MétaCan
Menu
Back to cohort
Record W2619091333

Towards an Understanding of Aboriginal Regional Corporations: The Case of the Inuvialuit of the Western Arctic of Canada

2016· article· en· W2619091333 on OpenAlexaboutno aff
James C. Saku

Bibliographic record

VenueGeographical research forum/Geography research forum · 2016
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsCorporationArcticSettlement (finance)SubsidiaryGeographyHuman settlementEconomic geographyPolitical scienceRegional scienceEconomic growthBusinessEconomicsMultinational corporationArchaeologyEcology
DOInot available

Abstract

fetched live from OpenAlex

A new approach to economic development in northern Canadian Aboriginal communities emerged about three decades ago. Through the settlement of Modern Land Claim Agreements (MLCAs), Aboriginal corporations were created to address regional economic issues of Aboriginal people. With complex institutional structures, these corporations provide the opportunity for Aboriginal people to be involved in the management and decision-making process of their lands and communities. This paper examines the corporate structures created in the Western Arctic of Canada when the Inuvialuit Final Agreement (IFA) was achieved in 1984. In particular, the functions of the Inuvialuit Regional Corporation (IRC) and its subsidiaries in advancing regional economic development of the Inuvialuit are examined.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.129
Threshold uncertainty score0.935

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0300.023
Scholarly communication0.0140.003
Open science0.0030.004
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.166
GPT teacher head0.462
Teacher spread0.297 · 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 designQualitative
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
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueGeographical research forum/Geography research forumSame topicIndigenous Studies and EcologyFrench-language works237,207