Understanding patterns of pleasure craft tourism in the Canadian Arctic and implications for safety management
Bibliographic record
Abstract
This study establishes an understanding of pleasure craft tourism patterns in the \nCanadian Arctic from 1990-2013 with a focus on the implications for safety. Two \nspecific objectives were fulfilled: 1. to develop an understanding of the pleasure craft \nvessel traffic and pleasure craft travel patterns, and 2. to develop an understanding of \nincidents, close-calls, and safety issues. \nPleasure craft tourism in the Canadian Arctic is a relatively new industry, \nalthough it is now the fastest growing marine sector. There is a lack of information on \nthese small vessels compared to larger expedition cruise ships that have been the focus \nof research and management concerns. The increase in pleasure craft traffic in the \nregion should raise concern about traffic patterns and safety of these tourists because they are traveling in a region with limited infrastructure, services, and search and \nrescue. Other issues that need examination are behaviour, monitoring, and control of \npleasure craft vessels, indicating the need for insight into vessel numbers, spatial \npatterns, and vessel preparedness. \nA literature review was conducted to identify the current state of pleasure craft \ntourism in the Canadian Arctic. This included identifying patterns of vessel traffic, \ndefining pleasure craft and the management context, as well as the management context \nof Antarctica and the European Arctic. The literature review concludes with the \nknowledge gaps related to pleasure craft tourism that drive this study. \nThis research takes a quantitative approach to understanding pleasure craft \nvessels in the Canadian Arctic. This study uses two main sources of data: the Pleasure \nCraft Dataset, developed specifically for use in this project; and, a database of Internet \nweb logs (Blog File) gathered for this research. The Pleasure Craft Dataset is comprised \nof information on pleasure crafts extracted from the NORDREG database (for the \npurposes of this research called the NORDREG pleasure craft data), a publicly available \ndatabase collected by the Canadian Coast Guard, and data on additional vessels found \nthrough a literature review and Internet searches. The first phase of this study involved \nthe analysis of the Pleasure Craft Dataset to explore spatial and temporal patterns. The \nsecond phase of this study used content analysis on blogs with material focusing on the \nexperiences of pleasure craft travelers in the Canadian Arctic. \nThe results show an increase in pleasure craft tourism in the Canadian Arctic, \nand a concentration of vessels and vessels days spent in the Northwest Passage while \ndemonstrating that not all vessels are reporting to NORDREG. Further, vessels days are \nnow greater on a per vessel basis than in the past. The results also indicate an increasing \nnumber in pleasure craft travelers overall and the advent of larger pleasure craft vessels \nto the region. Blog analysis was able to provide insight into pleasure craft travelers and \ntheir vessels, including aspects such as: sites visited, behaviour of travelers, and \ninteractions with the environment. The increase in vessel numbers, larger pleasure craft \nvessels in the region, and the spatial extension of vessel presence presents issues for management in the Canadian Arctic regarding growing pressure on infrastructure, \nservices, and search and rescue. \nThere is a need for further research on pleasure craft tourism in Arctic Canada. \nAdditional research should contribute to this sector of marine tourism by focusing on \nunderstanding management implications related to safety, insurance, behaviour \ncontrols and monitoring. There is also a need for research into pleasure craft tourism \nexperiences, the views of community members on the sector, and the role of individuals \nwho provide support to pleasure craft tourism formally and informally. There is also a \nneed for policies and guidelines to aid pleasure craft travelers, and quite possibly a \nneed for mandatory pleasure craft reporting to ensure appropriate monitoring and \nsupport.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".