Bibliographic record
Abstract
Existing studies of secessionism focus predominantly on why these movements gain momentum and persist. A subset of work focuses on why secessionist tensions cease. We contribute to these latter studies by adapting the main theories developed to explain why secessionist agitation occurs, to account for abatement. We focus specifically on the island of Nevis in St Kitts and Nevis, a country that should be a “least likely” case for secession, given its small population, territory, and economy, yet has experienced secessionist agitation for much of the second half of the 20 th century. Since the late 1990s, momentum for secession has subsided. We explain why by reference to rationalist, culturalist and institutionalist arguments. We use an in-depth case study method, drawing on a range of sources, that foregrounds equifinality and concatenation across more than a century of inter-island politics. The findings suggest that all three types of arguments have some explanatory value but each fall short of fully accounting for the ebb and flow of secessionist dynamics. The findings may be of particular interest to multi-island states and territories in the Caribbean. They also offer practical lessons about the importance of policies that promote sectoral integration, encourage sociological linkages, and provide scope for dynamic political settlements.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".