An assessment of mineral development adjacent to Kluane National Park and Reserve, Yukon
Bibliographic record
Abstract
This study assessed the potential for competing land use along the boundaries of national parks in northern Canada to impact the wilderness character of these parks, using Kluane National Park and Reserve (KNPR) in the southwest Yukon as a case study. A survey on wilderness and park values was distributed to KNPR visitors to determine the relative importance of these values from the perspective of a park visitor. The survey results provided a foundation for the assessment of KNPR and adjacent development based on the most important wilderness characteristics identified by respondents: the preservation of wildlife habitat, the protection of endangered species, and ecosystem protection. Survey results also illustrated that, with respect to KNPR, park visitors value the opportunity to encounter untouched nature, to experience the wilderness character of a national park, and to view wildlife in a natural setting. A GIS-based approach was used to assess the compatibility of mineral development and the preservation of key wildlife habitat in the Kluane region with respect to the park. Key habitat for the seven wildlife species considered was primarily concentrated in the region adjacent to the park. There was also a high concentration of quartz and placer mineral claims in this region, including a proposed large-scale, open-pit nickel and platinum-group metals mine that is currently in an advanced state of exploration. Adjacent mineral development may impact the wilderness character of the park by compromising key wildlife habitat adjacent to KNPR. Other national parks in northern Canada also face similar challenges. As development in northern Canada increases, regional management strategies must prioritize ecosystem protection to preserve the wilderness character of northern national parks.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".