Bibliographic record
Abstract
Multination states have been unstable. The presence of more than one group seeking status as a “nation” within the boundaries of a single state has given rise to strong tensions that have generally been difficult to overcome. The means by which these tensions are addressed and the instruments available for seeking compromises between states and such groups largely determine the extent to which violence can be avoided. In the worst cases, the world has witnessed long periods of violent conflict. The breakup of the former Yugoslavia and the subsequent war, as well as the long-standing conflict in Sri Lanka are two of the most glaring examples. More often than not, one group gains control of the state and imposes its own view of an overarching national identity. This is rejected by the other group, which sees itself as a distinct nation. The conflict often takes the form of a sub-state nationalist movement against the state, but in reality it reflects intense disagreements based on competing nationalist visions. While one group may make strong claims that the state represents a single nation that can be defined inclusively, it may clash with a group within the state that refuses to be encapsulated within that vision. As happened in Sri Lanka, such a single nation might even exclude a group entirely by defining itself in cultural, exclusivist terms.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.393 | 0.196 |
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".