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Record W4402174270 · doi:10.1080/02673037.2024.2393661

Rental housing types and economic wellbeing in Canada

2024· article· en· W4402174270 on OpenAlexafffundabout
Xavier Leloup, Catherine Leviten‐Reid, Nazeem Muhajarine, Kristen Desjarlais-deKlerk, Laurence Simard

Bibliographic record

VenueHousing Studies · 2024
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing, Finance, and Neoliberalism
Canadian institutionsSaskatchewan HealthUniversity of WinnipegCape Breton UniversityInstitut National de la Recherche Scientifique
FundersCanadian Institutes of Health Research
KeywordsRental housingRentingEconomicsDemographic economicsLabour economicsSociologyPolitical science

Abstract

fetched live from OpenAlex

The aim of this article is to examine the association between different types of rental housing and household economic wellbeing. Its main objective is to better understand how the different types of assistance promoted by housing policies contribute to the reduction of material hardship among renter households. To achieve this objective, the study is based on the creation of an original typology designed to catch the different models of social and non-market housing that characterize the rental housing system in Canada. The research design it adopts controls for compositional effects linked to housing policy through a matching procedure that reduces the imbalance existing between households residing in social housing and the rest of the population. The analyses produced demonstrate the importance of promoting and maintaining social and non-market housing models that favour rent-geared-to-income housing, guarantee long-term affordability, and value public and co-operative tenure models.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.230

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.006
Science and technology studies0.0030.001
Scholarly communication0.0020.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.028
GPT teacher head0.233
Teacher spread0.205 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2024
Admission routes3
Has abstractyes

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