MétaCan
Menu
Back to cohort
Record W2116829636 · doi:10.3763/ijas.2009.0454

Putting the culture back into agriculture: civic engagement, community and the celebration of local food

2010· article· en· W2116829636 on OpenAlexaffabout
Jennifer Sumner, Heather Mair, Erin Nelson

Bibliographic record

VenueInternational Journal of Agricultural Sustainability · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicUrban Agriculture and Sustainability
Canadian institutionsUniversity of GuelphUniversity of WaterlooUniversity of Toronto
Fundersnot available
KeywordsAgricultureUrban agricultureFood systemsSustainable agricultureSustainable Agriculture Innovation NetworkSociologySustainabilityCivic engagementBusinessPolitical scienceMarketingGeographyFood securityEcology

Abstract

fetched live from OpenAlex

This paper reports on the case study of a community-supported agriculture (CSA) farm in south-western Ontario, Canada. As an exemplar of urban agriculture, Fourfold Farm CSA operates from an alternative agriculture paradigm and is built upon the socio-ecological practices of civic engagement, community and the celebration of local food. Analysis of in-depth, key informant interviews with members of the CSA as well as the co-founders reveals the extent to which the farm is much more than a source of healthy, organic food. The paper outlines the ways the CSA operators and their members articulate a deeper endeavour to link urban food consumers with food producers through cultural activities. The discussion concludes with a call for more social research in agriculture as well as a broader effort to articulate the ways urban agriculture can contribute to putting the culture back into agriculture and creating sustainable systems of farming.

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)0.002
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.322
Threshold uncertainty score0.641

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0190.025
Scholarly communication0.0070.002
Open science0.0010.007
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.008
GPT teacher head0.223
Teacher spread0.216 · 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

Citations75
Published2010
Admission routes2
Has abstractyes

Explore more

Same venueInternational Journal of Agricultural SustainabilitySame topicUrban Agriculture and SustainabilityFrench-language works237,207