The pronunciation of English sentences by Korean children and adults
Bibliographic record
Abstract
This study examined English sentences produced by four groups of native Korean subjects (18 each) who differed according to mean age (children=12 years, adults=32 years) and length of residence in North America (means=3 vs 5 years). A delayed repetition technique was used to elicit English sentences at Time 1 and one year later at Time 2. Native English-speaking listeners used a 9-point scale to rate the sentences for overall degree of foreign accent. The ratings obtained for the native Korean (NK) subjects were converted to z-scores using the mean ratings and standard deviations obtained for sentences produced by control groups of Native children and adults. As expected, analyses of the standardized ratings revealed that the NK children produced the sentences with milder foreign accents than the NK adults did at both Time 1 and Time 2. Unexpectedly, the adult–child difference was larger at Time 2 than Time 1 because the NK children’s foreign accents diminished whereas the NK adults’ foreign accents grew significantly stronger from Time 1 to Time 2. Possible explanations for this are age-related differences in motivation, English input, or the strength of influence of Korean phonetic structures on the English sound system.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".