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Record W2125201329 · doi:10.1017/s0142716409990531

Response to Commentaries on the interface between bilingual development and specific language impairment

2010· article· en· W2125201329 on OpenAlexaff
Johanne Paradis

Bibliographic record

VenueApplied Psycholinguistics · 2010
Typearticle
Languageen
FieldPsychology
TopicLanguage Development and Disorders
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsSpecific language impairmentPsychologyNeuroscience of multilingualismPerspective (graphical)Interface (matter)LinguisticsSection (typography)SituatedLanguage developmentCognitionCognitive scienceCognitive psychologyDevelopmental psychologyComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

The Keynote Article examined research situated at the interface of bilingualism and specific language impairment (SLI) primarily to evaluate theories of SLI and secondarily for clinical considerations. The purpose was not to argue for one theoretical perspective over another, but instead to demonstrate how they both need some refinements and extensions to account for data from bilingual children. The breadth and depth of the Commentaries on this Keynote Article were impressive, and common themes emerged across many of them. This response article is organized into sections according to these themes. I hope that the review and synthesis in each section reveals how this collection of contributions has moved us forward in our understanding of the interface between bilingual development and SLI. The final section of this article includes more longitudinal data from English second language (L2) children to explore ideas arising from the discussion of cross-linguistic transfer, cognitive processes, and age effects.

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 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)0.000
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: Empirical
Teacher disagreement score0.757
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0010.001

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 head0.023
GPT teacher head0.334
Teacher spread0.311 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations18
Published2010
Admission routes1
Has abstractyes

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