<i>Children's Perceptions of</i>Healthful Eating and Physical Activity
Bibliographic record
Abstract
PURPOSE: Healthful lifestyle habits established in childhood may continue through adulthood. Such habits may also be effective in preventing or reversing overweight and obesity. However, little is known about children's perceptions of healthful eating and physical activity. Thus, we sought a better understanding of how children perceive healthful eating and physical activity. METHODS: A purposeful selection was made of Winnipeg, Manitoba, boys (n=23) and girls (n=22) aged 11 to 12 years. The children were interviewed using a semi-structured, in-depth interview guide. Data were analyzed using thematic coding. RESULTS: Although healthful eating was seen as necessary for health, high-fat, high-sugar foods were a source of pleasure and enjoyed during social times. Physical activity was a way of spending time with friends, either through active play or watching sports. Boys viewed screen time and homework as barriers to physical activity, while girls identified no common barriers. Children viewed physical activity as easier than healthful eating, describing the former as "play" and "fun." CONCLUSIONS: Knowing how children think about food choices will further our understanding of the disconnect between nutrition knowledge and dietary behaviours. Understanding conflicting pressures that influence children's healthful lifestyles may enhance communication about these topics among parents, educators, and children.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".