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Evidence of Degrowth Values in Food Justice in a Northern Canadian Municipality

2021· article· en· W3165762407 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEnvironmental Values · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicOrganic Food and Agriculture
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsDegrowthContext (archaeology)SustainabilityConsumption (sociology)Economic JusticePsychological resilienceSociologyEconomicsSocial scienceEcologyBiologyNeoclassical economics

Abstract

fetched live from OpenAlex

Our case study draws on emerging ideas of degrowth, showing how degrowth values and strategies may emerge where cities rely heavily on global food systems, and contributes to literature on food for degrowth in local contexts. Degrowth rejects the imperative of economic growth as a primary indicator of social wellness. A holistic understanding of wellness prescribes radical societal transformation, downscaling and decreasing consumption, strengthening community relationships and promoting resilience. Building on Bloemmen et al. (2015), we apply a holistic model of degrowth in a small-scale context, embedded within larger capitalist economies, to examine degrowth opportunities and constraints in Edmonton, Canada. Emergent themes in interviews reveal opportunities and challenges for local food for degrowth, by altering local food supplies, reducing food waste and decreasing consumption. We explore the role of social relationships in food justice work, increasing food knowledge, and building capacity for local, sustainable food production.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.662
Threshold uncertainty score0.983

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)0.0000.000

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 head0.030
GPT teacher head0.211
Teacher spread0.181 · 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