Balancing Recreation and Ecology in Long Distance Trail Management The Great Divide Trail
Bibliographic record
Abstract
This study investigates the perspectives of land managers regarding the challenges and opportunities associated with the Great Divide Trail (GDT). It emphasizes the delicate balance these managers must strike between ecological conservation and recreational access while overseeing backcountry trail systems. The research also examines how neighbouring park agencies collaborate to address these dual demands. By comparing the current situation of the GDT with other linear backcountry trail systems across North America, the project identifies potential avenues for future research, supporting land managers to harmonize ecological integrity and recreational access. Employing qualitative analysis of six semi-structured interviews with land managers from parks along the GDT, the findings suggest that jurisdictions face similar challenges and threats. They rarely participate in cross-jurisdictional collaboration. Additionally, the Great Divide Trail Association emerges as a pivotal non-profit organization, positioned to advocate for the GDT and foster community among land managers, thereby facilitating opportunities for enhanced collaboration in the Canadian Rocky Mountains.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".