Vocabulary Skill of Bilingual Adolescents: The Effects of First Language Background and Language Learning Context
Bibliographic record
Abstract
This thesis investigated the vocabulary skill of bilingual adolescents and young adults with two studies. Study 1 examined the contributions of English phonological awareness and morphological awareness to English vocabulary in 80 Spanish-English and 117 Chinese-English bilingual adolescents educated in Canada. Using Structural Equation Modelling, the study showed that English derivational awareness, word reading and length of residence contributed to English vocabulary for both language groups. In addition, for the Chinese-English bilingual group, English phonological awareness contributed to English vocabulary both directly and indirectly through the mediation of English word reading. Study 2 compared the contributions of Chinese compound awareness and homograph awareness to Chinese vocabulary between Chinese L1 young adults educated in China and in Canada. Participants included 96 and 66 first-year university students in China and Canada, respectively. Using hierarchical regression analyses, Study 2 showed that Chinese homograph awareness and character reading contributed to Chinese vocabulary for both groups of Chinese L1 young adults; however, the contribution of Chinese compound awareness was not significant. The association of Chinese homograph awareness with Chinese vocabulary was not significantly different between the two groups, whereas the association of Chinese character reading with Chinese vocabulary was stronger for the Chinese L1 young adults in China. Overall, the thesis highlights the importance of morphological awareness to vocabulary across English and Chinese for older students.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| 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".