Walking and child pedestrian injury: a systematic review of built environment correlates of safe walking
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
BACKGROUND: The child active transportation literature has focused on walking, with little attention to risk associated with increased traffic exposure. This paper reviews the literature related to built environment correlates of walking and pedestrian injury in children together, to broaden the current conceptualization of walkability to include injury prevention. METHODS: Two independent searches were conducted focused on walking in children and child pedestrian injury within nine electronic databases until March, 2012. Studies were included which: 1) were quantitative 2) set in motorized countries 3) were either urban or suburban 4) investigated specific built environment risk factors 5) had outcomes of either walking in children and/or child pedestrian roadway collisions (ages 0-12). Built environment features were categorized according to those related to density, land use diversity or roadway design. Results were cross-tabulated to identify how built environment features associate with walking and injury. RESULTS: Fifty walking and 35 child pedestrian injury studies were identified. Only traffic calming and presence of playgrounds/recreation areas were consistently associated with more walking and less pedestrian injury. Several built environment features were associated with more walking, but with increased injury. Many features had inconsistent results or had not been investigated for either outcome. CONCLUSIONS: The findings emphasise the importance of incorporating safety into the conversation about creating more walkable cities.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| 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 it