Assessing Canada’s support of international students: a comprehensive review of Canada’s retention and settlement of its “Model Immigrants”
Bibliographic record
Abstract
The unprecedented growth in the number of international students in Canada over the last decade has drawn the attention of policy makers at all levels of government in Canada. The federal, provincial and territorial levels of government have introduced permanent residency pathways to encourage international students to become permanent residents of Canada. International students are an attractive group as prospective immigrants because of their Canadian education and human capital. However, they experience variety of challenges transitioning to employment and permanent residency in Canada. Lack of limited co-operative education opportunities and labor market preparation hinders the process of finding employment while the absence of settlement services and the complexities of immigration policies complicate the process of seeking permanent residency in Canada. These realities hold significant policy implications for the federal and provincial levels of government because Canada continues to admit educated and skilled labor in order to address labor and demographic needs. Key words: socioeconomic integration, human capital, internationalization, transitional barriers, recruitment and retention
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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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.009 | 0.016 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".