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Record W2247310672 · doi:10.25916/sut.26278456

Overview of Aboriginal communities and economic partner agreements in northern Canada

2006· other· en· W2247310672 on OpenAlexaboutno aff
Richard Missens, Léo‐Paul Dana

Bibliographic record

VenueSwinburne Research Bank (Swinburne University of Technology) · 2006
Typeother
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceGeographyBusiness

Abstract

fetched live from OpenAlex

Natural resources are a cornerstone of Canada's economy. Today, natural resources industries support more than 650 communities and accounts for 12% of Canada's Gross Domestic Product (Industry Canada). The Canadian diamond industry in 2004 accounted for 4% of the total expenditures on mining and processing and is poised for significant growth and contribution to the economy of Canada. This emerging industry has created a unique opportunity for Canada's northern Aboriginal people. In negotiation with the diamond companies the Aboriginal 1 communities have provided their consent for the diamond mines and have ensured their participation in all diamond projects within their traditional territories. Five Aboriginal communities have signed partnership agreements with Diavik Diamond Mines Inc. providing joint control of training, employment and business opportunities. This paper will discuss the commitments, and the progress, made by Diavik in the participation agreements with the First Nation and Aboriginal signatories.

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)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.071
Threshold uncertainty score0.513

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.012
Science and technology studies0.0220.002
Scholarly communication0.0070.002
Open science0.0020.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0160.001

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 head0.021
GPT teacher head0.257
Teacher spread0.236 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2006
Admission routes1
Has abstractyes

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