A framework for sustainable tourism in Pulau Banggi, Sabah : integrating biophysical and socio-economic considerations
Bibliographic record
Abstract
Ecotourism is often viewed as a sustainable form of tourism, but has the potential to impart negative environmental and social impacts if not well managed. When planning tourism, ex ante assessments can provide a contextual understanding of the ecological, economic, and socio-cultural forces that shape the prospects for sustainable tourism development. Underlying conditions can suggest 'limits' to acceptable change levels incurred by tourism development, which respect socio-cultural expectations and biophysical realities. Pulau Banggi is a relatively remote island on the brink of tourism development in the Malaysian state of Sabah. I conduct an ex ante biophysical study that evaluates how existing conditions of the island's marine biodiversity, seasonality, and infrastructure might influence options for sustainable tourism development. Through interviews, I also assess local residents' perceptions and trade-off preferences towards environmental and socio-economic change associated with tourism growth. I find that human expectations of economic benefits might demand tourism development on a scale not compatible with existing biophysical capacity. Persistent use of destructive fishing techniques, uncertainty over groundwater capacity, and inadequate waste infrastructure are major ecological constraints to growth. I conclude that prospects for sustainable tourism in Pulau Banggi can be enhanced through small scale development operating under a community based approach, and institutionalised within a Marine Protected Area framework.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.014 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".