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Record W1504088674

Aboriginal Conditions in Census Metropolitan Areas, 1981-2001

2001· preprint· en· W1504088674 on OpenAlexaffabout
Andrew J. Siggner, Rosalinda Costa

Bibliographic record

VenueRePEc: Research Papers in Economics · 2001
Typepreprint
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsStatistics Canada
Fundersnot available
KeywordsMetropolitan areaCensusMetisGeographyPopulationSocioeconomicsDemographySociologyArchaeology
DOInot available

Abstract

fetched live from OpenAlex

This report examines the demographic and socio-economic characteristics of the Aboriginal population living in 11 metropolitan centres in 1981 and 2001. It studies the size, age and mobility of the population; the family structure of Aboriginal people; school participation and educational attainment; and the labour market characteristics and transfer dependence of Aboriginal people. It finds that Aboriginal people living in the nation's largest metropolitan centres were faring better overall in 2001 than they were two decades earlier. Nevertheless, these Aboriginal urban dwellers still faced many challenges, especially those in living in urban centres in the western provinces, where large gaps remained with their non-Aboriginal counterparts. The report examines the Aboriginal identity population, which refers to those persons who identified with at least one Aboriginal group, that is, North American Indian, Metis or Inuit. The concept of identity allows for historical comparability with the concept used in the 1981 Census to discuss changes over time. Data came from the censuses of 1981, 1996 and 2001, as well as the 2001 Aboriginal Peoples Survey. The metropolitan areas examined include Montreal, Ottawa-Hull (now known as Ottawa-Gatineau), Toronto, Sudbury, Thunder Bay, Winnipeg, Regina, Saskatoon, Calgary, Edmonton and Vancouver.

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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.487
Threshold uncertainty score0.981

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.038
GPT teacher head0.402
Teacher spread0.365 · 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

Citations27
Published2001
Admission routes2
Has abstractyes

Explore more

Same venueRePEc: Research Papers in EconomicsSame topicIndigenous Health, Education, and RightsFrench-language works237,207