Cruising the marginal ice zone: climate change and Arctic tourism
Bibliographic record
Abstract
The effects of climate change are leading to pronounced physical and ecological changes in the Arctic Marginal Ice Zone (MIZ). These are not only of concern for the research community but also for the tourism industry dependent on this unique marine ecosystem. Tourists increasingly become aware that the Arctic as we know it may disappear due to several environmental threats, and want to visit the region before it becomes irrevocably changed. However, ‘last-chance tourism’ in this region faces several challenges. The lack of infrastructure and appropriate search and rescue policies are examples of existing issues in such a remote location. Additionally, tourism itself may further amplify the physical and ecological changes in the Arctic region. In this article, we provide an interdisciplinary analysis of the links between the MIZ, climate change and the tourism industry. We also identify existing regulations and the need for new ones concerning operations in the MIZ and in the Arctic Ocean.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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 teacher head, 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".