseOptimality theoryOrder (exchange)PsychologyPortuguesePhilosophyPhonologyEconomics

Abstract

fetched live from OpenAlex

Abstract. The study provides a stochastic optimality theoretic account for the acquisition of word‐final voiceless stops (codas) in the developing grammar of Brazilian Portuguese (BP) speakers learning English as a second language (L2). Following a variationist methodology for data collection and analysis of learner speech, the study focuses on Onset‐Nucleus Sharing (ONS), a developmental phenomenon found in intermediate stages of L2 acquisition, phonetically manifested as aspiration. This phonetic behavior is interpreted to be an instantiation of ONS, wherein the potential coda syllabifies as an onset and, in order to be licensed, some of its features spread (via aspiration) into the following empty nucleus in order to optimize the syllable shape of the emerging grammar.

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)0.001
metaresearch head score (Gemma)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.754
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.034
GPT teacher head0.336
Teacher spread0.302 · 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