Building evidence-based research for park development and design in Canadian cities : cases from the City of Vancouver parks
Bibliographic record
Abstract
Urban parks are among the few urban infrastructures that promote the social, economic and environmental well-being of city residents at the same time. Despite the importance of parks towards the development of cities, there is a major research gap within the Canadian context. The goal of this study is to examine the factors influencing the development and management of urban parks in the City of Vancouver. The research focused on three main themes namely: the evolution of park planning, urban park management models and park user characteristics. Methodologically, the study relied on the mixed methods approach consisting of primary and secondary sources of data. The secondary data used for this study was collected from a variety of documentary sources such as Parks Board records, City of Vancouver documents, old newspapers and archival records. On the other hand, the primary data was collected by interviewing key stakeholders and conducting park user survey in Stanley Park and Queen Elizabeth Park. The historical analysis of parks showed that the development of parks in the City of Vancouver has been approached from a multi-stakeholder perspective since the 19th century. Also, there has been an increase in the number of physical structures and area of hard landscaping on these parks. This is as a result of the continuous increase in the provision of more recreational facilities. Historically, the management of parks in the City of Vancouver has not been approached by one particular model but rather a combination of the elements of the public-for-profit model and the public-non-profit model. However, these models were not strategically laid down to guide the development of parks but rather came along with the incremental development of parks in the City of Vancouver. Similar to the historical approach to park management, the contemporary park management system of the City of Vancouver still relies on the hybrid model. Park management decisions should be informed by the type of park, type of activities and the type of people who use the parks. The bivariate analysis showed that there is the need for park researchers to be cautious in generalizing their findings on the relationship between demographic characteristics and park use. Some of the results ascertained from assessing the relationships between demographic characteristics and park use are generalizable whilst others are context specific. For example, the chi-square analysis indicated that there is no statistically significant relationship between gender and active walking in Stanley Park (P>0.05). However, the relationship between gender and walking in Queen Elizabeth Park was statistically significant (P≤0.05). It is, therefore, important for park administrators and policy makers to formulate context-specific policies and management decisions in relation to the demographic characteristics of park users and active walking. The statistical analysis also indicated that the intensity of Stanley Park use is influenced by demographic characteristics such as marital status, place of origin, race, and age. On the other hand, the intensity of park use in Queen Elizabeth Park is influenced by demographic characteristics such as employment, gender, place of origin and religion. The results of the study showed a strong relationship between the place of origin of park users and the intensity of park use. The research finding showed that park users who live in Vancouver use both Stanley Park and Queen Elizabeth Park at a higher intensity rate than park users coming from outside Canada.
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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 | 0.020 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.014 |
| Science and technology studies | 0.017 | 0.007 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".