Bibliographic record
Abstract
Many of the world's islands are dependent on tourism as their main source of income. It is therefore imperative that these destinations are managed for long-term viability. The natural appeal of a destination is typically one of its main tourism related assets, yet the natural environment is also the feature most directly threatened by potential overexploitation. Sustainable Tourism in Island Destinations builds on existing literature in the subject by providing innovative discussions and practical management structures through the use of the authors' various island project work. An original feature is the focus on islands which are part of larger nations, rather than just on island sovereign states. Through an illustrated case study approach, the book focuses on the successes and challenges islands face in achieving sustainable tourism. The authors put forward innovative mechanisms such as multi-stakeholder partnerships and incentive-driven non-regulatory approaches as ways that the sustainability agenda can move forward in destinations that face specific challenges due to their geography and historic development. The case studies - from Canada, St Kitts, Honduras, China, Indonesia, Spain, Tanzania and Thailand - provide the foundation which suggests that alternative approaches to tourism development are possible if they retain sustainability as a priority.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.004 |
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".