Lessons from the political economy of small islands : the resourcefulness of jurisdiction
Bibliographic record
Abstract
Preface: Introducing the North Atlantic Islands Programme H.Bagole & B.Lindstrom Editorial Acknowledgements G.Baldacchino & D.Milne Brief Notes on Contributors EDITORIAL INTRODUCTION G.Baldacchino & D.Milne PART I: SMALL ISLANDS IN CONTEXT Islands in Comparative Constitutional Perspective R.Watts Small Islands in the Global Kaleidoscope: The Politics of Localism B.Bartmann Identity, Culture and Self-Confidence in a New World of Old Possibilities H.Srebrnik PART II: CONSTITUTIONALISM AS AN ECONOMIC RESOURCE: ISLAND CASE STUDIES The Economic Costs of Divided Jurisdiction: the Canadian Island Provinces of Newfoundland and Prince Edward Island D.Milne The Jurisdiction of the Isle of Man: Catapult to Development W.R.McKercher Autonomy, Culture and Economic Development in the Aland Islands B.Lindstrom Constitutionalism and Economics in the Faroes A.Olafsson From Home Rule to Sovereignty: The Case of Iceland G.H.Kristinsson PART III: ORGANIZING FOR BUSINESS AND ECONOMIC DEVELOPMENT: SECTORAL PERSPECTIVES The Primary Sector: Problem and Opportunity for Islands R.Paterson Manufacturing Development on the North Atlantic Rim R.Greenwood & S.McCarthy Small Places, Big Ideas: Exporting Knowledge-Based Services from the Atlantic Periphery M.Shrimpton & C.Pollett Tourism and Cold Water Islands in the North Atlantic T.G.Baum with L.H.Grant, L.Jolliffe & B.Sigurjonsson Conclusion G.Baldacchino & D.Milne Subject and Author Index
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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 | 0.003 | 0.010 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.013 | 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".