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Record W2126431236 · doi:10.1068/a41314

Indigenous-Inclusive Citizenship: The City and Social Housing in Canada, New Zealand, and Australia

2010· article· en· W2126431236 on OpenAlexaffabout
Ryan Walker, Manuhuia Barcham

Bibliographic record

VenueEnvironment and Planning A Economy and Space · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsUniversity of Saskatchewan
FundersUniversity of Pittsburgh
KeywordsIndigenousCitizenshipGovernment (linguistics)AutonomyPublic housingEconomic growthPolitical scienceSocial citizenshipIndigenous rightsGeographyPolitics

Abstract

fetched live from OpenAlex

Indigenous peoples in Canada, New Zealand, and Australia are highly urbanised. In spite of this, urban Indigenous communities have a difficult time giving effect to self-determining autonomy in comparison with their rural, remote, and reserve counterpart communities. The place of authentic Indigeneity in the public perception has remained outside of urban areas. All three countries have had social housing initiatives that aim to even out life-chances among citizens. How Indigeneity features in the housing sector varies from country to country. Through an examination of social housing developments from the 1930s to the present, we develop knowledge of how the place of authentic Indigeneity has changed over time and has been linked to the creation of Indigenous-inclusive citizenship in the city. While the Canadian experience continues to pair self-government with common social housing goals, New Zealand never really linked self-government with common social citizenship in the housing sector; Australia did for a time, but it is regressing quickly.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.067
Threshold uncertainty score0.487

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.004
Science and technology studies0.0210.009
Scholarly communication0.0050.002
Open science0.0010.006
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 head0.016
GPT teacher head0.253
Teacher spread0.237 · 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

Citations51
Published2010
Admission routes2
Has abstractyes

Explore more

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