Bibliographic record
Abstract
Coastal tourism is gaining recognition in public-sector planning as a means to stimulate economic development. This paper describes the extent to which this form of tourism is explicitly incorporated into Official Community Plans (OCPs). The research is built on the premise that tourism objectives in OCPs are more likely to be met, if tourism is recognized explicitly rather than implicitly. A combination of survey and content analysis techniques are used to identify coastal tourism’s recognition in OCPs associated with communities and regional districts within the Canadian Georgia Basin. A local government survey is used to identify planning perspectives surrounding tourism recognition in community planning. The findings from this phase of the research suggest that while a variety of tourism planning policies exist in the study area, OCPs represent the most comprehensive means of incorporating tourism concerns into regional and community initiatives. The content analysis focuses on identifying the level of presence of coastal tourism policies within a sample of coastal and inland community OCPs. This is done through the use of Tourism Recognition Factor (TRF) indices that determine the weighted incidence of explicit compared to implicit tourism policies in these OCPs. This phase of the research indicates that
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.847 | 0.667 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".