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Record W4394903714 · doi:10.1016/j.lingua.2024.103724

The linguistic and metalinguistic abilities of monolingual and bilingual speakers with Prader–Willi syndrome

2024· article· en· W4394903714 on OpenAlexaff
Estela García-Alcaraz, Juana M. Liceras

Bibliographic record

VenueLingua · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Syndromes and Imprinting
Canadian institutionsWilfrid Laurier UniversityUniversity of Ottawa
Fundersnot available
KeywordsGrammaticalityNeuroscience of multilingualismPsychologyLinguisticsMetalinguistic awarenessCatalanSemantics (computer science)MultilingualismGrammarComputer science

Abstract

fetched live from OpenAlex

Although bilingualism is encouraged and promoted among typically developing (TD) individuals, some countries continue to recommend monolingualism for non-TD individuals. This common practice seems unfounded because existing research investigating the effects of bilingualism on non-TD individuals has not revealed a detrimental effect of bilingualism. In this study, we analyzed the linguistic and metalinguistic abilities of individuals with Prader–Willi syndrome (PWS). To manipulate grammaticality and semantics, a grammaticality judgment task was created and administered in Spanish to eight Spanish monolingual speakers and seven Spanish–Catalan bilingual speakers, all with PWS. Similar results were obtained for linguistic and metalinguistic abilities in both groups, even if the bilingual speakers were Catalan dominant. Thus, these results not only support previous research within the field in not identifying a negative effect of bilingualism but also emphasize the fact that bilingual speakers can mirror monolingual speakers even in their “weaker” language.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.006
GPT teacher head0.235
Teacher spread0.229 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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