How Climate Change is Considered in Sustainable Tourism Policies: A Case of The Mediterranean Islands of Malta and Mallorca
Bibliographic record
Abstract
Mediterranean island case studies of Calvià, Mallorca, and Malta are used to examine how sustainable tourism policies do, do not, and should factor in climate change in order to reduce the vulnerabilities of the tourism sector to climate change. Data were collected from key actors responsible for policy implementation as well as tourism policy and planning documents from Malta's and Calvià's tourism industries. Tourism in both sites has significant vulnerabilities to climate change, but climate change was rarely stated as being an important tourism issue. That was the case even when policies include measures that contribute to climate change adaptation, although those policies were implemented for reasons other than climate change. Six policy suggestions are made for adapting to climate change in the case studies' tourism industries: Enacting effective control systems to ensure that policies are implemented and monitored; improving education and awareness on climate change and its potential impacts; placing sustainable tourism and climate change within broader policy frameworks; implementing economic incentives to encourage adjustment strategies; using accountable, flexible, and participatory approaches for addressing climate change in sustainable tourism policies; and filling in policy gaps while further integrating policies. Placing climate change into wider contexts reveals that some aspects of tourism might not be sustainable for small islands. Climate change should therefore be one dimension among many topics within sustainable tourism policies. That approach would provide impetus and support for pursuing strategies that should also be implemented for reasons other than climate change.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".