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Record W4391448832 · doi:10.1080/02673037.2024.2307595

Housing as a human right, rent supplements and the new Canada Housing Benefit

2024· article· en· W4391448832 on OpenAlexafffundabout
Catherine Leviten‐Reid, Megan Digou, Jacqueline Kennelly

Bibliographic record

VenueHousing Studies · 2024
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing, Finance, and Neoliberalism
Canadian institutionsCarleton UniversityCape Breton University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsBusinessHousing tenurePublic housingFair Housing ActRental housingSubdivisionAffordable housingLabour economicsEconomicsEconomic growthPublic economicsPolitical scienceRentingLawCivil engineeringEngineeringCivil rights

Abstract

fetched live from OpenAlex

Demand-side' approaches to housing affordability-including rent supplements and housing allowances-are used to address housing precarity in many countries.A core program of Canada's new National Housing Strategy is the Canada Housing Benefit (CHB), an allowance co-designed and co-funded by provinces and territories alongside the federal government.We explore the implementation of the CHB in one province (Nova Scotia) through the experiences of those receiving rental assistance and non-profit staff supporting them.First, we ask whether the provision of rent subsidies meets a rights-based approach to housing, focusing on affordability, habitability, and security of tenure.Second, we ask whether the transition from the former rent supplement system to the new CHB facilitates or inhibits a rights-based approach.We find that tenants on either subsidy live in housing which is unaffordable, of poor quality, and may lack security of tenure; secondly, the introduction of the new CHB has largely left tenants worse off than under the previous rent subsidy system.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.054
Threshold uncertainty score0.392

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.004
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.035
GPT teacher head0.261
Teacher spread0.226 · 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

Citations11
Published2024
Admission routes3
Has abstractyes

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