Selection of Appropriate Coastal Protection Strategies for Caribbean Coastlines
Bibliographic record
Abstract
The coastlines of the Caribbean are unique in many ways. Their warm waters and sandy beaches attract millions of visitors to their shores and these attributes provide an essential economic opportunity. Coastal hazards affecting the region include hurricanes, tsunami, and coastal erosion. For islands with mountainous interiors, development is often concentrated along the coastlines. This paper draws on more than 20 years of experience designing and evaluating coastal protection schemes in the region, and the related issues, constraints and opportunities are discussed. Projects in the Bahamas, St. Vincent, Guyana, Jamaica, and Barbados are cited and the reasons for their appropriateness to the region and specific locations are highlighted. The paper highlights the importance of multi-criteria analyses for coastal project selection and the need for funding agencies to insist on a thorough evaluation of options at the design stage. The unique nature of both the local and regional issues must be recognized and, as such, the design parameters used must have a Caribbean focus. Stakeholder consultation is an essential component of the design process and projects should be treated as an opportunity for socio-economic enhancement as much as possible. Eco-system based approaches should also be given due consideration. Experience has shown that the regulations and codes that govern coastal development need to be updated in most cases. Further, proper enforcement of these regulations will be key if Caribbean coastlines are to survive the next century of anticipated sea level rise.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".