The Status of Durand Line under International Law: An International Law Approach to the Pakistan-Afghanistan Frontier Dispute
Bibliographic record
Abstract
The Durand Agreement, which gave birth to the Durand Line-the border between Afghanistan and Pakistan, is one of the most controversial issues for Afghanistan. This Agreement resulted in the annexation of a part of the territory of Afghanistan to British-India (now in Pakistan). Although, the agreement was concluded by the direct participation of the ruler of Afghanistan, the consecutive governments of Afghanistan, in particular, those after partition of British-India, refused to accept Durand Line as an international border. They asserted that the territory of Afghanistan extends beyond the Durand Line, thereby giving rise to a dispute with the neighboring state of Pakistan. What course of action should be adopted by the government and the people of Afghanistan within the contours of international law in order to resolve the border dispute with Pakistan is always being pertinent. This necessarily entails two significant arguments- (1) whether the disagreement over the Durand Border between Afghanistan and Pakistan falls in a “dispute” situation and (2) if there exists a legal dispute, how it should be settled. The paper, therefore, tries to examine above-mentioned arguments and suggests legal/practical solutions within the international law framework to prevent further conflict, thus taking a momentous pace towards regionalism.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.010 | 0.027 |
| Scholarly communication | 0.017 | 0.008 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".