MétaCan
Menu
Back to cohort
Record W2344000616 · doi:10.1504/ier.2016.076141

Identifying opportunities and hurdles for food security: a critical examination of the City of Edmonton's food and agriculture strategy

2016· article· en· W2344000616 on OpenAlexaffabout
Lorelei L. Hanson, Deborah Schrader

Bibliographic record

VenueInterdisciplinary Environmental Review · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicUrban Agriculture and Sustainability
Canadian institutionsUniversity of AlbertaAthabasca University
Fundersnot available
KeywordsTransformative learningFood securityFood systemsStatus quoLeverage (statistics)AgricultureSustainabilitySustainable agricultureUrban agricultureBusinessEconomic growthPolitical scienceSociologyEconomicsGeography

Abstract

fetched live from OpenAlex

Local food has emerged as a popular social movement across much of the developed world. While many are quick to see it as a challenge to the dominant agri-food system, some critical social scientists caution against assuming its transformative potential. Using a case study of the development of a food and urban agriculture strategy in Edmonton, Canada, we explore both the transformative potential of local urban food initiatives and the hurdles faced in trying to move beyond maintaining the status quo. Utilising survey data and semi-structured interviews, we examine how citizens and stakeholders conceptualise sustainability and a more sustainable food system emerging in Edmonton, and identify the leverage points within these imaginings for long-term local food system transformation.

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)0.007
metaresearch head score (Gemma)0.005
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 score0.120
Threshold uncertainty score0.622

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.006
Science and technology studies0.0150.011
Scholarly communication0.0120.003
Open science0.0030.005
Research integrity0.0030.003
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 head0.042
GPT teacher head0.266
Teacher spread0.223 · 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

Citations0
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueInterdisciplinary Environmental ReviewSame topicUrban Agriculture and SustainabilityFrench-language works237,207