Systemic Conditions and Security Cooperation: Explaining the Persistence of the Nuclear Non-proliferation Regime 1
Bibliographic record
Abstract
This article analyzes systemically the understudied topic of why and how the nuclear non-proliferation regime has remained a sustainable, even expanding entity, despite the unequal status of its members, and the fragility of international regimes as a species. The author argues that the convergence of two sets of distinct interests derived from the systemic roles and preferences of nuclear 'haves' and 'have-nots' has determined the creation and sustenance of the regime. For the nuclear-armed major powers the key factors that facilitate cooperation are the preservation of monopoly rights to possess nuclear weapons and the denial of similar rights to non-major power states. For most non-nuclear states, the regime's norms and principles render an important constraint against nuclear acquisition by their neighbors and a powerful normative restraint against nuclear use by the nuclear weapon states. This unique combination of interests and norms explains why the regime has persisted despite predictions of its demise. The larger theoretical implication is that favorable systemic conditions and system-induced interests have to be present in order for a multilateral security regime to emerge and persist. Conversely, when these favorable systemic conditions change, the regime is likely to weaken or dissipate.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.018 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 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".