Bibliographic record
Abstract
In the contemporary world the mad nuclear arms race is high on the political agenda of most neo-cons, super-patriots, religious fanatics and arms dealers. Throughout the nuclear era, the conventional wisdom has been that one state’s nuclear acquisition has driven its adversaries to follow suit but it is not always the case and instead, the primary security factor driving nuclear weapons proliferation today is the disparity in conventional military power. This is likely to continue in the future, with profound consequences for which states do and don’t seek nuclear weapons. As proliferation begets proliferation, the analysis of reasons why states have sought nuclear weapons remained a central theme of the whole aspect. Several theories-traditional and modern, exist today with their arguments but no single theory is in a position to prove itself as the sole influencing factor which makes it difficult for academician and policymakers to forecast-why states start nuclear weapons programmes or refrain from it. With these facts and factors in the background the paper aims to analyze various existing motivational theories / influencing factors to provide new insight and to be helpful to analysts and policy makers who deal with potential current or future proliferating states. Only by knowing why states behave like they do, effective policies to influence this behaviour can be made.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.130 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".