The role of civic organizations in regional parks governance, a case study on Kelowna, B.C.
Bibliographic record
Abstract
The governance between civic organizations and local governments plays a fundamental role in preserving, planning, and managing urban green spaces. Regional Parks are crucial because they are closely linked to urban development in mid-sized cities. These urban green spaces balance ecological conservation with recreational and community needs. This exploratory study examines the role of civic organizations involved in the governance of regional parks in Kelowna, British Columbia. Additionally, it explores the collaboration of civic organizations with local governments and how this governance structure serves the public. This study investigates how these partnerships influence decision-making, policy implementation, and long-term park sustainability. The research identifies key governance dynamics, including formal and informal collaborations, shared responsibilities, and challenges such as resource constraints and communication barriers. The analysis includes findings that are important for the planning, implementation, and management of collaborative arrangements in regional parks in Kelowna. The findings provide valuable insights for policymakers, civic organizations, urban planners, and the general population. The findings offer practical recommendations to enhance collaborative governance. These insights contribute to more effective regional park management, fostering sustainable urban development and environmental preservation. The study’s recommendations are tailored to Kelowna and the Regional District of Central Okanagan. Nonetheless, the framework is applicable to other mid-sized cities facing comparable dynamics between natural and built environments and stakeholders.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.011 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".