Federalism and the creation of new states : justifying internal secession
Bibliographic record
Abstract
This thesis addresses the creation of new states within federal arrangements – particularly federations - and their justification in liberal democratic contexts. It is presented as a set of three cumulative articles. The first article argues that existing liberal approaches to justifying secession have important shortcomings if they are to provide moral guidance to when internal secession is justified. In order to address this shortfall, the second article examines the process followed in three existing cases (the creation of Jura in Switzerland, Nunavut in Canada and Jharkhand in India) and how they were justified. Based on the process identified, the third article develops a procedural account of the grounds that may justify internal secessions. Overall the thesis argues that internal secessions should be negotiated between the secessionists, the existing unit they belong to, and the federation as a whole, delimited by the specific federal context in which they take place.
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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 | 0.012 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.027 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.004 | 0.005 |
| 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".