Active Travel in Rural New Zealand: A Study of Rural Adolescents’ Perceptions of Walking and Cycling to School
Bibliographic record
Abstract
Background: Walking and cycling to school have been extensively studied in urban settings, whereas data from rural areas remain sparse. This study examined perceptions of walking and cycling to school amongst adolescents living within 4.8 km of school in rural New Zealand. Methods: Adolescents (n=62; 53.2% females; 15.6±1.5 years; five schools) residing and attending a secondary school in a rural settings (population <1,000) completed an online survey about their perceptions of walking and cycling to school. Home-to-school distance was calculated using Geographic Information Systems shortest network path analysis. Results: Overall, 73% of adolescents walked and 11% cycled to school. Compared to cycling, adolescents reported a greater desire (57% vs 26%) and intention (74% vs 13%) to walk to school, and perceived more support from friends (37% vs 30%), parents (81% vs 40%), and schools (61% vs 34%) (all p<0.001). Adolescents also reported better physical infrastructure (presence/availability of footpaths vs cycle lanes) for walking versus cycling to school (86% vs 36%, p<0.001). Over 95% of adolescents perceived both walking and cycling to school as safe. Conclusions:Compared to cycling, walking to school was a more common and preferred transport mode, with greater social support and physical infrastructure, whereas both modes were perceived to be safe by rural adolescents living within 4.8 km of their school. The findings suggest that supportive social and built environments appear to encourage walking to school in rural areas. Mode-specific approaches may be required to encourage cycling to school for rural adolescents.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".