Water, Livelihoods, and Migration in SIDS: Climate Change and Future Prospects for Carriacou, West Indies
Bibliographic record
Abstract
Caribbean Small Island Developing States (SIDS) are among the most vulnerable to climate change, which will have a disproportionate impact on local environments and economies. Whilst there is a growing literature on how Caribbean SIDS can adapt to become more resilient, an issue that has received little attention is with regard to migration as an unplanned response. It is recognised that events such as hurricanes and flooding can lead to internal relocation in the short term, but societal responses to droughts through migration have not generally been investigated. This paper seeks to address this by considering the case of the island of Carriacou, part of the state of Grenada. Carriacou, with its small population, limited land area, and local economy historically based on agriculture, has had a high degree of migration. This is in part a response to limited economic opportunities. Environmental stress, manifest through limited water availability, inappropriate land management, and social conditions, is likely to be exacerbated by climate change and variability. Resultant increases in the frequency and intensity of droughts, in the absence of proactive interventions, are likely to result in non-linear migration, both to Grenada itself and beyond.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".