Learning the Language of a New Country: A Ten‐year Study of English Acquisition by South‐East Asian Refugees in Canada
Bibliographic record
Abstract
ABSTRACT The University of Toronto Refugee Resettlement Project (RRP) investigated language acquisition over a ten‐year period among a sample of 608 South‐East Asian Refugees in Canada. Two years after arrival, 17 per cent spoke English well, 67 per cent had moderate command of the language, and 16 per cent spoke no English. Ten years later, 32 per cent had good language skills, 60 per cent moderate skills, and 8 per cent still spoke no English. The most rapid improvement occurred during the early years of resettlement. Although demographic characteristics and pre‐immigration achievement were the major factors determining English‐language proficiency during the early years of resettlement, post‐migration opportunities and incentives became increasingly important over time. The results highlight the responsibility receiving countries have to provide opportunities and incentives to facilitate language acquisition by newcomers.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".