A 4-year longitudinal study examining lexical and syntactic bootstrapping in English Language Learners (ELLs) and their monolingual peers.
Bibliographic record
Abstract
age = 77 months, low socioeconomic status backgrounds). Children were assessed annually from Grade 1 to Grade 4 on a syntactic and a vocabulary task. Overall, autoregressive cross-lagged analyses indicated that early syntax predicted later vocabulary and vice versa, yet, the magnitude of prediction varied across groups. Notably, in the early stages of L2 learning, the predictive power from vocabulary to syntax was stronger than that in the opposite direction. Moreover, the predictive power from vocabulary to syntax was consistently stronger in the ELL than in the EL1 group. The results suggest that, in general, with sufficient quantity and quality of exposure to the L2, lexical and syntactic bootstrapping coexist. However, among novice young ELLs, bootstrapping is stronger from vocabulary to syntax than the other way around. Results underscore the importance of studying the relations between vocabulary and syntax longitudinally, and caution about an injudicious application of L1-based models to young L2 children's language development. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".