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Record W2321924123 · doi:10.5509/2006793433

Can Japanese Foreign Aid to North Korea Create Peace and Stability?

2006· article· en· W2321924123 on OpenAlexvenueno aff
Marie Söderberg

Bibliographic record

VenuePacific Affairs · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicKorean Peninsula Historical and Political Studies
Canadian institutionsnot available
Fundersnot available
KeywordsStability (learning theory)Political scienceComputer science

Abstract

fetched live from OpenAlex

the end of the Cold War, whenever the prospect of a normalization of relations between and North Korea has been brought forward, foreign aid or the expectation of such aid has been mentioned as one of the central ingredients.1 It was also raised in the Pyongyang Declaration, issued in connection with the meeting between Japanese Prime Minister Koizumi Junichiro and Chairman Kim Jong II of North Korea in September 2002. This might be quite natural considering the immense economic need in North Korea. The fact that Japan, one of the world's largest donors of official development assistance (ODA),2 provides huge amounts of aid to most other Asian countries enhances these expectations; so do the large sums received by South Korea in connection with its normalization of relations with Japan. Peace building and peace preservation are new key concepts in Japanese foreign aid policy. According to the revised ODA Charter of 2003,3 Japan aspires for world peace ... actively promoting the aforementioned effort with ODA, which will carry out even more strategically in the future. Asia, and especially East Asia, is pointed out as a priority region. North Korea, with which has not yet normalized relations, is one of Japan's closest neighbours geographically, and from a logical point of view would therefore seem like an important starting point for the ODA effort. However, according to the main Japanese aid agencies, such as JICA (Japan

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.870
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.017
GPT teacher head0.237
Teacher spread0.220 · 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 teacher head, 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

Citations6
Published2006
Admission routes1
Has abstractyes

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