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Record W7125465289

Exploring rental housing affordability issues among international students in Halifax, Nova Scotia

2025· article· en· W7125465289 on OpenAlexaboutno aff
Bright Ofori Kwakye

Bibliographic record

VenueSaint Mary's University Institutional Repository (Saint Mary's University) · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicPlace Attachment and Urban Studies
Canadian institutionsnot available
Fundersnot available
KeywordsNova scotiaMetropolitan areaRentingCoping (psychology)Qualitative researchRental housingStudy abroad
DOInot available

Abstract

fetched live from OpenAlex

In Canada, research on international students’ experiences has largely focused on major metropolitan areas such as Toronto and Vancouver, with limited attention given to small and midsized cities like Halifax. This study examines international students’ experiences in the rental housing market in Halifax, Nova Scotia, and compares them with those of domestic students. Using a sequential explanatory mixed-methods approach, the study draws on 168 online surveys across three student groups—domestic students from Nova Scotia, domestic students from other provinces, and international students—and 11 in-depth interviews with international students. Guided by intersectionality, the findings reveal that international students experience a disproportionate burden of housing affordability challenges, intensified by intersecting identities such as race and nationality. International students employ coping strategies such as using online platforms and social networks to secure housing. The study calls for a coordinated response involving governments, post-secondary institutions and other stakeholders to address students’ housing needs.

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 categoriesMeta-epidemiology (narrow), Science 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 score0.414
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0000.002
Open science0.0010.001
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 head0.033
GPT teacher head0.274
Teacher spread0.241 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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