Tourism and Change in Polar Regions: Climate, Environments and Experiences
Bibliographic record
Abstract
Part 1: The Context 1. Tourism and Change in the Polar Regions: Introduction - Definitions, Locations, Places and Dimensions (C. Michael Hall & Jarkko Saarinen) 2. Tourism and Environmental Change in Polar Regions: Impacts, Climate Change and Biological Invasion (Hall) Part 2: Tourism and Change in the Northern Polar Regions 3. Cruise Tourism in Arctic Canada: Navigating a Warming Climate (E.J. Stewart, S.E.L. Howell, D. Draper, J. Yackel & A. Tivy) 4. Climate Change and Polar Bear Viewing: A Case Study of Visitor Demand, Carbon Emissions and Mitigation in Churchill, Canada (Jackie Dawson, Emma Stewart & Daniel Scott) 5. Climate Disruption and the Changing Dynamics of Polar Bear - Human Interactions in Northern Ontario: A Case Study of Polar Bear Management in Polar Bear Provincial Park, Ontario, Canada (Raynard Harvey Lemelin, Norman McIntyre, Rhonda Koster & Margaret Johnston) 6. Cruise Tourist Experiences and Management Implications for Auyuittuq, Sirmilik and Quttinirpaaq National Parks, Nunavut, Canada (Patrick T. Maher) 7. A Holiday on Ice on Hold? Nature-based Tourism and Climate Change in the Nordic North (Linda Lundmark) 8. Sustainability and Emerging Awareness of a Changing Climate: The Tourism Industry's Knowledge and Perceptions of the Future of Nature-based Winter Tourism in Finland (Kaarina Tervo & Saarinen) 9. Constraints and Opportunities in the Development of Diamond Tourism in Yellowknife, NWT (Jamie Noakes & Margaret Johnston) Part 3: Tourism and Change in the Southern Polar Regions 10. Cultural heritage tourism in Antarctica and Svalbard: Patterns, Impacts, and Policies (Ricardo Roura) 11. Narratives of history, environment and global change: expeditioner-tourists in Antarctica (Mark Nuttall) 12. Awesome size...magnitude of the place...the incredible beauty...: Visitors' onsite experiences in the Ross Sea region of Antarctica (Maher) 13. Images of Antarctica and Ushuaia (Argentina) as a Gateway Port: Antarctic Visitors and Their Expectations (Marisol) 14. Business as (Un)Usual: Integrated Scenario Analysis for Tourism in Antarctica (Machiel Lamers, Bas Amelung & Jan H. Stel) 15. Tourism, Conservation and Visitor Management in the Sub-Antarctic Islands (Hall and Sandra Wilson) Part 4: Conclusions and Future Issues 16. Contested Place and the Legitimization of Sovereignty through Tourism in Polar Regions (Dallen J. Timothy) 17. Last Chance to See? Future Issues for Polar Tourism and Change (Hall & Saarinen)
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".