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Record W3121990937 · doi:10.5539/ass.v9n7p54

India’s Foreign Policy towards Malaysia & Singapore: Evolution and Determinants

2013· article· en· W3121990937 on OpenAlexvenueno aff
Rashmi Sehgal, Zarina Othman, Nor Azizan Idris

Bibliographic record

VenueAsian Social Science · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicSocioeconomic Development in Asia
Canadian institutionsnot available
Fundersnot available
KeywordsSoutheast asiaForeign policyCold warDevelopment economicsPower (physics)ChinaEconomyPolitical scienceTigerGeographyHistoryEconomicsEthnologyPolitics

Abstract

fetched live from OpenAlex

This paper presents a review of the evolution of India’s relations with Southeast Asian countries, particularly Malaysia and Singapore. Over the centuries, India and Southeast Asia have shared history, culture and social values. As a result, the relationships between these two regions exhibit an evolving pattern. During the onset of the Cold War when the world had a bipolar system, India made some weak policy choices due to several factors which affected its relations with Southeast Asia adversely. However, after the end of the Cold War and fall of the Soviet Union, India felt a need to strengthen its ties with Southeast Asia and thus launched the Look East Policy. This paper traces the evolution of India’s foreign policy towards Malaysia through two defining periods – pre- and post-Cold War. An attempt is also made to explain this evolution and shift from time to time in India’s foreign policy towards Malaysia by highlighting the factors responsible for this. The paper makes important contributions by helping understand the trajectory of relations between India, a major regional power and Malaysia. This paper also briefly covers some historical importance of Singapore to India and Malaysia, since both Malaysia and Singapore are considered as two tiger economies in the Southeast Asian region.

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)0.000
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.020
GPT teacher head0.315
Teacher spread0.295 · 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
Published2013
Admission routes1
Has abstractyes

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