MétaCan
Menu
Back to cohort
Record W2001291065 · doi:10.1080/14927713.2014.906172

Gardening in green space for environmental justice: food security, leisure and social capital

2013· article· en· W2001291065 on OpenAlexvenueno aff
Rob Porter, Heather McIlvaine-Newsad

Bibliographic record

VenueLeisure/Loisir · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicUrban Agriculture and Sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsRecreationFood securitySocial capitalContext (archaeology)SociologyEthnographyEconomic JusticeEconomic growthOrder (exchange)AgriculturePublic relationsBusinessPolitical scienceGeographySocial scienceEconomics

Abstract

fetched live from OpenAlex

This ethnography examines the origins and growth of a rural community garden in the context of food security, leisure and social capital within an environmental justice framework. Community residents, including low-income populations, people with disabilities and senior citizens, banded together with the assistance of local leaders in order to grow healthy produce based on concerns of produce cost and commercial growing practices. Results indicate that participants did enter into the garden activity mainly for food security, but soon realized leisure benefits such as socializing and meeting new people. Moreover, the external social networks that facilitated the gardens resulted in the creation of internal social capital, including increased gardening knowledge and shared ability. Finally, we discuss implications to community/recreation leaders in the context of building social networks in rural areas, creating access and bringing together diverse populations within a leisure-based community garden.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.004
Scholarly communication0.0020.002
Open science0.0000.003
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.010
GPT teacher head0.198
Teacher spread0.188 · 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 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

Citations24
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueLeisure/LoisirSame topicUrban Agriculture and SustainabilityFrench-language works237,207