Students’ residential mobility during the COVID-19 pandemic: evidence from Québec, Canada
Bibliographic record
Abstract
Many students face considerable housing precarity given their frequent moves, short-term stays in their city of study, and limited incomes, which may make them more susceptible to pandemic-related housing disruptions. As universities transitioned to online teaching during the COVID-19 pandemic, many temporarily returned to the parental home, while for others, the departure of roommates or loss of income may have left them unable to pay rent on their own. The need for better Wi-Fi and working space at home may also have prompted students to move. We investigate how the pandemic affected students’ residential moves in the province of Québec, how these impacts differ between students, and the reasons for – and outcomes of – these moves, drawing on a survey of students’ demographic and housing characteristics undertaken in 2021. We find that non-male respondents and non-Québec residents were more likely to effectuate pandemic-related moves, and that moves were also associated with financial precarity. Mental health concerns were an overriding reason for moving, followed by physical wellness. Some, but not all, outcomes of moves differed by gender, race, and students’ geographic origin. As underlying vulnerabilities persist, these findings suggest better supports are needed to ensure satisfactory, affordable housing for students.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.008 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".