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Record W4392683375 · doi:10.1080/01495933.2024.2317254

Preparing for a two-front conflict: The role of the Indian Navy and the Indian Air Force

2024· article· en· W4392683375 on OpenAlexaff
Amit Gupta

Bibliographic record

VenueComparative Strategy · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicSouth Asian Studies and Conflicts
Canadian institutionsCanadian Federation of University Women
Fundersnot available
KeywordsNavyDoctrineModernization theoryChinaPaceFront (military)Political scienceDenialMilitary doctrineLawAeronauticsEngineeringGeography

Abstract

fetched live from OpenAlex

This article argues that while India is preparing for the contingency of a two-front war against China and Pakistan, its procurement and arms production policies make it problematic for the Indian Air Force (IAF) and Indian Navy (IN) to meet these challenges. IAF doctrine is not aligned to its current capabilities and is, therefore, largely speculative. Further, due to budgetary shortfalls in its modernization efforts, the IAF will find it difficult to fulfill its stated doctrinal role against China or Pakistan. On the other hand, the Indian Navy’s doctrine is better aligned with its objectives and capabilities. The IN can carry out its doctrine of sea control against the Pakistani Navy, but will have to adopt a sea denial posture against China because of the rapid growth of the PLA Navy’s force and capabilities. Given their slow pace of modernization, neither service will be able to decisively counter the Chinese military.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.090

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0170.018
Scholarly communication0.0110.004
Open science0.0010.006
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0050.000

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 head0.038
GPT teacher head0.342
Teacher spread0.304 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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
Published2024
Admission routes1
Has abstractyes

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