Motion Lexicalization in Chinese among Heritage Language Children in Canada
Bibliographic record
Abstract
Heritage language speaking children often show signs of attrition, particularly as they get older and are educated in the majority language of the society where they live. In this study, we tested the hypothesis that simplification is one process of attrition for heritage language speakers. We tested this hypothesis on the expression of motion events among children who are first language speakers of Mandarin Chinese and early second language speakers of English, the majority language in this community. We compared their motion expressions to those of monolingual Mandarin-speaking children living in mainland China. Two age groups were included: younger children (4-6 years, not yet in school) and older children (8-10 years; in school for two to five years). The children watched a cartoon and recounted the story. We coded the motion expressions used in their retellings. The results showed that the older bilingual children showed clear signs of attrition, particularly simplification, but also some signs of cross-linguistic influence from English. These results suggest that attrition in a heritage language can quickly follow the onset of schooling in the majority language.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 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) | 0.002 | 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 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".