India's Military Procurement Programs & Economic Capacity: Compatibility & Pragmatism
Bibliographic record
Abstract
In a world of Realpolitik, each state in the world always looks for increasing its power; some for the purpose of their survival and some seek to fulfill their hegemonic ambitions. Having a huge population, territory, economy, and military, the states like India usually desire to establish their hegemony; therefore, it is not surprising that India wants to achieve a Great Power status in world politics. Although India has great numbers in each area of strategic significance it lacks qualitative capacity in terms of military strength where the advanced weapon systems are the backbone of a country’s military power. In order to fill this gap, the Indian government has announced very ambitious military modernization programs and is concluding various military procurement programs around the world bearing huge costs while the big arms-exporting countries are getting involved in such ambitious military modernization programs of India. Over the past few years, it has been observed that the Indian economy has not been able to fulfill the costs of military modernization programs and the gap between the estimated costs of military procurements and the budget allocation is continuously increasing. Therefore, this study hypothesized that Indian military procurement programs and Indian economic capacity are not compatible with each other, which shall have perilous effects for the countries involved in such projects. This study provides an analysis of Indian economic growth and its comparison with the costs of India’s military procurements and finds that the stated hypothesis is correct to the extent of compatibility difference between the Indian economic capacity and military procurement cost.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".