Studying in a new home; geographies of international student housing at \nMemorial University of Newfoundland and Labrador
Bibliographic record
Abstract
International students are vital to Canada’s economy and immigration systems, with their contributions surpassing $21 billion annually. Despite their significant economic and immigration impacts, they face housing insecurity, a lack of affordable options, and exclusion from government-funded settlement services. Limited research exists on their experiences outside major metropolitan areas, posing challenges for smaller urban centres like St. John’s and Corner Brook. My research aims to address this gap by examining MUNL international students’ housing experiences and their perceptions of (un)welcoming communities amidst the COVID-19 pandemic. Grounded in concepts of international student mobility, geographies of student housing, and welcoming communities, this study incorporates a mixed methodology, involving interviews, a photovoice study, and a survey. The findings highlighted significant housing challenges faced by MUNL international students, exacerbated by the impacts of COVID-19 pandemic as well as mobility challenges due to the pandemic’s travel restrictions. Results also revealed a generally welcoming atmosphere in NL communities, with student participants describing friendly interactions and a sense of neighbourhood but expressed their incomplete sense of being at-home. Thus, this thesis calls for comprehensive solutions to address the housing needs of international students in NL while contributing to broader discussions on immigration and 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 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".