Seychelles, a vulnerable or resilient SIDS? A local perspective.
Bibliographic record
Abstract
This article analyses perceptions of residents of the Seychelles in the western Indian Ocean in relation to a long-running debate over small island developing states (SIDS) as to whether they are vulnerable or resilient. The results of data obtained from 25 key informant interviews and 70 household surveys conducted in 2013 showed that respondents perceived their country to be both vulnerable and resilient. Moreover, the data revealed that the relationship between vulnerability and resilience was complex, and that five interpretations of that relationship were evident: conflict, compromise, complementarity, symbiosis and transformation. Also, the conceptual distance between the two terms – vulnerability and resilience – was shown to be closer than may be commonly assumed. Finally, the paper questions whether the debate over vulnerability versus resilience is rightly confined to SIDS or could be equally applied to other states.
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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 | 0.002 | 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 | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".