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Record W2053140199 · doi:10.1075/arla.2.06ros

Relations between segmental and prosodic structure in first language acquisition

2002· article· en· W2053140199 on OpenAlexaffabout
Yvan Rose

Bibliographic record

VenueAnnual Review of Language Acquisition · 2002
Typearticle
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsMarkednessLinguisticsFeature (linguistics)PhonologyComputer scienceLanguage acquisitionMelodyPsychology

Abstract

fetched live from OpenAlex

In this paper, I discuss a number of relations that take place between melodic content and higher prosodic structure in first language phonological development. I explore acquisition patterns found in data on the acquisition of Québec French. Starting with the observation that prosodic structure and, more specifically, stressed syllables, play a central role in phonological acquisition, I hypothesize that the inter-relations between prosodic and segmental structure posited by formal models of phonological organisation should be witnessed within and across developmental stages. I support this hypothesis through two findings from the French data. First, complex onsets emerge in stressed syllables before unstressed ones. Second, different types of consonants (placeless versus place-specified) emerge in word-final position at different stages. From these observations, I argue that the phenomena observed in these data are best captured in an analysis based on constituent structure and relationships between feature specification and prosodic constituency, which are governed by universal markedness.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.014
GPT teacher head0.329
Teacher spread0.315 · 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 designObservational
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

Citations10
Published2002
Admission routes2
Has abstractyes

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