Tourist Carrying Capacity Measures: Crowding Syndrome in the Caribbean
Why this work is in the frame
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Bibliographic record
Abstract
International tourism is increasing at an unprecedented rate. Understanding the variety of national and local impacts of this increase is of importance to a growing number of governments. Butler's resort cycle model (1974 Butler, R. W. 1974. “Problems in the prediction of tourist development: A theoretical approach”. In Studies in the Geography of Tourism, Edited by: Matznetter, J. 49–64. Institute for Economics and Social Geography Frankfurter Wirtschafts-Und. Sozialgeographische Schriften 17. [Google Scholar], 1980 Butler, R. W. 1980. The concept of a tourist area cycle of evolution: Implications for management of resources. The Canadian Geographer, 24: 5–12. [Crossref], [Web of Science ®] , [Google Scholar],; 1991) Butler, R. W. 1991. The resort cycle revisited—A decade of discussion. Paper presented at the Annual Meeting of the Association of American Geographers. 1991, Miami, Florida. [Google Scholar] provides for several long-term possibilities as to the relationship between crowding and growth. McElroy, de Albuquerque, and Dioguardi (1993) McElroy, J. L., de Albuquerque, K. and Dioguardi, A. 1993. Applying the tourist destination life-cycle model to small Caribbean and Pacific islands. World Travel and Tourism Review, 3: 236–44. [Google Scholar] focus on one of those possibilities. Specifically, using their penetration ratio, they predict that as tourist crowding continues for a group of Caribbean islands, the appeal of these islands decreases in the eyes of potential tourists and that, as time increases, the growth rate of the affected islands, actually decreases. Our article indicates that such a simple, straight-line relationship between increased crowding and a decrease in the rate of change may not be inevitable; indeed, diseconomies of scale may be avoided. The use of a curvilinear regression function reveals how both positive and negative scale economies existed in the Caribbean during the years 1992 through 1996.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it