An Apple A Day: Exploring Food and Agricultural Knowledge and Skill Among Children in Southern Ontario
Bibliographic record
Abstract
While the literature on food has somewhat addressed rudimentary food skills and their importance in the creation and maintenance of a healthy population, there remains a serious lack of research into the importance of food and agricultural skills and knowledge transference to children, especially given the rise in diet-related illnesses. This study focuses on the perceived importance of food and agricultural education initiatives, as well as the opportunities and barriers that exist within the elementary school classroom to incorporate food and agricultural topics, in the context of southern Ontario, specifically Wellington County. Drawing on Wilkin's concept of ‘food citizenship’ as a desirable end goal of alternative food movements, food and agricultural education presence in the curriculum is researched for its potential contribution to healthy, active communities.\nThis study highlights experiences and insights through key informant interviews with teachers, parents, Upper Grand District School Board employees, nutritionists, and people involved in relevant community organizations, to determine the current role that formal secondary-level public educational institutions, and the educators within them, play in the dissemination of food and agricultural knowledge and skill. More specifically, the questions asked focus on what opportunities exist for teachers to enable and assist their students in becoming food citizens, and specifically: in what ways does the provincial curriculum as it currently exists, lend support to teachers, who can then enable students to become food citizens? And perhaps most importantly, do food skills and knowledge contribute to the holistic development of young people?\nThis study uses a qualitative approach, through the use of key informant interviews and curriculum analysis. Research findings indicate that food and agricultural education is seen as important to respondents, and that there are a number of complex opportunities for and barriers to including these topics in classrooms and encouraging greater food citizenship in young people.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".