“I can’t trust anyone”: International Students’ Experience with Student Support Services in Canada
Bibliographic record
Abstract
The number of international students in Canada continues to rise. Out of the 642,480 international students in Canada, 60% of them want to immigrate to Canada permanently after completing their studies (CBIE, 2018). Using data from a qualitative research study, I will discuss the transition of international students to university at a research institution in Southwestern Ontario. This paper focuses on their transition to Canada through their engagement with on-campus support services. The findings suggest very different levels of support in accessing resources within the International Student Centre compared to other student service offices on campus. Within the purview of the International Student Centre, the findings highlight the struggles that international students have to navigate the basic needs in their new country, including accessing their health care plan, phone plans, and bank accounts. However, students found that the International Student Centre was supportive. When engaging with resources outside of the International Student Centre, like career services, academic advising, and navigating the health care system, participants found themselves unsupported and confused. This study concludes that additional training for staff and faculty outside of the International Student Centre is necessary as the number of international students continues to rise.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.044 | 0.017 |
| Scholarly communication | 0.014 | 0.003 |
| Open science | 0.004 | 0.013 |
| Research integrity | 0.003 | 0.010 |
| Insufficient payload (model declined to judge) | 0.006 | 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".