An overview of mini systematic literature on factors that influence the parents "perspective of leaving their children to / from school
Bibliographic record
Abstract
The first walk to school program was in 1997, with just five primary schools taking part in Hertfordshire. Walk to School Day began in the United States of America (USA). as a one-day event. The first-ever International Walk to School Day launched in 2000. Today the International Walk to school day is celebrated in more than 40 countries and in thousands of schools across the United States of America (USA). The programs were extended to Canada, United Kingdom (UK), United States of America (USA), Ireland, Cyprus, and Gibraltar [1]. In 2003 the International Walk to School Day extended to become a week of activities in 33 countries including the United States of America (USA), Belgium, Canada, Australia, and New Zealand supported the activities. In 2006 the first International Walk to School Month was launched [2]. Every October, Victoria primary school encourages kids to walk, ride or scoot to and from school, local councils and communities are also encouraged to make active travel easy, safe, and accessible. Currently, 759 primary schools across Victoria take part in Walk to School, with 140,303 primary school kids walking more than 1.6 million kilometres during October, the equivalent of walking two return trips to the moon [3].
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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 | 0.010 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.016 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".