Promoting sustainable and equitable access to parks : a study of transit-to-parks initiatives and user perceptions
Bibliographic record
Abstract
In response to increasing sustainability challenges and the critical need for equitable park access, this thesis investigates the development of Transit-to-Parks (T2P) initiatives that link public transit to natural areas across Canada, and analyzes factors influencing park visitors' transportation choices in Metro Vancouver. The thesis employs a mixed-methods approach, combining qualitative insights gathered from semi-structured interviews with ten Transit-to- Parks (T2P) initiative practitioners and quantitative analyses of 430 park-user survey responses. The research uncovers three motivations for T2P initiatives: parking and traffic congestion, environmental impacts of traffic, and equity considerations. It highlights key facilitators such as policy advocacy, partnerships, and community engagement in the successful implementation of T2P initiatives while also pointing out challenges, including limited funding and labor shortages, inadequate infrastructure, and siloed agencies. Furthermore, analysis of park visitors' mode choices indicates that socio-demographic and trip-related factors significantly influence the decision to use sustainable transport options for park visits. These findings suggest that targeted infrastructure improvements, policy interventions, and planning efforts are essential to reducing car dependency and fostering a shift toward more sustainable transportation modes. This thesis contributes to the discourse on urban planning, green equity, transportation equity, and recreational management, offering practical insights for transit agencies, urban planners, and policymakers aiming to improve park accessibility through sustainable transportation. It advocates for the integration of transportation planning with park access strategies to foster more sustainable, equitable urban environments.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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".