Lexical acquisition over time in minority first language children learning English as a second language
Bibliographic record
Abstract
ABSTRACT The English second language development of 19 children (mean age at outset = 5 years, 4 months) from various first language backgrounds was examined every 6 months for 2 years, using spontaneous language sampling, parental questionnaires, and a standardized receptive vocabulary test. Results showed that the children's mean mental age equivalency and standard scores on the Peabody Picture Vocabulary Test—Third Edition nearly met native-speaker expectations after an average of 34 months of exposure to English, a faster rate of development than has been reported in some other research. Children displayed the phenomenon of general all-purpose verbs through overextension of the semantically flexible verb do , an indicator of having to stretch their lexical resources for the communicative context. Regarding sources of individual differences, older age of second language onset and higher levels of mother's education were associated with faster growth in children's English lexical development, and nonverbal intelligence showed some limited influence on vocabulary outcomes; however, English use in the home had no consistent effects on vocabulary development.
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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 | 0.000 | 0.002 |
| 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 | 0.001 |
| 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".