Navigating the housing crisis: A comparison of international students and other newcomers in a mid‐sized Canadian city
Bibliographic record
Abstract
Abstract This article investigates the housing experiences of international students in comparison to other newcomers in the mid‐sized Canadian city of St. John's, Newfoundland and Labrador, with a focus on how they navigate housing crises. Drawing on recent literature on housing justice, a quantitative survey of 188 participants, and 30 qualitative interviews, the findings reveal that international students and other newcomers are at different stages of their housing careers, have different needs and goals, and are experiencing the affordability crisis differently. Housing discrimination is a pressing concern, especially for international students who are subjected to intersectional prejudice, exploitation by landlords, and amplified challenges due to the COVID‐19 pandemic. The article argues for inclusive housing and immigration policies that acknowledge international students as part of the Canadian housing market and ensure their rights to housing .
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".