Individual differences and language interdependence: a study of sequential bilingual development in Spanish–English preschool children
Bibliographic record
Abstract
The purpose of the current study is to examine language influence in sequential bilinguals. Specifically, this study evaluates whether performance in a first language predicts success in the acquisition of a second language nine months after exposure to the second language begins. Forty-nine Spanish-speaking children attending English-only pre-kindergarten classrooms participated in the study. Children were assessed in Spanish at the beginning of the school year using the Spanish version of the Bilingual English Spanish Assessment (BESA), MLU in words, and a lexical diversity measure, D, obtained from a language sample. Nine months later, children were assessed in English using the English-BESA. Analyses indicated significant correlations between semantic and grammatical measures across languages. Stepwise regression analyses found that grammatical and semantic measures in the first language robustly predicted grammatical and semantic measures in the second language. We propose that native language skills predict the success in second language acquisition, not because of linguistic transfer, but by virtue of individual differences in language learning abilities present in typical populations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".