Measuring Temporal Differences in Rural Canadian Children’s Moderate-to-Vigorous Physical Activity
Bibliographic record
Abstract
The purpose of this study was to measure the factors that influence children's moderate-to-vigorous physical activity (MVPA) during school curriculum time, recess time, and outside school time in a rural area. During the Fall and Winter of 2016, 34 boys and 55 girls aged 8-14 years from rural communities in rural Northwestern Ontario participated in the Spatial Temporal Environment and Activity Monitoring project. The children's MVPA was measured using an accelerometer, and child-level demographic, behavioral, and environmental data were gathered from surveys, passively logging global positioning units, and municipal datasets. Data on daily temperature and precipitation were gathered from the closest Environment Canada weather station. A mixed model was used to assess the relationship between child- and day-level factors and children's MVPA. On average, children were getting 12.9 min of MVPA during recess, 17.7 min during curriculum time, and 29.0 min of MVPA outside school time. During all three time points, boys were more active than girls. During curriculum time, children in lower grades were more active, and the weather had differing impacts depending on the time of day. The findings of this study illustrate the differences in MVPA and the factors that influence MVPA by time of day. Examining different time segments provides valuable information for understanding children's MVPA patterns.
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 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 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".