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Record W2610875278 · doi:10.1080/10357718.2017.1317328

Explaining North Korea's Nuclear Ambitions: Power and Position on the Korean Peninsula

2017· article· en· W2610875278 on OpenAlexfundno aff
Nicholas D. Anderson

Bibliographic record

VenueAustralian Journal Of International Affairs · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicKorean Peninsula Historical and Political Studies
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaUniversity of International RelationsKorea International Trade AssociationYale University
KeywordsHegemonyPeninsulaArgument (complex analysis)Nuclear weaponPolitical sciencePosition (finance)Foreign policyPower (physics)Nuclear powerPolitical economyOrder (exchange)Development economicsInternational tradeGeographyLawSociologyEconomicsPolitics

Abstract

fetched live from OpenAlex

The USA has long called for the complete, verifiable and irreversible denuclearisation of North Korea. But is this a realistic policy option? In order to address this question, a broader question needs to be answered: What are the primary drivers of North Korea’s interest in nuclear weapons? Most answers to this question take one of two basic positions. ‘Doves’, on the one hand, see North Korea developing nuclear weapons because of the threatening foreign policies of the USA and South Korea. ‘Hawks’, on the other hand, see North Korean nuclear development as driven by factors internal to the North Korean regime, inherent in its personality. The author examines these two arguments against the evidence and finds them both wanting. In contrast, he puts forth an alternative argument focused on the power of the global hegemon, the USA, and its position on the Korean Peninsula. This power and positional alternative is shown to be better reflected in the evidence presented.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.007
Scholarly communication0.0030.002
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.034
GPT teacher head0.302
Teacher spread0.268 · 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

Citations20
Published2017
Admission routes1
Has abstractyes

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