Gaining insight from the most challenging expedition: climate change from the perspective of Canadian mountain guides
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Nature based tourism (NBT) is becoming increasingly popular, particularly following the COVID-19 pandemic as people began to sought outdoor activities. Accompanying the projected rise in NBT demand in a post COVID-19 era are increasing challenges associated with climate change, particularly in mountain regions. However, there is limited local knowledge documented to date from those who are intricately involved in mountain NBT activities and have experienced the impacts of climate change first hand. Using an online survey (n = 169), this research is the first to present the intimate knowledge of mountain guides in Canada, offering novel insight into climate change risks and opportunities for NBT in mountain regions, including strategies to contend with risk and adaptation. From this survey, 99% of guides indicated that they have experienced change in the mountain environment throughout the course of their career and due to the adaptive nature of guides, many have already implemented strategies to adapt to the impacts of climate change. While findings presented in this paper offer practical knowledge to plan for a future threatened with rapid climatic change, further research is required to explore effectiveness of adaptation strategies, scope of adaptive capacity, changes in natural infrastructure, and guides’ roles as educators.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 it