MétaCan
Menu
Back to cohort
Record W2979340818 · doi:10.1075/lab.19043.goa

Prosodic effects on L2 grammars

2019· article· en· W2979340818 on OpenAlexaff
Heather Goad, Lydia White

Bibliographic record

VenueLinguistic Approaches to Bilingualism · 2019
Typearticle
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsMcGill University
Fundersnot available
KeywordsSyntaxLinguisticsComputer scienceInflectionFocus (optics)PragmaticsSemantics (computer science)Rule-based machine translationTRACE (psycholinguistics)Contrast (vision)Natural language processingComprehensionArtificial intelligenceProgramming languagePhilosophy

Abstract

fetched live from OpenAlex

Abstract This paper provides an overview of the Prosodic Transfer Hypothesis (PTH), which accounts for certain difficulties that learners experience with L2 morphosyntax. We focus on inflection and articles, which have often been accounted for through defective syntactic representations or problems with the interface between morphology and syntax (inflection) and between semantics or discourse/pragmatics and syntax (articles). We argue that some problems in these domains reflect transfer of L1 prosodic constraints: certain forms cannot be prosodically represented as target-like and hence are omitted or mispronounced. We trace how the PTH has developed over time, from its initial instantiation as involving permanent L1 transfer, to currently, where L1 representations are seen as adaptable to the needs of the L2, and new representations can in fact be acquired. We provide an overview of work conducted in this framework and discuss how the theory has been extended beyond production to encompass comprehension and processing.

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)0.007
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0020.001
Open science0.0000.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0140.001

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 head0.117
GPT teacher head0.333
Teacher spread0.215 · 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

Citations64
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueLinguistic Approaches to BilingualismSame topicPhonetics and Phonology ResearchFrench-language works237,207