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Immigration, Housing, and Health

2025· reference-entry· en· W4409408275 on OpenAlexaffabout
Caris Towle, K. Bruce Newbold

Bibliographic record

VenueOxford Research Encyclopedia of Global Public Health · 2025
Typereference-entry
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsImmigrationBusinessPolitical scienceLaw

Abstract

fetched live from OpenAlex

Abstract Immigration, housing, and health are linked, as the Canadian experience illustrates. Refugees and asylees are more vulnerable relative to other immigrant arrivals who can draw upon financial resources or family and social networks to support their housing. Refugees and asylees, by comparison, experience poorer health, poorer health outcomes, and poorer housing opportunities, given their experiences as refugees and weaker economic and social connections. The nexus of the immigration, housing, and health literature indicates that the housing situation affects both physical and psychological health. Moreover, it is not a unidirectional relationship: Poor housing is reflective of poor health status, and poor health status often results in poor housing. Poor housing is also associated with food insecurity, which is more common among low-income households with children and those that are dependent on social welfare programs as a source of income. Refugees and asylees are ultimately more likely to experience poor housing outcomes that further exacerbate poor health.

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)0.011
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.768
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.002
Science and technology studies0.0030.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.003
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 head0.163
GPT teacher head0.495
Teacher spread0.332 · 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 designNot applicable
Domainnot available
GenreReview

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 routes2
Has abstractyes

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