Private Land, Public Interest: Securing Community Access to Private Lands for Mountain Biking and Amenity Migration in Canada
Bibliographic record
Abstract
Abstract In order to support diversified forms of economic and community development, rural communities are increasingly investing in recreational opportunities on neighbouring lands, including agri-tourism and mountain resort development. However, in communities where significant proportions of peripheral land holdings are privately owned, opportunities for recreational land access and development are restricted or threatened. The Village of Cumberland, located on Vancouver Island, British Columbia, is home to a premier network of mountain biking trails developed by local users on a mix of both public recreational and privately owned industrial land. Without the existence of a formalized land use agreement between local public, private and not-for-profit land interests, the value of Cumberland’s mountain biking trail network cannot be wholly realized. This case study details the collaborative land use management partnership that has been developed in Cumberland in order to support economic and community development through amenity migration and the promotion of recreational mountain biking. Through sharing the costs and benefits of managing private land use, Cumberland’s multi-sector stakeholders have ensured that their individual strengths are utilized and unique interests are addressed. Information Vancouver Island University World Leisure Centre of Excellence Main image: Burns Lake bike trails By Britcruise - Own work, CC BY-SA 3.0, https://commons.wikimedia.org/w/index.php?curid=15729806 © Jeff Wahl and Pete Parker 2015
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.002 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".