MétaCan
Menu
Back to cohort

Role of Food System Planning in Facilitating Local Food Procurement for School Meals

2023· article· en· W4390012066 on OpenAlexaffvenue
Elina Blomley, Tammara Soma, Christine Callihoo, Richard Han, Claudia Páez-Varas, Chris Bodnar, Belinda Li

Bibliographic record

VenueCanadian Planning and Policy / Aménagement et politique au Canada · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicOrganic Food and Agriculture
Canadian institutionsUniversity of Northern British ColumbiaSimon Fraser University
Fundersnot available
KeywordsProcurementFood systemsBusinessLocal governmentAgricultureFood processingMarketingSustainable agricultureProduction (economics)Food securityEnvironmental planningEconomicsGeographyPolitical sciencePublic administration

Abstract

fetched live from OpenAlex

Farm to School (F2S) programs seeks to connect students with their local food system and community. Providing local food to schools, however, relies on the continuity of local food production in British Columbia (B.C.), as well as the capacity and willingness of farmers to support this “alternative market.” Planners have an important role to play in supporting farmers’ ability to sustain local food systems. At the provincial level, planning for farmland preservation through the Agricultural Land Reserve has helped to secure some of the farmland needed to support local food production into the future. However, preserving farmland is only one part of the solution to sustain local food systems. Drawing upon key informant interviews (n=21), this paper identifies planning-related barriers and opportunities for local food procurement in schools. This research emphasizes the invaluable roles that farmers, government, and planners can play in reimagining a just and sustainable food system transition.

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)0.007
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.699
Threshold uncertainty score0.598

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0120.006
Scholarly communication0.0060.002
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0100.000

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 head0.019
GPT teacher head0.237
Teacher spread0.218 · 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 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

Citations0
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Planning and Policy / Aménagement et politique au CanadaSame topicOrganic Food and AgricultureFrench-language works237,207