Sea Ice in Canada’s Arctic: Implications for Cruise Tourism
Bibliographic record
Abstract
ABSTRACT. Although cruise travel to the Canadian Arctic has grown steadily since 1984, some commentators have suggested that growth in this sector of the tourism industry might accelerate, given the warming effects of climate change that are making formerly remote Canadian Arctic communities more accessible to cruise vessels. Using sea-ice charts from the Canadian Ice Service, we argue that Global Climate Model predictions of an ice-free Arctic as early as 2050–70 may lead to a false sense of optimism regarding the potential exploitation of all Canadian Arctic waters for tourism purposes. This is because climate warming is altering the character and distribution of sea ice, increasing the likelihood of hull-penetrating, high-latitude, multi-year ice that could cause major pitfalls for future navigation in some places in Arctic Canada. These changes may have negative implications for cruise tourism in the Canadian Arctic, and, in particular, for tourist transits through the Northwest Passage and High Arctic regions. Key words: Canadian Arctic, Northwest Passage, sea ice, tourism, polar tourism, cruise tourism RÉSUMÉ. Bien que le nombre de voyages de croisières se soit accru régulièrement depuis 1984, certains commentateurs ont laissé entendre que la croissance de ce secteur de l’industrie touristique pourrait s’intensifier en raison des effets de réchauffement du changement climatique qui rendent des lieux de l’Arctique canadien autrefois éloignés plus accessibles aux navires de croisière. En nous appuyant sur les cartes de la fréquence de présence de glace de mer du Service canadien des glaces, nous soutenons que les prédictions du modèle climatique mondial selon lesquelles il n’y aurait plus de glace dans l’Arctique dès les années 2050 à
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".