Bibliographic record
Abstract
Abstract In this article I examine why Vietnam, a state possessing neither nuclear weapons nor nuclear power plants, adopted nuclear security purely as a preventive measure against nuclear terrorism. Although nuclear security emerged as a norm specifically related to countering nuclear terrorism following 9/11, it has received diverse responses from states. Nuclear weapon states, and states that possess nuclear materials (encompassing the United States, Japan and Canada) have actively advanced nuclear security as they face the threat of nuclear terrorism. In contrast, states without nuclear power plants have been unwilling to do so as they do not identify nuclear terrorism as a national threat. However, among these states, Vietnam began to adhere to the norm in 2012, and by 2014 was even recognized as one of the most progressive states in the nuclear security field. Drawing on Vietnamese regulations, elite statements and interviews conducted with Vietnamese officials, I endeavour to show that Vietnam actively changed its stance after nuclear security began to be diffused as an independent norm, in isolation from the other nuclear norms it had previously been grafted onto. Further, I discuss the merits of these strategies as barriers and facilitators for norm adoption in the case of Vietnam.
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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 | 0.015 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.020 | 0.055 |
| Scholarly communication | 0.012 | 0.009 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.004 | 0.012 |
| 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".