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Record W1998030644 · doi:10.3197/096327110x485400

A Values-Based Framework for Community Food Choices

2010· article· en· W1998030644 on OpenAlexaffabout
Nicole Gregory, Robin Gregory

Bibliographic record

VenueEnvironmental Values · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicOrganic Food and Agriculture
Canadian institutionsDalhousie University
Fundersnot available
KeywordsCognitive reframingConsumption (sociology)Distribution (mathematics)Production (economics)Food consumptionFood policyEconomicsPublic economicsSociologyPolitical scienceMicroeconomicsPsychologySocial psychologySocial scienceFood securityGeographyAgricultural economicsMathematicsAgriculture

Abstract

fetched live from OpenAlex

This paper examines the definition and implementation of community-based alternative food systems (AFS), drawing on examples from British Columbia, Canada. We seek to reframe the goals of AFS by focusing on the values associated with food production, distribution and consumption strategies. We argue that current AFS thinking suffers from an over reliance on policies reflecting single rather than multiple objectives and arguments over specific alternatives ratherthan a values-focused debate. A decision-focused approach, using a consequence matrix, is proposed to link people's expressed values to food policy responses and clarify trade-offs across options. This reframing should encourage new dialogue, new policy alternatives, and increased acceptance of actions supporting AFS.

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)0.011
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.042
Threshold uncertainty score0.163

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.005
Science and technology studies0.0090.039
Scholarly communication0.0120.010
Open science0.0030.006
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0060.001

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 head0.018
GPT teacher head0.218
Teacher spread0.199 · 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 designTheoretical or conceptual
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

Citations9
Published2010
Admission routes2
Has abstractyes

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