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Record W2333080697 · doi:10.15353/cfs-rcea.v3i1.144

Constituting community through food charters: A rhetorical-genre analysis

2016· article· en· W2333080697 on OpenAlexaffvenueabout
Philippa Spoel, Colleen Derkatch

Bibliographic record

VenueCanadian Food Studies / La Revue canadienne des études sur l alimentation · 2016
Typearticle
Languageen
FieldHealth Professions
TopicFood Security and Health in Diverse Populations
Canadian institutionsToronto Metropolitan UniversityLaurentian University
Fundersnot available
KeywordsRhetorical questionCharterAction (physics)SociologyIdeologyFood systemsFood securityIdentity (music)Listing (finance)Political scienceLawAestheticsHistoryPoliticsBusinessAgricultureArtLiterature

Abstract

fetched live from OpenAlex

Communities across Canada are increasingly developing food charters, with at least 22 regional charters published in Ontario alone. As a rhetorical genre, food charters are persuasive actions that articulate not only the kind of food system to which a community aspires, but also the kind of community that it aspires to be. We argue that Ontario’s food charters play an important role in constituting a sense of community identity and values through the rhetorical action of the genre itself. We analyze how this is accomplished through two rhetorical features, the naming of community and the listing of community priorities, showing how these features simultaneously obscure and reveal ideological tensions and logical incongruities within each community’s vision for its food system. Our analysis illustrates how the genre of the food charter both responds to and shapes the diverse, possibly conflicting values that inform food policy and food security initiatives in Ontario, and it offers insight into how the genre itself may inadvertently constrain the action it is intended to perform.

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 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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.704
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0050.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.375
GPT teacher head0.422
Teacher spread0.047 · 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 teacher head, not a consensus.

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

Citations9
Published2016
Admission routes3
Has abstractyes

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