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Record W2167329224 · doi:10.14430/arctic711

Sustainable Development for Canada's Arctic and Subarctic Communities: A Backcasting Approach to Churchill, Manitoba

2002· article· en· W2167329224 on OpenAlexafffundvenueabout
Steven Newton, Helen Fast, Thomas Henley

Bibliographic record

VenueARCTIC · 2002
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsUniversity of ManitobaFisheries and Oceans Canada
FundersChurchill Northern Studies Centre
KeywordsBackcastingSubarctic climateArcticSustainable developmentGeographyTourismEnvironmental planningCommunity developmentBayEnvironmental resource managementSustainabilityPolitical scienceEcologyEnvironmental scienceArchaeology

Abstract

fetched live from OpenAlex

Backcasting has been used to evaluate sustainable development in several communities in Canada, Europe, and the United States, but no research has applied it to a remote northern community. This first such effort, which took place in Churchill, Manitoba, evaluated the environmental, social, and economic aspects of a small Subarctic community. As part of the backcasting approach, a community survey identified local issues and concerns, such as tundra vehicle damage, alcohol abuse, and the future economic viability of the Hudson Bay Port Company. Community residents also identified potential growth areas, including the establishment of Nunavut and increased tourism opportunities. The application of the backcasting approach in Canada's northern regions will have benefits for research and management by identifying local issues and building strategies for sustainable development.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.076
Threshold uncertainty score0.553

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0130.002
Scholarly communication0.0040.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.060
GPT teacher head0.295
Teacher spread0.234 · 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

Citations21
Published2002
Admission routes4
Has abstractyes

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