Reassessment of Japan's Official Development Aid to Asia Pacific Developing Nations at the Start of the 21 Century
Bibliographic record
Abstract
In the last quarter of the 20 century, Japan s official development assistance (ODA), i.e. governmental transfers of financial resources to the developing part of the world, passed a long and spectacular way. The overall volume of financial flow from Tokyo to developing nations grew from $1, 148 million in fiscal 1975 to $14, 720 million in 1995 which meant an unprecedented 13-fold increase in 20 years; the record was beaten in 1999 when Japan dispatched to developing nations, mostly those which belong to Asia Pacific region, as much as $15, 320 million. Despite their huge volumes, Japans aid programs have never been immune from international criticism. In addition, in the previous decade they became increasingly disapproved of their inflexible and inefficient performance domestically, by Japans public opinion and mass-media. The reassessment of Japanese ODA's objectives, tools, and affordable volumes has led to an essential change which is presently underway. The paper aims to portray certain important changes in Japanese aids paradigm, such as: ⒜ serious quantitative and geographical transformation, ⒝ altering treatment of China as the key aid recipient, ⒞ growth of political incentives in aid-giving, and ⒟ increasing role of technical cooperation aimed at fostering foreign human resources.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".