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Record W4306409880 · doi:10.15353/cfs-rcea.v9i3.482

Operationalizing sustainable food systems through food programs in elementary schools

2022· article· en· W4306409880 on OpenAlexaffvenueabout
Tracy Everitt, Rachel Engler‐Stringer, Wanda Martin

Bibliographic record

VenueCanadian Food Studies / La Revue canadienne des études sur l alimentation · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicDiverse Educational Innovations Studies
Canadian institutionsUniversity of SaskatchewanSt. Francis Xavier University
Fundersnot available
KeywordsCurriculumSustainabilityFood systemsOperationalizationSustainable agricultureExperiential learningBusinessAgriculturePsychologyPedagogyFood securityGeography

Abstract

fetched live from OpenAlex

Healthy eating supports optimal growth, development, and academic achievement. Yet, the diet quality of school-aged children is poor. Food insecurity and chronic disease are concerns, as are unsustainable agricultural practices. Sustainable food systems have a low environmental impact and can address both dietary and sustainability concerns. This multi-case study was conducted in two Community Schools in a mid-sized Canadian city. Data was collected through interviews, observations, a checklist, and curriculum and policy review. The purpose of this study was to understand the capacity of local elementary schools to implement sustainable food systems strategies in curriculum, policy, and practice. Teachers were doing some cooking and gardening with students, and schools were doing some recycling. There were no specific food policies. Infrastructure challenges varied by school. Insufficient funding and curriculum resources were seen as barriers to implementing sustainable food systems. Staff characteristics and relationships were seen as facilitators. Schools can be positioned to be strong leaders in the area of school food by prioritizing food literacy and sustainable food system strategies and developing supportive policies, including community members and students in programming, and including experiential food production opportunities for all students.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.797
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0020.000
Scholarly communication0.0000.001
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 head0.113
GPT teacher head0.255
Teacher spread0.142 · 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 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

Citations6
Published2022
Admission routes3
Has abstractyes

Explore more

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