Enhanced <i>De Facto</i> Constraints Imposed by Non-legally Binding Instruments and Interactions with Normative Environment: An Analysis of the Joint Statements for the Conservation and Management of Japanese Eel Stock
Bibliographic record
Abstract
Abstract Since 2012, Japan, China, South Korea, and Chinese Taipei have consecutively held informal consultation meetings to discuss the conservation of Japanese eel stock. As a conservation and management measure, these participants adopted the Joint Statement in 2014 to regulate the initial input of Japanese eel seeds into aquaculture ponds. Despite the fact that the input limits were de facto constraints, these measures were implemented as domestic legal regulations in each participant's jurisdiction. This study examines the nature of the de facto constraints imposed by the Joint Statement for conserving and managing Japanese eel stock as a case study of stock regulations. This study further explores the possibilities of strengthening the de facto constraints through interactions with the normative environment; that is, the principle of sustainable development, domestic laws, and the relevant provisions in the United Nations Convention on the Law of the Sea (UNCLOS).
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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 | 0.011 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".