India in the Indian Ocean: Growing Mismatch between Ambitions and Capabilities
Bibliographic record
Abstract
Given the rise of major economic powers in the Asia-Pacific that rely on energy imports to sustain their economic growth, the Indian Ocean region has assumed a new importance. Various powers are once again vying for the control of the waves in this part of the world. This article examines the emerging Indian approach towards the Indian Ocean in the context of India's rise as a major regional and global actor. It argues that though India has historically viewed the Indian Ocean region as one in Which it Would like to establish its own predominance, its limited material capabilities have constrained its options. With the expansion, however, of India's economic and military capabilities, the country's ambitions vis-a-vis this region are soaring once again. India is also trying its best to respond to the challenge that growing Chinese capabilities in the Indian Ocean are posing to the region and beyond. Yet, preponderance in the Indian Ocean region, though much desired by the Indian strategic elites, remains an unrealistic aspiration for India given the significant stakes that other major powers have in the region.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.000 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".