International Students’ Perceptions of Their University-To-Work Transition
Bibliographic record
Abstract
International students are increasingly seeking a foreign education. Part of this increase is due to institutional goals for revenue generation and for diversifying the student population. At the same time, governments of developed countries such as Canada are creating incentives for international students to work in the destination country post-graduation to fill skilled labour shortages. Post-study, international students often face barriers when integrating into the workforce, defeating these policies and decreasing the value of a foreign education. Moreover, researchers have predominately focused on the in-study experiences of international students, particularly their academic adjustment. Few studies have addressed the post-study experiences of former international students. In my doctoral thesis, I sought to help address this gap by investigating the post-study experiences of former international students, three to five years post-graduation. Specifically, I used Interpretative Phenomenological Analysis to explore how former international students in Canada made sense of their transition out of university and into the Canadian workforce. Guided by a Systems Theory Framework, I used the results to offer insights into the barriers these former international students faced, how they were able to overcome them, and the influences that were important to their workplace transition. Implications included suggestions for policy-makers, universities, and career practitioners to help international students successfully navigate the transition into and out of study. By supporting former international students in their post-study transition, practitioners can help with concerns such as un/under-employment, universities can help improve the value of education, and policy-makers may recruit highly talented workers to address labour shortages.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.007 |
| Scholarly communication | 0.014 | 0.004 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".