Bibliographic record
Abstract
For over a century, international lawyers have debated the right of a group to choose its sovereignty. The emergence of new states and self-determination movements after the Cold War has only intensified the disagreement over the status of a right to secede. I have sought in this book to shift the discussion from the articulation of the norm to the inevitable activity of interpretation. Whereas self-determination is routinely analysed as recognizing diversity through statehood, self-government and other forms of political organization, I have argued that the practice of its interpretation also involves and illuminates a more general problem of diversity raised by the exclusion of many of the groups that self-determination most affects from the making and the perspective of the norm. Distinguishing different types of exclusion and the relationships between them has revealed the deep structures, biases and stakes in the scholarship and decisions on self-determination. This framework of analysis has also revealed – perhaps more surprisingly – that the leading cases have grappled with these embedded inequalities. Through new readings of the cases, challenges by Islamic communities, colonies, ethnic nations, indigenous peoples, women and others to the culture or gender biases of international law have emerged as integral to the interpretation of self-determination historically, as have attempts by judges and other institutional interpreters to meet these challenges.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.122 | 0.039 |
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".