Nuclear doctrines and stable strategic relationships: the case of south Asia
Bibliographic record
Abstract
This article offers a discussion of nuclear doctrines and their significance for war, peace and stability between nuclear-armed states. The cases of India and Pakistan are analysed to show the challenges these states have faced in articulating and implementing a proper nuclear doctrine, and the implications of this for nuclear stability in the region. We argue that both the Indian and Pakistani doctrines and postures are problematic from a regional security perspective because they are either ambiguous about how to address crucial deterrence related issues, and/or demonstrate a severe mismatch between the security problems and goals they are designed to deal with, and the doctrines that conceptualize and operationalize the role of nuclear weapons in grand strategy. Consequently, as both India's and Pakistan's nuclear doctrines and postures evolve, the risks of a spiralling nuclear arms race in the subcontinent are likely to increase without a reassessment of doctrinal issues in New Delhi and Islamabad. A case is made for more clarity and less ambition from both sides in reconceptualizing their nuclear doctrines. We conclude, however, that owing to the contrasting barriers to doctrinal reorientation in each country, the likelihood of such changes being made—and the ease with which they can be made—is greater in India than in Pakistan.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.018 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".