Autonomy in the Southern Borderland of Nepal: A Formula for Security or Cause of Conflict?
Bibliographic record
Abstract
Autonomous movements in southern Nepal have added a new layer of conflict to a volatile political situation. The Maoist armed uprising and pro-democracy movement that abolished the monarchy and initiated a republic unleashed sub-national aspirations for autonomy in the southern borderland region of Nepal. In this article, Madhesi autonomous sentiment in Nepal's southern borderland region is explored within the context of ethno-federalist concepts of the role of core ethnic identities and state stability as articulated by Hale and others. This inquiry is undertaken against the backdrop of Nepal's Constituent Assembly's (CA) failed efforts to draft a new constitution. Several key disagreements between the main political parties continue to be contentious and could undermine efforts to elect a new CA and restart efforts to draft a new constitution. Among the areas of contention are proposals to redraw internal political boundaries along ethnic lines and proposals to integrate proportional representation into Nepal's democratic system. Both of these proposals have significant implications for the power balance between the Madhesi of the Terai and the centre in Kathmandu. The article also explores post conflict concessions by the new democratic government and the role that they have played in both diffusing and exacerbating conflict in the Terai. The Terai borderland's role in Nepal's geopolitical position relative to India and China is also considered.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.016 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 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".