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Record W2991067088 · doi:10.1017/s1366728919000610

Vulnerability of clitics and articles to bilingual effects in typically developing Spanish–English bilingual children

2019· article· en· W2991067088 on OpenAlexaff
Anny Castilla-Earls, Ana Teresa Pérez‐Leroux, L. Martínez Nieto, M. Adelaida Restrepo, Christopher Barr

Bibliographic record

VenueBilingualism Language and Cognition · 2019
Typearticle
Languageen
FieldPsychology
TopicLanguage Development and Disorders
Canadian institutionsUniversity of Toronto
FundersNational Institute on Deafness and Other Communication Disorders
KeywordsCliticNeuroscience of multilingualismPsychologyLinguisticsPhilosophy

Abstract

fetched live from OpenAlex

Abstract This study examines bilingual effects in Spanish–English bilingual children with good maintenance of the minority language. The present study compares the performance of a group of Spanish-monolingual children (MON; n = 30) with two groups of Spanish-speaking bilingual children (Low English proficiency group: LEP; n = 36; High English proficiency group, HEP; n = 36) on the elicited productions of Spanish articles and object clitics. Our results suggest that children with LEP performed significantly lower than MON children of the same age on both articles and clitics in Spanish. However, children with HEP, who were a year older on average, performed similarly to the MON group. Both groups of bilingual children produced errors of clitic omission and substitution, but these errors were minimal in the MON group. The results suggest that Spanish clitics and articles are vulnerable to bilingual effects for English/Spanish speaking children with good Spanish maintenance.

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)0.002
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 score0.009
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
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 head0.008
GPT teacher head0.285
Teacher spread0.276 · 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

Citations40
Published2019
Admission routes1
Has abstractyes

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