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Record W2327247112 · doi:10.1055/s-0035-1549110

Preschool Language Interventions for Latino Dual Language Learners with Language Disorders: What, in What Language, and How

2015· article· en· W2327247112 on OpenAlexaboutno aff
Gabriela Simon‐Cereijido

Bibliographic record

VenueSeminars in Speech and Language · 2015
Typearticle
Languageen
FieldPsychology
TopicLanguage Development and Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsPsychological interventionVocabularyPsychologyLanguage developmentFirst languageDual languageLanguage assessmentLanguage impairmentHome languagePopulationLanguage acquisitionQuarter (Canadian coin)English languageLinguisticsDevelopmental psychologyMedicineMathematics educationGeographyEnvironmental healthPsychiatry

Abstract

fetched live from OpenAlex

About a quarter of young children in the United States are dual language learners. The large majority are Latino children who are exposed to Spanish in their homes. The language needs of Latino dual language preschoolers are different from the needs of monolingual English-speaking children. As a group, they are likely to live in environments that put them at risk of delays in language development. This situation is direr for dual language preschoolers with language impairment. Recent findings from studies on interventions for Spanish-English preschoolers with language impairment suggest that a bilingual approach does not delay English vocabulary and oral language learning and promotes Spanish maintenance. Targets and strategies for different language domains are described. The effects of pullout versus push-in interventions for this population are preliminarily explored.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.017
GPT teacher head0.315
Teacher spread0.298 · 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 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

Citations13
Published2015
Admission routes1
Has abstractyes

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