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Record W7002281180

MOVING HOUSE: URBAN ABORIGINAL HOUSING IN CANADA

2011· article· en· W7002281180 on OpenAlexaboutno aff

Bibliographic record

VenueScholarship@Western (Western University) · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicUrban, Neighborhood, and Segregation Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCensusProxy (statistics)Housing tenureDescriptive statisticsMetropolitan areaPublic housing
DOInot available

Abstract

fetched live from OpenAlex

Existing research shows that Aboriginal people in Canada have higher rates of mobility than the rest of the population. Mobility, along with rentalship have been linked to housing insecurity. Using the 2006 Canadian Census Data, descriptive statistics and regression analyses were run to investigate the differences in urban housing insecurity between Aboriginal and non-Aboriginal people in Canada. To look at urban housing insecurity, rentalship was used as a proxy as those who rent in Canada are more vulnerable to housing instability than those who own. Urban Aboriginal people were found to be more susceptible to housing insecurity than Non-Aboriginal people. Overall, Status Aboriginals were the most vulnerable to housing insecurity, followed by Non­ Status Aboriginals, Métis, and then with Non-Aboriginal people being the least vulnerable to housing insecurity. These findings are important as they show that certain groups experience housing insecurity differently, which should be considered to develop appropriate interventions.

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)0.000
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.140

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0060.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.111
GPT teacher head0.314
Teacher spread0.203 · 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

Citations0
Published2011
Admission routes1
Has abstractyes

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