The Republic of Korea’s experience with an ocean dumping management system to enhance compliance with the London Protocol: highlights of major institutional history over 40 years
Bibliographic record
Abstract
Since the late 1980s, in efforts to reduce the burden of waste treatment on land and to protect the nation’s rivers, the Korean government has licensed dumping at sea only for waste difficult to treat on land. However, owing to the “not in my backyard” (NIMBY) phenomenon and the higher cost of land-based treatment, the amount of ocean-dumped waste has increased rapidly. The categories of waste dumped have also expanded to include sewage sludge containing highly concentrated hazardous substances, raising concerns about damage to the marine environment. The Korean Ministry of Oceans and Fisheries has noted that compliance with the London Protocol could be essential for limiting ocean dumping activities. The Republic of Korea enacted comprehensive measures to ensure compliance and formally acceded to the London Protocol in 2009. This paper presents Korea’s implementation of the criteria that led to the cessation of ocean dumping of sewage sludge in 2016.
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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 | 0.030 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.008 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".