Bibliographic record
Abstract
The relationship between the United States and China is an extraordinarily challenging one, giving rise to the American perception of a growing ‘China Threat’. Yet there is need for a careful reappraisal of the so-called ‘China Threat’. China is not only a trading partner of unparalleled importance, but an increasingly important political player, with influence in key areas of United States (U.S.) interest. A closer look at the domestic, cultural, and historical imperatives which shape Chinese foreign policy presents an alternative perspective of the China Threat. A re-interpretation of the China Threat would pave the way for increased U.S. influence in Chinese foreign policy, while reducing the likelihood of the worst of all possible outcomes: deteriorated relations and the possibility of open conflict between the two powers. The American government must use every tool at its disposal to ensure it can exert the maximum possible influence over the decisions and actions of the rising Chinese behemoth. Allowing a stark, black and white portrayal of the China Threat to fester will only restrict U.S. policy makers and increase the odds of negative outcomes.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.019 | 0.001 |
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".