Why Does a Border Dispute Exacerbate? Analyzing the India–Nepalese Escalation Over Kalapani Through Securitization Theory
Bibliographic record
Abstract
Kalapani is a strategic tri-junction valley between India, China, and Nepal, and is currently a territory of India. It consists of the Lipulekh pass, which connects to Tibet. The Kalapani area remains non-demarcated and disputed between India and Nepal. Nepal claims significant territory of the region. The border was created under the 1816 Sugauli Treaty, signed between the British East India Company and the Kingdom of Nepal, in which the River Kali is mentioned as the boundary. The treaty does not define the origin point of the river, with Nepal claiming Limpiyadhura as the origin point while India considers Lipulekh the origin point.A road was inaugurated by India on this route in May 2020. Subsequently, the Nepali government protested over the road and took several steps in retaliation. This escalation can be studied and understood from the confined frame of securitization theory, as devised by the Copenhagen school. The article does specifically focus on the role of the borderland population in the Kalapani region as both a securitizing and desecuritizing actor, and future securitization that may occur in Kumaun.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.015 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 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".