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Record W4399209590 · doi:10.18584/iipj.2024.15.1.14819

Leveraging culturally-relevant urban social housing to address Indigenous youth homelessness and transitions out of government care

2024· article· en· W4399209590 on OpenAlexaffvenueabout
Darrien Morton, Quinn Conlon, Quinton Delorme, Alex Pierce, Jacqueline Rieu, Rafael Terrain, Fearless R W, Andrew R. Hatala

Bibliographic record

VenueInternational Indigenous Policy Journal · 2024
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsUniversity of TorontoUniversity of Manitoba
Fundersnot available
KeywordsIndigenousGovernment (linguistics)SociologyPublic housingEconomic growthPolitical scienceSocioeconomicsEconomics

Abstract

fetched live from OpenAlex

Indigenous children and youth are overrepresented in settler-colonial child protection systems globally. They experience higher rates of homelessness and housing precarity when leaving care and searching for family and a place to call home. Missing from Canadian policy and research discussions is the role social housing can play to address these realities by providing a social safety net for permanent low-barrier housing. In this article, we highlight a community-based Solutions Lab that analyzed discursive policy constructions of ‘youth transition’ and explored the implications of austerity-driven social housing reform in a mid-sized metropolitan Canadian city. We illustrate potential challenges and opportunities for leveraging social housing by state governments and private markets which mediate housing precarity, belonging, and cultural conceptions of home.

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)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.656
Threshold uncertainty score0.692

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0130.011
Scholarly communication0.0050.002
Open science0.0020.011
Research integrity0.0010.002
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 head0.050
GPT teacher head0.398
Teacher spread0.348 · 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 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

Citations1
Published2024
Admission routes3
Has abstractyes

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