Can ecotourism change community attitudes towards conservation?
Bibliographic record
Abstract
Abstract A basic tenet of ecotourism is to enhance conservation. However, few studies have assessed its effectiveness in meeting conservation goals and whether the type of tourism activity affects outcomes. This study examines whether working in ecotourism changes the perceptions of and attitudes and behaviours of local people towards the focal species and its habitat and, if so, if tourism type affects those outcomes. We interviewed 114 respondents at four whale shark Rhincodon typus tourism sites in the Philippines to compare changes in perceptions of and attitudes and behaviours towards whale sharks and the wider marine environment. We found that the smaller scale tourism sites had greater social conservation outcomes than the mass or failed tourism sites, including changes in conservation ethics and perceptions of and attitudes and behaviours towards whale sharks and the ocean. Furthermore, of the three active tourism sites, the smallest site, with the lowest economic returns and the highest negative impacts on whale sharks prior to tourism activities, had the largest proportion of respondents who reported a positive change in perceptions of and attitudes and behaviours towards whale sharks and the ocean. Our results suggest that tourism type, and the associated incentives, can have a significant effect on conservation outcomes and ultimately on the ecological status of an Endangered species and its habitat.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".