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Record W2901799522 · doi:10.36939/cjur/vol26no2/art92

A Place to Stand on Your Own Two Feet: The Role of Community Housing in Immigrant Integration in Montréal, Quebec

2017· article· en· W2901799522 on OpenAlexaffvenueabout
Raphaël Fischler, Lindsay K. Wiginton, Sarah Kraemer

Bibliographic record

VenueCanadian journal of urban research · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicFrench Urban and Social Studies
Canadian institutionsPembina InstituteMcGill University
Fundersnot available
KeywordsMetropolitan areaImmigrationPublic housingSocial integrationCommunity integrationDistribution (mathematics)Quality (philosophy)Order (exchange)Economic growthSociologyPolitical scienceBusinessGeographyEconomics

Abstract

fetched live from OpenAlex

Research on the housing conditions of immigrant households has tended to focus on their spatial distribution in metropolitan areas, the discrimination they face in the search for housing, and their housing trajectories, in particular their access to homeownership. Little research has been done on what role, if any, housing plays in their integration in their host society. This research tests the hypothesis that community housing, in which tenants participate actively in the management of their buildings, gives immigrants social contacts and skills that help in their integration. The authors conducted interviews and focus groups with renters, homeowners and housing specialists in order to understand better what respondents understand by “integration” and to investigate the possible causal relationship between life in community housing and social integration. The findings both support and contradict the original hypothesis and are the basis for recommendations for community housing developers. The most important lesson to be drawn from the research is that participation in in-house activities in community housing are not necessarily a positive factor in social integration—it may actually be perceived negatively by some immigrants—and are clearly secondary to questions of housing quality and affordability.

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)0.008
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.391
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.133
GPT teacher head0.379
Teacher spread0.246 · 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 designQualitative
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

Citations2
Published2017
Admission routes3
Has abstractyes

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