International Students and the Post Graduate Work Permit Program (PGWPP)
Bibliographic record
Abstract
This study investigates the impacts of Canada's PGWPP on the employment outcomes of international students and how their integration into the Canadian labour market could be improved. The following research question is addressed in this paper: "What effect does PGWPP have on the employment outcomes of international students, and how can their integration in the workforce be enhanced? A qualitative methodology was adopted based on in-depth interviews with international graduates and critical stakeholders, including employers and university representatives. The descriptive analysis of the survey data that shows trends in awareness and utilization of PGWPP was also used. Participants were chosen by a purposive sampling strategy to ensure a broad representation across demographic variations, fields of study, and employment experiences. Findings showed that while PGWPP facilitates entry into the workforce for many graduates, systemic barriers around credential recognition, limited networking opportunities, and employer biases remain vital challenges. Participants identified a need for better career services, employer education, and program process streamlining. This research underlines the need for targeted policy interventions and increased institutional support if the program is to realize its full potential. It contributes to scholarship and practice by providing actionable insights to policymakers, educational institutions, and employers on how best to ensure fair and prosperous integration of international graduates into the Canadian labour market.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.023 | 0.002 |
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".