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Record W4408954287 · doi:10.1080/08882746.2025.2484504

Students’ residential mobility during the COVID-19 pandemic: evidence from Québec, Canada

2025· article· en· W4408954287 on OpenAlexafffundabout
Nick Revington, Andrée-Anne Lefebvre, Amel Gherbi-Rahal, Christine T. O. Nguyen

Bibliographic record

VenueHousing and Society · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsInstitut National de la Recherche Scientifique
FundersMitacs
KeywordsCoronavirus disease 2019 (COVID-19)PandemicSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)2019-20 coronavirus outbreakGeographyVirologyMedicineOutbreakInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.039
GPT teacher head0.339
Teacher spread0.301 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes3
Has abstractyes

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