Understanding consumer behaviour and adaptation planning responses to climate-driven environmental change in Canada's parks and protected areas: a climate futurescapes approach
Bibliographic record
Abstract
Parks and protected areas are a global ecological, social and health resource visited by over 8 billion people annually. Their use can yield substantial benefits, but only if a balance between ecological integrity and sustainable visitation is struck. This research explores the potential influence of climate-driven environmental change on visitation to North America's most popular glacier, the Athabasca Glacier in Jasper National Park, Canada. Photorealistic environmental visualizations were used to gauge visitors’ perceptions of environmental change and potential impacts on consumer behaviour. Results suggest that impacts could substantially diminish the site's pull as a tourism destination. Rather than improving visitation prospects, expert-proposed adaptations underestimated the importance of perceived naturalness and contributed to further potential decline. Findings are relevant to protected areas planning and management. They suggest that a natural path to climate change adaptation is the best way to support both ecological integrity and the long-term tourism pull of protected areas.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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".