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Record W3016465105 · doi:10.26710/jbsee.v6i1.1033

India's Military Procurement Programs & Economic Capacity: Compatibility & Pragmatism

2020· article· en· W3016465105 on OpenAlexaff
Romana Fahmeed, Syed Shahid Hussain Bukhari, Shakeel Ahmad

Bibliographic record

VenueJournal of Business and Social Review in Emerging Economies · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicIndian Economic and Social Development
Canadian institutionsMcGill University
Fundersnot available
KeywordsModernization theoryProcurementHegemonyPoliticsEconomic growthPolitical scienceEconomicsDevelopment economicsBusinessManagementLaw

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.674
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.075
GPT teacher head0.259
Teacher spread0.183 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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