Tourism economies and islands’ resilience to the global financial crisis
Bibliographic record
Abstract
The article is a comparative study of islands' reactions to the global financial crisis. The main aim is to identify conditions which influence how the effects of the crisis in the tourism sector differed between selected island territories. Seventeen island territories which rely on tourism were selected for analysis. Each reacted differently to the global financial crisis, especially with regard to changes in tourist movement, employment in tourism, and expenditure by foreign tourists. The factors analysed are: length of time as an independent state or dependent territory, degree of dependence on tourism, the diversity of the mix of foreign markets from which tourists arrive, level of dominance of the main foreign market, level of dependence on European and North-and South American markets, duration of flights from the main market, level of economic development, quality of life of the island area's residents, tourist expenditure, and changes in government expenditure on tourism. The statistical analysis was conducted using both the Spearman and the Kendall rank correlation coefficients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.011 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".