Effects of language mixing on bilingual children’s word learning
Bibliographic record
Abstract
Language mixing is common in bilingual children’s learning environments. Here, we investigated effects of language mixing on children’s learning of new words. We tested two groups of 3-year-old bilinguals: French–English (Experiment 1) and Spanish–English (Experiment 2). Children were taught two novel words, one in single-language sentences (“Look! Do you see the dog on the teelo?”) and one in mixed-language sentences with a mid-sentence language switch (“Look! Do you see the chien/perro on the walem?”). During the learning phase, children correctly identified novel targets when hearing both single-language and mixed-language sentences. However, at test, French–English bilinguals did not successfully recognize the word encountered in mixed-language sentences. Spanish–English bilinguals failed to recognize either word, which underscores the importance of examining multiple bilingual populations. This research suggests that language mixing may sometimes hinder children’s encoding of novel words that occur downstream, but leaves open several possible underlying mechanisms.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".