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Record W2252647366

Labour Market Prospects for the Métis in the Canadian Mining Industry

2013· preprint· en· W2252647366 on OpenAlexaboutno aff
Evan Capeluck, Andrew Sharpe

Bibliographic record

VenueRePEc: Research Papers in Economics · 2013
Typepreprint
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsnot available
Fundersnot available
KeywordsMetisMining industryBusinessPopulationWork (physics)Economic growthEconomicsEngineering
DOInot available

Abstract

fetched live from OpenAlex

The objective of this report is to review the prospects for Métis employment in the mining industry brought upon by a looming wave of retirements; to determine potential barriers to Métis employment in the mining industry; and to identify actions and strategies that the Métis National Council (MNC) and Métis Aboriginal Skills and Employment Training Strategy (ASETS) agreement holders should adopt to take advantage of and overcome obstacles to employment opportunities in the mining industry. The Canadian mining industry accounted for somewhere between two and five per cent of nominal GDP in Canada – depending on which definition of the mining industry is used – in 2008. This industry, concentrated in rural and remote locations, represents an important potential source of employment for the comparatively large youthful and rural Métis population entering the labour market in the coming decades. The mining industry has unique locational dynamics and hiring practices, a highly productive and experienced but aging work force, and growth prospects that are heavily reliant on global demand. Skilled workers are needed to replace the mining industry’s soon-to-be-retired baby boomers and to replace other workers leaving the industry. The Métis have unique demographic

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.567
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.003
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 head0.027
GPT teacher head0.267
Teacher spread0.240 · 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 designSimulation or modeling
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

Citations2
Published2013
Admission routes1
Has abstractyes

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