Access to Parks and Green Spaces in Quebec City, Canada: Developing Children-Specific Accessibility Measures
Bibliographic record
Abstract
Accessibility indicators are gaining traction in research and planning as they provide a joint understanding of how transport networks and land-use patterns enable individuals to reach a variety of destinations. Local accessibility is especially beneficial for children as they do not have the same capacities to travel as adults and their independent mobility is generally constrained to active modes such as walking and cycling. Further, active and independent travel are linked to their health and well-being. Yet, there does not appear to have been much work done in relation to developing accessibility indicators specific to children. This study presents a methodology to specifically assess accessibility to parks (a key destination for children) on foot and by bicycle for children in Quebec City, Canada using open-access data. Accessibility indicators were generated for each residential lot based on the suitability of the pedestrian and cycling infrastructure for children. The number of parks accessible was presented and the equity of accessibility to parks was considered through population and socioeconomic measures. The results revealed a notable decrease in walking accessibility when only dedicated pedestrian infrastructure was considered, and differences between walking and cycling accessibility. This enabled the identification of accessibility gaps where the existing infrastructure did not provide safe access to parks and green spaces for children This research will be of interest to researchers and planners aiming to refine accessibility indicators to support children’s independent mobility, while taking equity into consideration.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 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".