Examining Stakeholder Perceptions Towards Sustainable Tourism in an Island Destination. The Case of Savusavu, Fiji
Bibliographic record
Abstract
Island destinations attract a significant number of tourists each year. Sustainability is imperative as islands are especially vulnerable to the negative impacts of tourism. The purpose of this study was to explore stakeholder perceptions towards the potential for sustainable tourism development in the island destination of Savusavu, Fiji. Using a stakeholder analysis approach, a qualitative study was conducted in 2014 and 2016 and consisted of 51 in-depth interviews. This study determined that the issues facing Savusavu, Fiji are the lack of infrastructure and support for the development of systems in relation to access, waste and wastewater management and the protection of the marine environment. This study recommends an increase in stakeholder education and participation in tourism-related decisions in Savusavu, Fiji. Implementing initiatives such as a voluntary fund, increased community capacity and appointing an environmental coordinator are suggested as methods to increase sustainable tourism.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".