Warm versus Cold Water Island Tourism: A Review of Policy Implications
Bibliographic record
Abstract
Not sun, sea, sand but ice, isolation, indigenous people: the critical exploration of extreme tourism in cold water locations has barely started. Cold water island locations tend to have harsh, pristine and fragile natural environments, characterized by wide open spaces. They become contexts for an exceptional and expensive form of vigorous, outdoor, adventure or cultural tourism, and direct encounters with nature. The nature and practices of the tourism industry suggest a more sustainable form of island tourism, very different from what is experienced on the warm, tropical and exotic island stereotype. This paper critically reviews some of the salient contrasts between the ‘hot’ and ‘cold’ versions of island tourism. It discusses how, on many ‘cold water’ island locations, sound strategic management, limited civilian ‘buy in’, low populations and an absence of pluralism in political life, can conspire with climate and relative inaccessibility to limit tourism to a small scale, lowimpact industry with a relatively high, locally-retained value added. Some ‘warm water’ islands are trying to follow this model for tourism development, with mixed results.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".