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Record W4310090928 · doi:10.22584/nr53.2022.008

Participation in the Traditional Economy in Northern Saskatchewan: The 21st Century Landscape

2022· article· en· W4310090928 on OpenAlexaffvenueabout
Bonita Beatty, Stan Yu

Bibliographic record

VenueThe Northern Review · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Sciences and Governance
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsIndigenousLivelihoodFishingGovernment (linguistics)Traditional knowledgeEconomyPsychological resilienceEconomic growthGeographyPolitical scienceAgricultureEconomicsEcologyArchaeologyLaw

Abstract

fetched live from OpenAlex

This article discusses the resilience of the northern traditional economy. In northern Saskatchewan mitho-pimachesowin speaks to the freedom and capacity to make a good living. For northern Indigenous People, this includes participation in the traditional economy that reflects their culture, identity, and way of life. Most still blend their land-based livelihood activities (harvesting, trapping, commercial fishing) and other forms of revenue income to support their families and communities. This blended approach is an example of sustainable development that works, and it should be supported by all levels of government with strategic approaches and investments. This article is a chapter in the open textbook Indigenous Self-Determination through Mitho Pimachesowin (Ability to Make a Good Living), developed for the University of Saskatchewan course Indigenous Studies 410/810 and hosted by the Northern Review.

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)0.001
metaresearch head score (Gemma)0.001
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: none
Teacher disagreement score0.210
Threshold uncertainty score0.423

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.006
Science and technology studies0.0030.004
Scholarly communication0.0040.002
Open science0.0010.003
Research integrity0.0010.001
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 head0.047
GPT teacher head0.305
Teacher spread0.259 · 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

Citations0
Published2022
Admission routes3
Has abstractyes

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