Children's participation in physically active leisure: income, gender, and regional differences.
Bibliographic record
Abstract
The recreation and leisure field has recently directed attention to physically active leisure for its potential health implications. With an increasing prevalence of childhood obesity, examining opportunities to increase the physical activity of children has become of importance to managers, programmers, instructors, and researchers. Previous research has suggested that gender, income, and geographic location play a large role in children’s access to physical activities and, therefore, the role of each was explored within this study. The sample for this project consisted of grade three children living in an eastern province of Canada and included two types of data-collection instruments: questionnaires administered to children and their parents (n=1,028 families), and accelerometer data (an objective measure of physical activity levels) (n=103). Frequencies, chisquare, and ANOVA were used to analyze the findings from these instruments individually and correlation coefficients were used to examine the relationship between each of the variables. The children were from diverse socioeconomic backgrounds and represented equal numbers of girls and boys. Both the questionnaire and accelerometer data indicated they were extremely active, participating on average three hours/day in a variety of physical activities. Contrary to previous research, girls, children of low income, and those living in rural areas did not have lower activity levels. Although children in each of these demographic groups reported experiencing more constraints to their participation, they negotiated through (or past) these factors to either maintain or participate at greater frequency than those who did not fall within these groups. Another important finding was that despite the large amounts of physical activity, the children’s Body Mass Index (BMI) was very high suggesting that they are overweight. Greater research is needed to explore this apparently contradictory relationship.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".