No island is an island: participatory development planning on the croatian islands
Bibliographic record
Abstract
This text provides an overview of the history of attempts to introduce participatory development planning on the Croatian islands.Within the study of islands, there has been little attention to islands in countries undergoing post-socialist transition.Similarly, within the study of post-socialist strategic development planning, there has been almost no attention to islands.This study addresses both the resilience of islands and their heightened susceptibility to change, borrowing a periodisation from political economies of contemporary Croatia which emphasise the signifi cance of multiple transitions.The text explores island development within socialist Yugoslavia, with islands subsumed within wider processes of industrialisation, urbanisation and, later, coastal tourism.As Croatia's independence was inextricably linked to war, a crisis-induced authoritarian centralism also mitigated against islanders becoming development subjects.The post-war picture, marked as it is by a slow process of integration into EU norms and practices, shows the gap between the legislative rhetoric and the on the ground practice of participatory development planning.The text concludes that, thus far, only the top down element of strategic planning in terms of island development has been implemented, and this itself in a distorted, contradictory, and highly inconsistent, way.
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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 | 0.014 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.016 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".