Parental Travel Behaviors and Children’s Independent Mobility: A MultiSite Study
Bibliographic record
Abstract
PURPOSE: Children who are allowed greater independent mobility (IM) are more physically active. This study investigated associations between parents' current travel mode to work, their own IM and school travel mode as a child, and their child's IM. METHODS: Children in grades 4 to 6 (n = 1699) were recruited from urban, suburban, and rural schools in Vancouver, Ottawa, and Trois-Rivières. Parents reported their current travel mode to work, IM, and school travel mode as a child. Children self-reported their IM using Hillman's 6 mobility licenses. Multiple imputation was performed to replace missing data. Gender-stratified generalized linear mixed models were adjusted for child age, parent gender, urbanization, and socioeconomic status. RESULTS: The older a parent was allowed to travel alone as a child, the less IM their child had (boys: β = -0.09, 95% confidence interval [CI], -0.13 to -0.04; girls: β = -0.09, 95% CI, -0.13 to -0.06). Girls whose parents biked to work (β = 0.45, 95% CI, 0.06-0.83) or lived in Trois-Rivières versus other sites (β = 0.82, 95% CI, -0.43 to 1.21) had higher IM. IM increased with each year of age (boys: β = 0.46, CI, 0.34-0.58; girls: β = 0.38, 95% CI, 0.28-0.48). CONCLUSION: Parents who experienced IM later may be more restrictive of their child's IM. This may help explain the intergenerational decline in children's IM.
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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".