Bibliographic record
Abstract
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
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".