The Challenges of Integrating Tourism into Canadian and Australian\nCoastal Zone Management
Bibliographic record
Abstract
This article discusses the challenges of integrating tourism into Canadian and Australian coastal zone management. Comparisons are drawn between coastal and marine tounsm resources in Australia and Canada. The resources considered include the cruise ship industry, recreational boating, fishing, sea kayaking, SCUBA diving and marine wildlife tourism. In the introduction, some of the problems of definition and data are addressed. Tourism is described as an industry, but unlike many traditional industries, the tourism arena consists of a myriad of players and sectors. After the comparison of tourism resources in both countries, the power and politics associated with managing user conflicts in marine areas in British Columbia and Australia are discussed. The third part of the article looks at the challenges of environmental management for coastal and marine tourism; specifically, the article focuses on issues arising from the creation of manne protected areas and the development of sustainable whale watching operations. The authors conclude with two case studies, the cruise industry in Pacific Canada and the recreational fishing industry in Australia.
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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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.012 | 0.004 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".