Amount trumps timing in bilingual vocabulary acquisition: Effects of input in simultaneous and sequential school-age bilinguals
Bibliographic record
Abstract
Objectives: This study examined the extent to which the language performance of school-age bilingual children is impacted by the amount of language exposure they have received in each language versus the timing of this exposure in terms of the age of first exposure (AoE). Methods: Receptive and expressive vocabulary and word morphology measures were administered in both languages to school-age simultaneous and sequential learners of French (other language English), and to their monolingual counterparts. Data and analysis: The study included 64 children in first grade and 68 children in third grade in French schools in Montreal. Within each grade level, simultaneous bilinguals, sequential bilinguals, and monolinguals were equivalent in age, nonverbal cognition and socio-economic status (maternal education). Detailed information on previous language exposure was gathered by parent report. Conclusions: Simultaneous bilinguals performed somewhat better than sequential bilinguals; however both groups overall performed significantly more poorly than monolinguals. Differences in performance between simultaneous and sequential bilinguals were mediated by differences in amount, not timing, of exposure. Sequential learners in grade 1 required lower amounts of input to reach high French scores than did their simultaneous counterparts; sequential and simultaneous learners in grade 3 did not differ in this respect. This finding suggests that the recency of bilingual exposure is a significant determiner of the rate of second language learning. The amount of exposure to each language since birth predicted performance in each language of the bilingual children. Originality: Bilingual children with different AoEs were compared while also controlling for differences in amount of exposure. Significant implications: The results call into question the traditional separation between simultaneous and sequential bilinguals and shows that an early start of bilingualism does not in and of itself predict better performance or performance within the monolingual range. Better performance was more strongly related to amount than timing of exposure.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".