Bibliographic record
Abstract
Sub-state national groups usually seek some form of self-determination and recognition of their special status. Self-determination is sometimes expressed in calls for an independent state that would coincide with the territorial homeland of the nation. For the most part, however, such goals are unattainable. Instead, most groups settle for some form of autonomy or for federalism, where such structures already exist. Autonomy allows the accommodation of ethno-nationalist demands by creating a new territorial unit with special powers, or by decentralizing additional powers to an existing territorial unit that corresponds to the group's homeland (Gurr 2000; Horowitz 1985). Asymmetrical federalism accomplishes the same goals. Groups not only obtain political control over their territorial homeland, but also, with their control of a sub-state government, they obtain the leverage to negotiate with the central government. Autonomy also provides a territorially grounded recognition of national status, although this is mostly implicit. Many states are reluctant to formally recognize sub-state national groups as “nations.” The recent recognition of the Catalan nation by the Spanish state is a rare exception. Some states in Asia have recognized “multination” status but, as Laliberté and Thawnghmung have noted in the cases of China and Burma, they have, ironically, done so against a backdrop of strong centralizing tendencies and an actual denial of significant powers to accompany such recognition. This kind of recognition is typical of the Soviet-style model of recognition.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.009 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.002 |
| 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".