Bilingual children's lexical strategies in a narrative task
Bibliographic record
Abstract
We investigated how bilinguals choose words in a narrative task, contrasting the possibilities of a developmental delay vs. compensatory strategies. To characterize a developmental delay, we compared younger (three to five years) and older (seven to ten years) children's lexicalization of target words (Study 1). The younger children told shorter stories, omitting many of the target concepts. To characterize compensatory strategies, we compared late second language learning adults to (seven- to ten-year-old) monolingual children (Study 2). The adults often lexicalized the target concepts even when not producing the target words. Finally, we compared French-English bilingual children with French and English monolinguals, all seven to ten years old (Study 3). The bilinguals produced fewer target words than the monolinguals. However, when not producing the target words, the bilinguals often lexicalized the concepts, sharing more in common with the adults (Study 2) in their use of compensatory strategies than with the younger children (Study 1). This interpretation was further corroborated by comparisons across studies (Study 4).
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".