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Record W2016958580 · doi:10.3112/erdkunde.2009.01.05

Development corporations in the Canadian north – examples for economic grassroots initiatives among the Inuit

2009· article· en· W2016958580 on OpenAlexaboutno aff
Gerlis Fugmann

Bibliographic record

VenueErdkunde · 2009
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsGrassrootsEconomic growthGeographyPolitical scienceEnvironmental planningEconomicsPolitics

Abstract

fetched live from OpenAlex

Starting with the James Bay and Northern Quebec Agreement of 1975 until the Nunavik Inuit Land Claim Agreement of 2006, the Inuit in Canada have negotiated some of the most extensive land claim agreements found in the Arctic region, opening up a variety of development opportunities for the beneficiaries of these regional agreements. One of the central purposes of these modern land claim agreements is to create an economic base and to promote economic self-reliance for the Inuit beneficiaries. As part of a local grassroots economic development movement that can be witnessed in these regions, development corporation were created starting in the 1970s with the mandate to invest capital into busi nesses and economic projects to create jobs and income for the local Inuit population. This paper will look at the efforts of two particular development corporations: the Makivik Corporation in Nunavik (Northern Quebec) and the Labrador Inuit Development Corporation (LIDC) in Nunatsiavut (Northern Labrador).

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)0.002
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score0.409

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0380.008
Scholarly communication0.0060.002
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.083
GPT teacher head0.357
Teacher spread0.274 · 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

Citations4
Published2009
Admission routes1
Has abstractyes

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