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Record W2270712509

Food Clusters, Rural Development and Creative Economy

2015· article· en· W2270712509 on OpenAlexaffvenueabout
Anne Lee, Geoffrey Wall

Bibliographic record

VenueJournal of rural and community development · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEntrepreneurship Studies and Influences
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsNexus (standard)Creative economyConceptual frameworkFood processingCluster (spacecraft)Process (computing)BusinessConsumption (sociology)Conceptual modelEconomic geographyEconomic growthMarketingRegional scienceCreativityEconomicsPolitical scienceComputer scienceGeographySociology
DOInot available

Abstract

fetched live from OpenAlex

This paper presents a conceptual framework that outlines the formation of a food cluster as part of creative rural development, transforming the 'comparative advantages' of a place into 'competitive advantages' by enhancing a local food production and consumption nexus. A conceptual framework is proposed that emphasizes four facilitators that constitute the innovation process that underpins the creation and operation of food clusters as place-based rural development. The framework is used to guide information acquisition, analysis and presentation in a case study of SAVOUR Muskoka, a food cluster in Ontario, Canada. Together, the framework and case study show how the innovation process involved in the formation of a food cluster contribute to the rural development of a creative food economy.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.488
Threshold uncertainty score0.476

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 studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.040
GPT teacher head0.234
Teacher spread0.194 · 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

Citations3
Published2015
Admission routes3
Has abstractyes

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