CHASE - Child Active Transportation Safety and the Environment
Bibliographic record
Abstract
Active transportation (AT), such as walking and biking, is a healthy way for children to explore their environment and develop independence. However, children can be injured while walking and biking and these injuries can be severe when children are hit by motor vehicles. Many Canadian cities make changes to the built environment (BE) (e.g., traffic calming features, separated bike lanes) to try and keep people safe. There is some research on how effective these changes are in preventing adult pedestrians and bicyclists from getting hurt, but very little research has been done to show how safe various environments are for children and youth. Our research program will study how features of the BE affect whether kids walk or bike to school and whether or not certain BE features increase or decrease their likelihood of getting hurt. Our program is unique because we are partnering with injury prevention professionals, provincial and municipal governments, environmental and not-for-profit organizations and traffic safety professionals who are in a position to help us better understand what features of traffic environments are dangerous or safe. Our team’s national scope will be invaluable in providing information regarding the variability in BE characteristics and is vital to producing evidence based recommendations that will increase safe AT.
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.035 | 0.035 |
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".