On your bike! a cross-sectional study of the individual, social and environmental correlates of cycling to school
Bibliographic record
Abstract
BACKGROUND: Active school transport (AST) has declined rapidly in recent decades. While many studies have examined walking, cycling to school has received very little attention. Correlates of cycling are likely to differ to those from walking and cycling enables AST from further distances. This study examined individual, social and environmental factors associated with cycling to school among elementary school-aged children, stratified by gender. METHODS: Children (n = 1197) attending 25 Australian primary schools located in high or low walkable neighborhoods, completed a one-week travel diary and a parent/child questionnaire on travel habits and attitudes. RESULTS: Overall, 31.2% of boys and 14.6% of girls cycled ≥ 1 trip/week, however 59.4% of boys and 36.7% of girls reported cycling as their preferred school transport mode. In boys (but not girls), school neighborhood design was significantly associated with cycling: i.e., boys attending schools in neighborhoods with high connectivity and low traffic were 5.58 times more likely to cycle (95% CI 1.11-27.96) and for each kilometer boys lived from school the odds of cycling reduced by 0.70 (95% CI 0.63-0.99). Irrespective of gender, cycling to school was associated with parental confidence in their child's cycling ability (boys: OR 10.39; 95% CI 3.79-28.48; girls: OR 4.03; 95% CI 2.02-8.05), parental perceived convenience of driving (boys: OR 0.42; 95% CI 0.23-0.74; girls: OR 0.40; 95% CI 0.20-0.82); and child's preference to cycle (boys: OR 5.68; 95% CI 3.23-9.98; girls: OR 3.73; 95% CI 2.26-6.17). CONCLUSION: School proximity, street network connectivity and traffic exposure in school neighborhoods was associated with boys (but not girls) cycling to school. Irrespective of gender, parents need to be confident in their child's cycling ability and must prioritize cycling over driving.
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".