The Evaluation of the 2nd Ocean Plan in Korea: Focused on the Implementing Power of the Plan
Bibliographic record
Abstract
There seem to be two types of ocean planning system in the world. First, the federal or united government suggests a basic framework of the plan which is followed by states, countries or areas as shown in the European Union, the United States, Canada, Australia, and so on. Second, a powerful central government prepares a basic ocean plan that guides the following sector plans of the relevant ministries. These cases are shown in Japan, Korea, and China. In Korea, the 2nd Ocean and Fishery Development Plan (OK21, 2011–2020) was made as a comprehensive ocean plan reflecting recent natural and social changes including global warming. The OK21 is declarative in its nature, and so evaluated by its sector plans, which have some specific implementing means such as budgets and manpower, organization, and so on, by the relevant laws. The 2nd OK21 is supported by 21 legally binding sector plans, 14 more than in the 1st plan, thus guaranteeing more effective implementation than in the 1st plan. In addition, most of sector plans are planned to be carried out through the well-coordinated system among the related ministries, thus showing a high degree of implementing efficiency of the plan. Every marine area in the plan, including marine environment, is being supported by more sector plans than before, indicating the equitable development of marine areas in the future. In sum, the 2nd OK21 is expected to show more implementing power due to the well-organized sector plans than in the 1st plan.
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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 | 0.026 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".