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Record W2043526168 · doi:10.1017/s0142716409990506

The potential of studying specific language impairment in bilinguals for linguistic research on specific language impairment in monolinguals

2010· article· en· W2043526168 on OpenAlexaboutno aff
Monika Rothweiler

Bibliographic record

VenueApplied Psycholinguistics · 2010
Typearticle
Languageen
FieldPsychology
TopicLanguage Development and Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsSpecific language impairmentPsychologyLanguage impairmentNeuroscience of multilingualismLinguisticsCognitive psychologyDevelopmental psychologyPhilosophy

Abstract

fetched live from OpenAlex

In her Keynote Article, Paradis discusses the role of the interface between bilingual development and specific language impairment (SLI) on two different levels. On the level of theoretical explanations of SLI, Paradis asks how domain general versus domain-specific perspectives on SLI can account for bilingual SLI, as well as what bilingual SLI may contribute to the discussion of these theories. Paradis argues in favor of domain-specific deficits (in addition to well-documented processing deficits in SLI), and especially for the maturational model (Rice, 2004). She argues against a mere processing deficit of input information and against deficits in working memory and processing speed as sole sources of SLI. On the practical level, Paradis focuses on the question of whether and how language tests that have been standardized for monolingual children are valid for the assessment of SLI in bilingual children. Both discussions, on theory and on practice, are based on empirical data from Canadian studies on bilingual children with and without SLI carried out by Johanne Paradis, Martha Crago, and Fred Genesee (e.g., Crago & Paradis, 2003; Paradis, 2007; Paradis, Crago, & Genesee, & Rice, 2003).

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.179
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.048
GPT teacher head0.401
Teacher spread0.352 · 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 designQualitative
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

Citations4
Published2010
Admission routes1
Has abstractyes

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