Assessing Canada’s Support of International Students [Working Paper]: A Comprehensive Review of Canada’s Retention and Settlement of its “Model Immigrants”
Bibliographic record
Abstract
Abstract The aim of this research paper is to present the findings of an extensive literature review related to barriers international students experience transitioning to employment and permanent residency in Canada. International students who wish to work in Canada temporarily have difficulty receiving employment because of limited co-operative education opportunities and a lack of professional networks. The lack of settlement services, the numerous complexities of immigration policies, and the minimal awareness among students hinder the process for these individuals to immigrate to Canada permanently. These realities hold significant policy implications for the federal and provincial levels of government because Canada continues to admit educated and skilled labour in order to address national priorities such as long-term labour shortage and population decline. International students, especially those who hope to secure employment and permanency in Canada, are an attractive population, given the Canadian education and social capital they have received upon completion of their studies. This report will also provide a comprehensive review of several best practices and policy suggestions in addressing the challenges described above. Additionally, I will offer some practical recommendations for those involved in this transition process.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 | 0.018 |
| 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) | 0.003 | 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".