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Record W1514746739

Yukon 2000: A Community-Based Planning Effort to Preserve “Things That Matter”

2001· article· en· W1514746739 on OpenAlexaboutno aff
Bryan T. Downes

Bibliographic record

VenueNorthern review · 2001
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRural development and sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsOutreachGovernment (linguistics)StakeholderDemocracyPlan (archaeology)Process (computing)Strategic planningQuality (philosophy)Political sciencePublic relationsEnvironmental planningPoliticsPublic administrationBusinessGeographyMarketingLawComputer science
DOInot available

Abstract

fetched live from OpenAlex

In the late 1980s, the Yukon’s New Democratic Party ( NDP ) government proved that an essentially community-based process could be used to plan the economic and environmental future of a vast sparsely populated region. The government was successful because the community-based approach was implemented systematically and comprehensively, with considerable effort invested in outreach to communities and citizens, before analyses began and recommendations emerged. The planning process used in the Yukon had two additional essential features: (1) it assumed that community needs had to be met if a quality strategy was to develop; and (2) it emphasized capacity building to increase local self-reliance and innovation. Communities and regions contemplating a decentralized approach to regional strategic planning, involving citizens extensively in the planning effort, can learn from the Yukon’s experience. However, areas with larger populations will have to be creative in developing means, such as those discussed in Weeks (2000) and Bryson and Anderson (2000), to assure widespread citizen and stakeholder involvement. One factor critical to the success of these efforts has been, and continues to be, the catalytic leadership of the Yukon’s Territorial government (Luke, 1998).

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.474
Threshold uncertainty score0.939

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 studies0.0000.000
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 head0.052
GPT teacher head0.275
Teacher spread0.223 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2001
Admission routes1
Has abstractyes

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