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Record W2331470019 · doi:10.5304/jafscd.2010.012.011

Assessing the pocket market model for growing the local food movement: A case study of Metropolitan Vancouver

2010· article· en· W2331470019 on OpenAlexafffundabout
Terri Evans, Christiana Miewald

Bibliographic record

VenueJournal of Agriculture Food Systems and Community Development · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicOrganic Food and Agriculture
Canadian institutionsSimon Fraser University
FundersSimon Fraser University
KeywordsMetropolitan areaBusinessMarketingPurchasingFood systemsOrder (exchange)Purchasing powerSustainabilityFresh foodFood securityEconomicsGeographyFinanceAgriculture

Abstract

fetched live from OpenAlex

In this study we explore the pocket market model, an emergent alternative retail marketing arrange­ment for connecting urban consumers with local food producers. In this model, community-based organizations act as local food brokers, purchasing fresh, healthful food from area farmers and food producers, and selling it to urban consumers in small-scale, portable, local food markets. The benefits of pocket markets are numerous. They include the provision of additional and more local­ized marketing outlets for local food producers; increased opportunities to educate consumers about local food and sustainable food systems; the convenience for consumers of having additional venues where local food is available for purchase; and an ability to increase access to fresh produce in areas with poor or limited retail food options. Despite these advantages, pocket market organiz­ers face many challenges in implementing this model successfully. These include a lack of public familiarity with the pocket market concept, an inability to address issues of food access in a way that is financially sustainable, and issues related to logistics, site selection, and regulatory requirements. In this paper, we will explore the pocket market model using those operating in metropolitan Vancouver (British Columbia, Canada) as an example, and assess the degree to which it addresses some of the current gaps in bringing local food to urban communities.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.755
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.031
GPT teacher head0.244
Teacher spread0.214 · 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.

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

Citations8
Published2010
Admission routes3
Has abstractyes

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