Why Has the India-Pakistan Rivalry Been So Enduring? Power Asymmetry and an Intractable Conflict
Bibliographic record
Abstract
The India-Pakistan conflict is one of the most enduring rivalries of the post-World War era. Thus far, it has witnessed four wars and a number of serious interstate crises. The literature on enduring rivalries suggests that the India-Pakistan dyad contains factors such as unsettled territorial issues, political incompatibility, irreconcilable positions on national identity, and the absence of significant economic and trade relations between the two states, all cause the rivalry to persist. In this article I present a crucial neglected structural factor that explains the endurance of the rivalry. I argue that the peculiar power asymmetry that has prevailed between the two antagonists for over half a century has made full termination of the rivalry difficult in the near-term. Truncated power asymmetry is a causal factor in this rivalry's persistence, as rivalries between a status quo power and a challenger state that are relatively equal in their capabilities at the local level are the most intractable and nearly impossible to resolve quickly. The duration of many other asymmetric rivalries can also be explained using a framework of global superiority versus local parity in power capabilities that exist between the antagonists.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| 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".