An In-depth Analysis of Planned Cruise Ship Itineraries and Voyages in the Canadian Arctic
Bibliographic record
Abstract
There is limited data on marine tourism traffic (cruise ships and pleasure craft) and on-shore locations visited by cruise ships in the Canadian Arctic. Marine tourism vessels represent 11.8% of all vessel voyages transiting within the Canadian Arctic, which is significant as these vessels "go off the beaten path" seeking out natural and cultural experiences. Given the vast landscape of the Canadian Arctic, as well as the fact that not all on-shore sites require a permit to visit, there is uncertainty as to where marine tourism vessels are disembarking passengers onto land. This research utilizes databases with information on marine tourism voyages (i. e., ship traffic) from 1990 to 2019 and shore locations from 2008 to 2019 to better understand the current scale and scope of the sector. Data on marine tourism voyages were acquired from the Canadian Coast Guard Ship Archive and shore location information were compiled from planned publicly available cruise ship itineraries. The results show that marine tourism vessels and related shore activities have been steadily increasing over time, while also illustrating and highlighting the infancy of the Canadian Arctic marine tourism industry as a total of 150 unique on-shore locations have been advertised to tourists from 2008 to 2019 with a minimum of 44 different on-shore locations advertised each season. This article advances and improves our understanding of the marine tourism industry and is vital for the management and planning of a sustainable tourism industry that ensures both respect of the northern ecosystems and environment and the rights and traditions of Indigenous northerners.
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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 | 0.001 |
| 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) | 0.000 | 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".