Bibliographic record
Abstract
Sino-Indian relations, which have long been fraught, took an especially adverse turn this summer with a military-to-military confrontation on the Doklam Plateau near the India-Bhutan-Tibet trijunction. After several weeks, Indian and Chinese forces withdrew from the region. However, neither side resiled from their respective territorial claims. This episode exemplified the troubles that have come to characterize the Sino-Indian relationship, especially since Prime Minister Modi assumed office in 2014. His regime, which is more nationalistic and reposes greater faith in the utility of force in international politics, had initially sought to diplomatically court the PRC in the hopes of improving their bilateral relationship. However, these efforts did not prove successful. Instead, the People’s Liberation Army, as in the past, continued to undertake limited probes along the Himalayan border, while the PRC continued to make diplomatic, commercial, and strategic inroads into India’s neighbours, trying to reduce India’s influence in those countries. The Modi regime, in turn, sought to counter these initiatives through various efforts of its own in the neighbourhood. Beyond South Asia, India has also sought to enhance its ties with Australia, Japan, the United States, and Vietnam in an attempt to hedge against the PRC’s growing economic and military assertiveness in Asia. These endeavours, however, have elicited hostile reactions from Beijing, which sees New Delhi as the only significant potential hurdle to the expansion of its influence in Asia. Despite Beijing’s adverse reactions it is unlikely that the current regime in New Delhi will scale back its efforts to cope with what it deems to be significant threats emanating from its behemoth northern neighbour.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.011 | 0.008 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.022 | 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".