Examining the transport to school patterns of New Zealand adolescents by home-to-school distance and settlement types
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Scholarship on active transport to school has largely focused on children, (large) urban areas, the umbrella term of “active transport” which considered walking and cycling together and without taking into account walking and/or cycling distance. This research examined adolescents’ patterns of transport to school in diverse settlement types and in relation to home-to-school distance in the Otago region of Aotearoa New Zealand. Patterns of transport to school by home-to-school distance, and across school locations, are described for a sample of 2,403 adolescents (age: 15.1 ± 1.4 years; 55% females) attending 23 out of 27 schools in large urban areas (n = 1,309; 11 schools), medium urban areas (n = 265; three schools), small urban areas (n = 652; four schools) and rural settings (n = 177; five schools). Empirical data were collected through an online survey, in which adolescents reported sociodemographic characteristics, travel to school, and perceptions of walking and cycling. Home-to-school distance was measured on the shortest route determined using Geographic Information Systems (GIS)-based network analysis. Transport to school patterns differed significantly by home-to-school distance and across settlement types. Profiles of different transport user groups showed significant variability in sociodemographic characteristics, family factors, average distance to school, self-reported physical activity, and perceived health. Initiatives to promote active transport and reduce reliance on car transport to school, whether to improve health and the environment or to reduce greenhouse gas emissions, need to pay closer attention to the settlement types, distance to school, and characteristics of different transport user modes.
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.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it