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Record W4313011579 · doi:10.15353/cfs-rcea.v9i2.544

Unwrapping school lunch

2022· article· en· W4313011579 on OpenAlexaffvenueabout
Jennifer Black, Rachel Mazac, Amber Heckelman, Sinikka Elliott

Bibliographic record

VenueCanadian Food Studies / La Revue canadienne des études sur l alimentation · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCulinary Culture and Tourism
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsGovernment (linguistics)PerceptionEthnographyDiversity (politics)PsychologyPublic relationsPedagogySociologyPolitical science

Abstract

fetched live from OpenAlex

Students are important stakeholders in school food programs. Yet children’s daily experiences and voices are often overlooked in advocacy around school food. In Canada, where the federal government recently expressed interest in creating a National School Food Program, nearly no research has documented the first-hand experiences of children during lunch. This ethnographic study draws on data collected during 36 lunchtimes in three Canadian schools during a transitional period in a school district’s lunch program. The findings unwrap the powerful role of students’ perceptions of and relationships to food in shaping their social interactions, and their sense of care, connection, and identity. Classroom observations coupled with photos of school lunches demonstrate the wide diversity of foods eaten at school and the nuanced, complex, and sometimes divergent meanings children give to food, school lunch and the people involved in preparing, serving, supervising, and sharing lunchtime experiences. Students demonstrated in-depth knowledge of the food choices and attitudes of their peers and actively marked out their identities vis-à-vis food. Students frequently talked about food as a site of care and support, and both the social relationships and care work that played out were a major part of school lunch experiences. Understanding the intricacies of children’s school lunch experiences, including the relationships, meanings, and values that shape school lunch, will be critical for creating robust school food programs and policies in Canada that better serve the needs of children and reduce rather than reproduce existing health and social inequalities.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.819
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.223
Teacher spread0.176 · 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 designNot applicable
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

Citations5
Published2022
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Food Studies / La Revue canadienne des études sur l alimentationSame topicCulinary Culture and TourismFrench-language works237,207