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REGIONAL INTEGRATION IN SOUTH ASIA: UTOPIA OR REALITY?

2022· article· en· W4313141532 on OpenAlexaboutno aff
Muhammad Tariq Niaz

Bibliographic record

VenueMargalla Papers · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicBelt and Road Initiative
Canadian institutionsnot available
Fundersnot available
KeywordsUtopiaRegional integrationPoliticsPolitical scienceSouth asiaQuarter (Canadian coin)PopulationDevelopment economicsGeographyEconomic integrationEthnic groupInternational relationsEconomyPolitical economyInternational tradeSociologyEthnologyBusinessEconomicsLaw

Abstract

fetched live from OpenAlex

South Asia comprises almost one-quarter of the world’s population. It faces a host of disputes of varying natures, including armed conflicts, proxy wars, and religious and ethnic strife. Despite its deplorable state of human security and impoverished people, South Asia is considered the least integrated region globally. Approximately 1.99 billion people suffer in terms of energy, food, water and health security due to conflicts and hostile interstate relationships. This paper analyses the socio-political and security environment of the region and explores the impediments to regional integration. Focusing on the South Asian Association for Regional Cooperation, it highlights that the idea of regional integration cannot be realized without resolving core issues. Economic cooperation between regional countries can only be achieved if integration models like the European Union and Association of South East Asian Nations are considered with necessary deviations. Bibliography Entry Niaz, Muhammad Tariq. 2022. "Regional Integration in South Asia: Utopia or Reality?" Margalla Papers 26 (1): 108-120.

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)0.002
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0020.008
Scholarly communication0.0070.008
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.066
GPT teacher head0.239
Teacher spread0.174 · 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 designQualitative
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

Citations3
Published2022
Admission routes1
Has abstractyes

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