Acquisition of Consonant Clusters and Acceptable Variants in Chinese-Influenced Malaysian English-Speaking Children
Bibliographic record
Abstract
PURPOSE: This study investigated consonant cluster acquisition in Chinese-influenced Malaysian English (ChME)-speaking children. METHOD: This cross-sectional study involved 262 typically developing ChME-speaking children (138 girls, 124 boys) ages 3 to 7 years old. A single-word picture-naming task, which contained 66 words and targeted 32 syllable-initial (SI) and 14 syllable-final (SF) consonant clusters, was administered. RESULTS: Older children produced more correct productions than younger children, and there was no sex effect for consonant cluster production. SF consonant clusters were more accurate than SI consonant clusters among the younger children. The overall sequence of SI consonant cluster accuracy based on cluster categories from most to least accurate was /s/ + C, C + /w/, C + /j/, C + /l/, and C + /r/, whereas for SF consonant clusters, the order was C + stop, C + /s/, nasal + C, and /l/ + C. Two-element clusters consistently had higher accuracy in comparison to three-element clusters across the age groups. The overall consonant cluster accuracy of the present study showed similar patterns to those found in previous studies of Standard English. CONCLUSION: The findings of the study will be useful in the assessment of consonant cluster production of ChME-speaking 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 | 0.000 | 0.001 |
| 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 | 0.000 |
| 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".