Nurturing Future Generations: Household Food Practices of Canadian Children and Family Meal Participation
Bibliographic record
Abstract
PURPOSE: Food knowledge and skills appear to have declined in the general population over recent decades and may be contributing to negative outcomes and poor nutritional health. It is pertinent to observe the food skills and habits of Canadians, particularly Canadian youth. METHODS: Data from the Canadian Community Health Survey 2013 Rapid Response on Food Skills (n = 10 098) were used to examine the involvement of children in food preparation processes by identifying and describing the role of children in meal preparation as well as the practice of family meals. Variables were examined to assess differentiations between socio-demographic groupings (marital status, education, and income). RESULTS: Results indicate a moderate to high level of child participation in Canadian household food-related activities, with two-thirds of households with children having children involved in choosing meals and grocery shopping and one-third of children helping with meal preparation. Some differences were observed between region, education level, and Aboriginal and immigration status. Seventy-five percent of respondents participated in family meals. CONCLUSIONS: Data from this study contribute to the current discussion regarding loss of food skills and the significance of family meals on social and health indicators. Results suggest a range of interventions for dietitians including improving the quality of foods prepared at home and campaigns to promote family meals.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".