Enhancing shared street accessibility in heritage sites for individuals with visual disabilities: a Canadian perspective
Bibliographic record
Abstract
Introduction: Heritage sites often pose significant accessibility challenges for individuals with visual disabilities due to their preserved architectural features and strict regulations against modifications. In shared streets, designed to encourage pedestrian use and reduce vehicle dominance, these challenges are exacerbated by the lack of tactile and directional cues for visually impaired users. This study, set in the context of Canadian heritage sites, explores how shared streets can be adapted to be more inclusive while respecting the integrity of historical environments. Objective: The objective of this study is to explore and propose practical solutions to enhance the accessibility of shared streets for individuals with visual disabilities within heritage sites, with a particular focus on preservation requirements. Methodology: The study adopts a three-phase methodology. First, co-design sessions were conducted with three groups of stakeholders: people with disabilities, caregivers, and experts in accessibility and heritage preservation. Second, a narrative literature review was undertaken to identify practices from existing research and urban planning cases. Finally, solutions were developed in collaboration with a design firm to create practical, adaptable prototypes that address the specific needs identified in earlier phases. Findings: The co-design sessions revealed several key challenges, including the lack of tactile references, difficulties with snow removal, and the need for clearer delineation between pedestrian and vehicular zones. Solutions such as tactile paving, modular bollards, and the use of contrasting materials were developed to address these issues. The narrative review reinforced the importance of universal design in heritage contexts and provided insights into successful implementations in other urban settings. Conclusion: The study concludes that shared streets can be made more accessible for individuals with visual disabilities by adopting a modular design approach that integrates tactile cues and adaptable urban furniture. These solutions ensure that accessibility and safety can coexist with heritage preservation, promoting inclusivity in public spaces. The research highlights the importance of stakeholder engagement in the design process and offers a replicable framework for improving accessibility in heritage sites globally. However, further field testing is needed to assess the feasibility and acceptance of these solutions within the regulatory constraints of heritage environments.
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How this classification was reachedexpand
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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".