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Record W4392815719 · doi:10.29173/jaed291

Editor’s Introduction

2011· article· en· W4392815719 on OpenAlexaboutno aff
Robert Oppenheimer

Bibliographic record

VenueJournal of Aboriginal Economic Development · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

The State of the Aboriginal Economy is a section of this journal that examines different aspects of the environment that may contribute to the economic well-being of Aboriginal communities and individuals.It is not intended to provide an assessment of how well or poorly Aboriginals across Canada are doing economically.If such an examination was provided, we would likely find that there is an extremely broad range results being achieved.Some communities are doing very well, many are struggling and others are getting by.This section includes four papers that address issues relating to the economic well-being of Aboriginals.A common theme among these four papers is the opportunities for enhancing Aboriginal economies.Seaman, Robertson and Ford discuss, in broad terms, investment opportunities for Aboriginal communities.This is presented in ways that are consistent with Indigenous laws and traditions, while recognizing constraints imposed by the federal government.Four potential areas that provide investment opportunities for those communities in a position to do so are reviewed.These include the gaming industry, with a focus on Saskatchewan, energy generation, with a focus on Ontario, carbon offset projects, which is still evolving and commercial real estate.Bailie, Parungao, Ouellette and Russell report on opportunities within the forestry sector.This includes the finding that Aboriginal communities have increased the amount of forestry under their management.Further, there has been a significant increase in the total median income for off-reserve Aboriginal men working in forestry.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.955
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.285
Teacher spread0.273 · 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 designNot applicable
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

Citations0
Published2011
Admission routes1
Has abstractyes

Explore more

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