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Record W4200220346 · doi:10.15353/cfs-rcea.v8i4.460

Eating and learning about food at school and on campus:

2021· article· en· W4200220346 on OpenAlexvenueaboutno aff
Estevan Leopoldo de Freitas Coca

Bibliographic record

VenueCanadian Food Studies / La Revue canadienne des études sur l alimentation · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicDiverse Educational Innovations Studies
Canadian institutionsnot available
FundersFundação de Amparo à Pesquisa do Estado de São Paulo
KeywordsProcurementCafeteriaResource (disambiguation)SociologyQualitative researchPublic relationsPedagogyBusinessPolitical scienceMarketingSocial scienceMedicineComputer science

Abstract

fetched live from OpenAlex

Food is an interdisciplinary topic that transverses different areas of knowledge, allowing it to be used as a pedagogical resource in numerous teaching-learning processes and environments. This paper seeks to contribute to early debates on the relationship between public procurement and food pedagogies in schools and universities, a topic that is still little addressed in the literature. I explore the Farm to Cafeteria Canada (F2CC) network in Metro Vancouver, British Columbia, which beyond institutional procurement recognises food as a pedagogical resource at schools and on campus. My research is based on 18 site visits and qualitative analysis of documents and 9 semi-structured interviews conducted with institutional administrators associated with F2CC in Metro Vancouver. This paper demonstrates how the F2CC network activities in Metro Vancouver contribute not only to food procurement, but also to the practical development of pedagogical activities from different areas of knowledge and in different educational spaces.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.905
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.048
GPT teacher head0.239
Teacher spread0.191 · 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 designObservational
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

Citations2
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Food Studies / La Revue canadienne des études sur l alimentationSame topicDiverse Educational Innovations StudiesFrench-language works237,207