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Record W4392815963 · doi:10.29173/jaed346

An Analysis of Aboriginal Employment: 2009–2013

2014· article· en· W4392815963 on OpenAlexaffabout
Robert Oppenheimer

Bibliographic record

VenueJournal of Aboriginal Economic Development · 2014
Typearticle
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsConcordia University
Fundersnot available
KeywordsUnemploymentUnemployment rateGeographyDemographic economicsDemographyEconomicsSociologyEconomic growth

Abstract

fetched live from OpenAlex

The employment, unemployment and participation rates are examined for Aboriginals living off-reserve in Canada from 2009 to 2013 as well as for non-Aboriginals. Employment is analyzed by educational level, gender and age, province and territory and by industry and sector. The rates of employment and unemployment for Aboriginals have continued to improve, lessening the differences with non-Aboriginals. Those in the 15 to 24 age group and women had the largest improvements in their employment and unemployment rates in 2013. The level of education obtained is directly related to the rate of employment for Aboriginals and non-Aboriginals and explains most of the difference in their rate of employment, but does not explain the differences in unemployment rates. The highest rate of employment for Aboriginals and non-Aboriginals is in Alberta. The areas in which the highest percent of those employed are in health care and social assistance followed by retail trade.

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)0.001
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 score0.031
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.005
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.005
GPT teacher head0.237
Teacher spread0.232 · 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

Citations1
Published2014
Admission routes2
Has abstractyes

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