The Effect of Language Background and Grade Level on Fricative Production of Children Learning Mandarin in a Chinese–English Bilingual Program
Bibliographic record
Abstract
PURPOSE: This study aims to examine how language background and grade level influence the voiceless sibilant fricative production of two groups of children enrolled in a Mandarin-English bilingual school in Canada. One group of children was exposed to Mandarin at home as heritage language (HL), and the other group had little to no exposure to Mandarin until they started learning it as a second language (L2) at school. METHOD: Eighty-two children in Grades 1, 3, or 5 as well as 12 teachers engaged in picture-naming tasks in both English and Mandarin. Their speech production of voiceless sibilant fricatives was analyzed using both transcription and acoustic methods. The center of gravity (CoG) and F2 onset of the vowel following the fricatives were measured in the acoustic analysis. RESULTS: Both groups of children exhibited high accuracy rates in producing English /s/ and /ʃ/ and were able to distinguish the two English fricatives based on the CoG regardless of their grade level. For Mandarin fricatives, children in the higher grades achieved higher accuracy rates. Mandarin HL speakers had a higher accuracy rate than Mandarin L2 speakers, with their productions more closely resembling teachers' productions. The CoG distinguished all three Mandarin fricatives regardless of grade level and language background. However, significant differences in F2 onset were only observed in the HL group. CONCLUSIONS: The finding that unshared fricatives were more difficult than shared ones, along with the significant impact of language background-but not grade level-on the accuracy of fricatives unique to Mandarin, suggests that students, even in higher grades, can benefit from more explicit teaching. The developmental patterns and error trends identified in this study can serve as a reference for speech assessment and aid in planning treatment or instructional sessions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".