Development of L1-L2 naming skills in a monolingual context: Evidence from children and adolescents
Bibliographic record
Abstract
Adolescence is marked by significant developmental changes that can influence language processing and control. This study aimed to uncover developmental differences in language co-activation and control in unbalanced Spanish (L1)-English (L2) bilinguals. Children and adolescents attending bilingual schools within a L1 monolingual context completed a picture-naming task including cognates and non-cognates nouns, with collection of behavioral and ERP data. The study consistently found a cognate facilitation effect (CFE) in L2, evident in enhanced accuracy, faster reaction times, and reduced N400 negativity for cognates in comparison with no-cognate nouns. However, in L1, CFE was only observed in the N400 component, indicating weaker transfer from L2 to L1. Additionally, children exhibited greater N200 negativity when naming cognates in L1, while adolescents showed no N200 modulations, suggesting differences in frontal control region involvement and potential differences in control strategies. Language co-activation appears independent of maturation, while language control depends on development. • Language co-activation initiates at early ages and it is independent of maturational changes. • Transfer from L2 to L1 is less established than L1 to L2 transfer; asymmetrical coactivation effect. • Development affects language control; adolescents use control more efficiently. • L2 learning in a L1 monolingual context have an impact on language development. • Neural and behavioral responses showed differential sensitivity during L1 naming.
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 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 | 0.000 | 0.001 |
| 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".