Bibliographic record
Abstract
FTA is acting as a central axis to accomplish the worldwide trade liberalization as FTA has been globally spreading with competition. As the global economic depression and the trend of new protectionism are getting grave, and the trade liberalization of GATT and WTO is getting delayed, FTA is spread as an alternative. FTA is often called as RTA: Regional Trade Agreement(regional free trade agreement) which takes place mainly around the neighbor nations or regular districts, and these days, it is tending towards agreements between long distant nations, so, it’s not limited to the regular districts. Among the FTA agreement items, in addition to the customs abolition, the opening and investment liberalization of service market like finance, communication etc., intellectual property rights are included in the government’s target range. Korea also is actively proceeding FTA conclusion. Korean government has concluded the agreements with Singapore, european nations beginning from Chile concluded in 2003, and is proceeding more the negotiations with Japan, Canada, Mexico, India etc. Now in 2009, FTA of Korea-United States is actually waiting for just the passage of assembly ratification. But, if FTA becomes effective, because our domestic market should be entirely opened, it is expected that the blow against our domestic agricultural field which is weak, compared with that of the United States, a nation of worldwide agricultural products, is not an ordinary one According to it, we need a whole plan to cope with, so, the purpose of this study is to suggest the strategy by comparing and analysing the Korean agricultural competitive power, and to find the other development stratagem.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.063 | 0.036 |
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".