Cultivating School Food Community: An Ethnography on Nutritional Wellbeing in a Calgary Public School
Bibliographic record
Abstract
The nutritional health of Canadian children has declined over the last 30 years. Public health campaigns and health education programs have been developed to address increased rates of obesity and overweight in young people. Schools are popular sites for health education programming in this regard. Although policies and initiatives have been used to improve student nutritional health, low-nutritional value foods (LNVFs) continue to proliferate in the school food environment (SFE). Critical Medical Anthropology (CMA) considers the social, political, economic, and environmental factors that interact with the body to impact overall health and may help shed light on why young people continue to consume LNVFs in school. CMA is both a theory and practice that can be used for improving health and wellbeing in communities. This thesis utilized CMA in an ethnography at a school in Calgary to better understand what factors influence food choice among students. Interviews, group discussions and participant observation were conducted between January 2015 and June 2015. Through collaborative initiatives including a garbology study and a cookbook project, students, teachers and researcher uncovered valuable information to help inform future food programming in schools.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.018 | 0.010 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".