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Record W4403911408 · doi:10.1080/13549839.2024.2419580

Achieving an equitable circular food economy in Vancouver

2024· article· en· W4403911408 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueLocal Environment · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicOrganic Food and Agriculture
Canadian institutionsSimon Fraser University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsCircular economyFood insecurityBusinessEconomicsFood securityGeographyEcologyAgricultureBiology

Abstract

fetched live from OpenAlex

Food loss and waste occur at an alarming rate while many households in the City of Vancouver are food insecure. Set within the context of City of Vancouver’s Zero Waste 2040 long-term strategic plan, the City seeks to promote a circular economy, including through food waste reduction and prevention, better food redistribution, and partaking in awareness campaigns. Food rescue and redistribution is often framed as a win–win solution to avoid throwing unwanted, unmarketable, or surplus foods from the landfill and instead redistributing the food to those who are food insecure. This solution has been framed as a useful tool to promote a circular economy. However, both food waste and food studies scholars have rightly noted that connecting unwanted foods with those who are food insecure to address systemic hunger is not a panacea, nor is it a systemic solution to prevent food waste. Drawing on key informant interviews with agri-food experts across the system (n = 20), this study identified the challenges, opportunities, and the overall vision of the circular food economy and how it is mobilised in the City of Vancouver. It seeks to understand how equity factors into the vision of a circular food economy and its implementation by agri-food and relevant actors. The findings in this study highlight the importance of dynamic governance systems that targets critical points for change including regulation, funding, and capacity building to ensure a circular food economy that considers equity and justice.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.957
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.168
Teacher spread0.160 · 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