Is cooking dead? The state of <scp>H</scp>ome <scp>E</scp>conomics <scp>F</scp>ood and <scp>N</scp>utrition education in a <scp>C</scp>anadian province
Bibliographic record
Abstract
Abstract High population rates of obesity and nutrition‐related chronic diseases warrant an examination of the role of food and nutrition education in health promotion. Using a mixed‐methods approach, this study explored student enrolment trends in, and perceptions of, Home Economics Food and Nutrition education in a Canadian province. Enrolment in Home Economics Food and Nutrition courses for grades 7–12 was examined from 2000 to 2010 using administrative data. Perceptions of Home Economics Food and Nutrition education by home economics teachers and superintendents were investigated through in‐depth interviews using a grounded theory approach. Results revealed that, although enrolment, including boys, increased slightly over the study period, the majority of children do not take Home Economics Food and Nutrition classes. Further, enrolment decreased significantly from grades 7 (45.77%) to 12 (7.61%). Home Economics Food and Nutrition education faces significant challenges to its future viability. These include: many school administrators, non‐home economics teachers and some parents do not value Home Economics Food and Nutrition education; Home Economics Food and Nutrition education is seen as less valuable than math and science for future career planning; outdated curriculum and teaching infrastructure; reduced numbers of new home economics teachers; decreasing student food knowledge and skills; and changing social norms regarding food and eating (increased use of convenience foods across population groups, a youth ‘fast food culture’ and fewer family meals). Results also indicated that Home Economics Food and Nutrition education is seen as critically important for youth, given that one third of Canadian children are now overweight or obese, fast and highly processed foods make up an increasing proportion of Canadians' diets, and there are increasing dilemmas being faced with food production and food safety. These results signal a growing tension between societal trends towards technological solutions in education and everyday living, and the growing acknowledgement of the externalities associated with these trends including poor health and environmental impacts. Consequently, evidence‐based food and nutrition education that is relevant for today's food environment and busy lifestyles is warranted to improve the health of current and future generations. This should be based on a comprehensive food and nutrition framework including functional, interactive and critical ‘food literacy’. Policy measures are urgently required to ensure all youth have access to food literacy education.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".