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Ten questions concerning First Nations on-reserve housing in Canada

2024· article· en· W4394876301 on OpenAlexafffundabout
Joonsoo Sean Lyeo, Michael D. Wong, Natalie Clyke, Becky Big Canoe, Penny Kinnear, Helen Stopps, Nicholas D. Spence, Sarah R. Haines

Bibliographic record

VenueBuilding and Environment · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsHudbay Minerals (Canada)Toronto Metropolitan UniversityAssembly of First NationsPublic Health OntarioUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of CanadaFaculty of Engineering and Architectural Science, Ryerson UniversityConnaught FundUniversity of Toronto
KeywordsGeographyEnvironmental planning

Abstract

fetched live from OpenAlex

Indigenous Peoples are the original inhabitants of Canada and are made up of three distinct groups: First Nations, Métis and Inuit. About 40% of First Nations people with Registered or Treaty Indian status live on-reserve. Relative to the general Canadian population, First Nations living on-reserve are more likely to live in inadequate housing conditions that include significantly higher rates of mold growth and overcrowding, as well as a significant amount of existing housing stock in need of major repairs. Efforts to improve on-reserve housing conditions must be understood in the context of colonial policies, which have systematically prevented First Nations from obtaining safe, secure, and sustainable housing. This paper aims to evaluate the range of challenges, concerns, and innovative solutions for First Nations on-reserve housing. Ten questions and answers have been presented to characterize the current state of First Nations on-reserve housing in relation to the rest of the Canadian housing stock, including an in-depth comparison of the differences between on-reserve and off-reserve housing. Various known causes of challenges resulting in adequate on-reserve housing are discussed, as well as a review of various operational and construction-related challenges facing on-reserve housing, such as community remoteness, a lack of available skilled trades, and mold and moisture issues. Human health and wellbeing are also discussed as a key outcome of poor housing quality, looking at both physical and mental health in communities, with special attention to IAQ problems as a result of overcrowding and mold accumulation.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.988
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.017
GPT teacher head0.272
Teacher spread0.254 · 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
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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