A comparison of bilingual and monolingual children’s conversational repairs
Bibliographic record
Abstract
This study examined the conversational repair skills of 2- and 3-year-old French— English bilingual children and monolingual French-speaking children. While the ability to respond to requests for clarification has been well researched in monolingual children, it has not been investigated among bilingual children except to examine their ability to repair breakdowns due to the use of a language not spoken by their interlocutor. The present study provides a direct comparison of bilingual and monolingual children’s repairs of the types of breakdowns in conversations that are experienced by both populations, e.g., breakdowns due to ambiguity, choice of words, mispronunciations, inaudible utterances, and so on. A methodology of stacked requests for clarification was used to examine the range of response strategies and the overall response patterns of the children.The results reveal no differences between the bilingual and the monolingual children’s conversational repair skills. The present findings contribute to the growing body of evidence that bilingualism does not interfere with the language development of simultaneous bilinguals. As well, they extend our understanding of their ability to repair conversational breakdowns of the type that are experienced by all children.
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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 | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".