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Record W2036650196 · doi:10.1080/13549830701803315

Closing the implementation gap: a framework for incorporating the context of place in economic development planning

2008· article· en· W2036650196 on OpenAlexafffundabout
Sean Markey, Greg Halseth, Don Manson

Bibliographic record

VenueLocal Environment · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRural development and sustainability
Canadian institutionsUniversity of Northern British ColumbiaSimon Fraser University
FundersWestern Economic Diversification CanadaMcKnight Foundation
KeywordsRestructuringClosing (real estate)Context (archaeology)SustainabilityPoliticsEconomic restructuringPolitical scienceSustainable developmentAction (physics)Economic transformationSocial changeEconomic growthEconomicsEconomic systemGeography

Abstract

fetched live from OpenAlex

Since the early 1980s, rural and small-town Canada has experienced considerable transformation from social, economic, and political restructuring. These changes put pressure on communities and regions to assume increasing levels of responsibility for economic planning and development. The record to date, however, reveals implementation gaps between plans and the results on the ground. This paper explores this implementation gap using a case study from northwestern British Columbia, Canada. The findings indicate that a failure to incorporate the context of place in the analysis of economic strategy reports results in flawed local and regional development processes and misdirected action plans. This research is set within a broader revival in the regional development literature, where an interest in regions is accompanied by enquiry into the ability of local action to influence economic development planning and longer-term community sustainability.

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)0.060
metaresearch head score (Gemma)0.047
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.060
Threshold uncertainty score0.319

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0600.047
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0090.007
Science and technology studies0.0140.104
Scholarly communication0.0210.029
Open science0.0080.020
Research integrity0.0090.012
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 head0.028
GPT teacher head0.247
Teacher spread0.219 · 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 designTheoretical or conceptual
Domainnot available
GenreMethods

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

Citations22
Published2008
Admission routes3
Has abstractyes

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