MétaCan
Menu
Back to cohort
Record W2099711229 · doi:10.7202/1015492ar

Taking Space to Grow Food and Community: Urban Agriculture and Guerrilla Gardening in Vancouver

2013· article· en· W2099711229 on OpenAlexvenueaboutno aff
Rachel E. Black

Bibliographic record

VenueCuizine The Journal of Canadian Food Cultures · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicUrban Agriculture and Sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsBeautificationUrban agricultureGrassrootsMainstreamCitizen journalismAgriculturePublic spaceUrbanismNegotiationGeographyPolitical scienceEnvironmental planningSociologyEconomic growthPoliticsCivil engineeringSocial scienceEngineeringArchitectural engineering

Abstract

fetched live from OpenAlex

City planners and citizens often see gardens as spaces for urban beautification projects. However, urban agriculture and growing food in cities is becoming an increasingly accepted use of public green spaces. This article examines how gardeners and the City of Vancouver negotiate space while trying to create green cities, greater awareness of food security issues, and community in urban environments. These gardens show how local discourses of health, environment, and food production are created through this process of appropriating urban spaces for horticultural activities. Based on ethnographic fieldwork, this paper explores the development of spontaneous and grassroots urban agriculture movements in Vancouver. This research was carried out from 2006 to 2008 while the city was preparing for the 2010 Winter Olympic Games. At this time, Vancouverites, local officials, and Games organizers were concerned about putting on a “green” Games. As the media spotlight began to fall on Vancouver, urban agriculture became a very public demonstration of the city’s environmental awareness. This article looks at how, at a particular historic moment, grassroots gardening movements gained mainstream acceptance and played a role in constructing the city’s image as an environmentally aware urban place with a high standard of living.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.790
Threshold uncertainty score0.956

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.014
GPT teacher head0.191
Teacher spread0.177 · 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 designNot applicable
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

Citations6
Published2013
Admission routes2
Has abstractyes

Explore more

Same venueCuizine The Journal of Canadian Food CulturesSame topicUrban Agriculture and SustainabilityFrench-language works237,207