We Want Them, but We Will Not Support Them: A Comparative Study of Settlement Services Provided to International Students in the USA and Canada
Bibliographic record
Abstract
In recent years, the number of international student’s to the USA has plateaued, with many International Students now choosing to migrate to Canada instead. Arguably, for its world-renounced education from leading post-secondary institutions, as well as possible pathways to Canadian citizenship. The Canadian government has also been quick to recognize the lucrative contributions of international students to the Canadian economy, even expanding immigration policies to create express pathways to citizenship for international students. Despite this, emerging research shows that international students find it difficult to adopt during their time in North America, and face challenges that can potentially hinder their long-term retention in Canada (Chevrier, 2019). Thus, using a comparative and integrative literature review, this research study assesses the structure of settlement service delivery, and current gaps that hinder the delivery of comprehensive settlement programs for international students in the USA and Canada. The findings of this review show that the American and Canadian governments have not taken an active role in supporting international students, and instead downloaded the responsibility of settlement service delivery to post-secondary institutions. Furthermore, privatization of services in America has been somewhat successful, while in Canada it has been largely unsuccessful. The implications of these research findings is that, if Canada wants to continue to retain its ISs population, it must ensure it is doing its part to support the short, and long-term resettlement and integration of international students into Canadian society.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.010 |
| Science and technology studies | 0.010 | 0.004 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".