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Record W2030400264 · doi:10.1177/0020702014540281

The India–Pakistan rivalry and failure in Afghanistan

2014· article· en· W2030400264 on OpenAlexafffund
John Mitton

Bibliographic record

VenueInternational Journal Canada s Journal of Global Policy Analysis · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicPolitics and Conflicts in Afghanistan, Pakistan, and Middle East
Canadian institutionsDalhousie University
FundersDalhousie University
KeywordsRivalryDominance (genetics)Competition (biology)Development economicsPolitical sciencePolitical economyPoliticsEconomicsLaw

Abstract

fetched live from OpenAlex

In discussions of NATO’s failure in Afghanistan, there is an increasing recognition of the damaging influence of competition between India and Pakistan. Yet, while reference to “rivalry” abounds, few authors connect Indian and Pakistani behaviour to the established literature on international rivalry. This paper corrects this explanatory gap by applying findings from the subfield of rivalry research. States engaged in rivalry behave differently; each issue of contention is fused into the broader rivalry relationship. For India, influence in Afghanistan is a component of its regional strategy, designed to maintain dominance over Pakistan in South Asia. For Pakistan, influence in Afghanistan is sought primarily for the opportunity to confront, damage, and frustrate Indian aims. The result is continued violence and instability. For policymakers, an appropriate appreciation of the strategic and political realities in a given region is a prerequisite for future international interventions in order to avoid such complications.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score0.099

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0090.008
Scholarly communication0.0050.002
Open science0.0000.004
Research integrity0.0010.002
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 head0.006
GPT teacher head0.310
Teacher spread0.305 · 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 designNot applicable
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
Published2014
Admission routes2
Has abstractyes

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