Enforcement of Illegal Fishing Laws that was Done by Foreign Ships in the Indonesian Sea Region, Viewed from International Sea Law
Bibliographic record
Abstract
This study aims to determine and examine the law enforcement of illegal fishing and the factors that inhibit law enforcement of illegal fishing conducted by foreign ships in the sea of Indonesia in terms of international maritime law. The type of research used by the authors in this study is a type of normative legal research. Normative legal research is done by examining the object of the form of legislation or legal norms applicable or applied to a particular legal problem. Concerning the type of research used the approach. The results showed that according to the 1982 International Maritime Law Convention (UNCLOS 1982) law enforcement of illegal fishing has been regulated in Article 73 UNCLOS 1982 while in the Indonesian National Law has been regulated in Article 69 Paragraph (4) law Number 45 of 2009 on Fisheries. Further obstacles to law enforcement are the impenetrable enforcement, lack of insight, and the integrity of law enforcement, and the lack of an active role and awareness of the community to assist law enforcement of illegal fishing in the Indonesian marine territory.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".