Bibliographic record
Abstract
Canadian higher education (CHE) places strategic importance on internationalisation. In the last decade, there has been a steep increase in the enrolment of international students in CHE. India is leading in study permit holders. The increase in students from India, particularly Punjab, is linked to the seemingly easy route to migration post-graduation. Punjabi students (PS) are a target for mass recruitment with the often-false promise of a pathway to permanent residency. This process particularly impacts those admitted to lower-tier institutions that provide low-value credentials. While education-migration in Canada assumes that international education is a route to migration and valuable credentials for skilled jobs, PS trajectory skews towards migration, often at a high personal and professional cost. This issue was taken up by non-governmental grassroots organisations (NGOs), who seek to provide support and advocacy for PS facing barriers in education-migration. This chapter draws on interviews with grassroots NGO volunteers to enrich the limited literature on the education-migration of PS in Canada. It highlights the barriers that PS face in education-migration and calls for changes in policies and practices to support PS in this process.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.044 | 0.017 |
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".