Falling between the Cracks: Ambiguities of International Student Status in Canada.
Bibliographic record
Abstract
As Canadian universities seek to attract more international students, there is a need to recognize and respond to the diversity within this group and to question the binary categories of domestic students and international students. Relying primarily on 116 qualitative interviews with international undergraduates at the University of British Columbia, we utilize American students as a case study from which to explore the complex and blurred boundaries between these two categories. Americans resemble domestic students in some respects and international students in others, yet they are often less prepared to meet adaptational challenges because they have low expectations of cultural and institutional differences. We compare the experiences of Americans and international students from other countries, as well as other groups of students who fall between the cracks of the domestic and international student classifications. We argue that, by targeting services on the basis of these broad administrative categories, categories that were created for financial purposes, the university reduces the take-up of the very services students need.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".