Bibliographic record
Abstract
Abstract The post-Cold War international system, dominated by the United States, has been shaken by the relative downturn of the US economy and the simultaneous rise of China. China is rapidly emerging as a serious contender for America’s dominance of the Indo-Pacific. What is noticeable is the absence of intense balance of power politics in the form of formal military alliances among the states in the region, unlike state behaviour during the Cold War era. Countries are still hedging as their strategic responses towards each other evolve. We argue that the key factor explaining the absence of intense hard balancing is the dearth of existential threat that either China or its potential adversaries feel up till now. The presence of two related critical factors largely precludes existential threats, and thus hard balancing military coalitions formed by or against China. The first is the deepened economic interdependence China has built with the potential balancers, in particular, the United States, Japan, and India, in the globalisation era. The second is the grand strategy of China, in particular, the peaceful rise/development, and infrastructure-oriented Belt and Road Initiative. Any radical changes in these two conditions leading to existential threats by the key states could propel the emergence of hard-balancing coalitions.
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 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 | 0.001 | 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 | 0.003 | 0.004 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".