Bibliographic record
Abstract
China’s preliminary inclination was to promote nuclear proliferation as a way to undermine the military strength of the established world powers, but it quickly reversed its course in both rhetoric and action after its October 16, 1964, nuclear detonation at Lop Nor.1 China’s nuclear sharing poses a puzzle, because its development of its own nuclear arsenal seems to contradict its nuclear sharing policy. China’s nuclear sharing policy is liberal, whereas the development of its own nuclear arsenal is very conservative. The explanation is that China is taking a measured but considered risk by not building up sufficient force to ride out a US or Russian first strike. Instead, China is focusing its efforts and resources on economic development, and relying on inexpensive sharing to shore up allies on its periphery. China had generally colluded with the Soviet Union in restraining a North Korean nuclear arsenal, but its interest in maintaining a buffer has not led it to engage in more confrontational or rollback policies against North Korea’s nuclear arsenal. China has furthermore helped Pakistan’s and Iran’s nuclear prospects, and has apparently allowed North Korea and Myanmar to improve theirs. This sharing behavior with states on China’s periphery is prone to costly blowback, because all of these states have alternate allies (the US or Saudi Arabia for Pakistan, Russia for North Korea) and can therefore resist Chinese compellence.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".