Obligations to Protect and Preserve Marine Environment from Land-Based Sources of Pollution: A Case of the Indian Ocean in Tanzania
Bibliographic record
Abstract
Abstract The 1982 United Nations Convention on the Law of the Sea (UNCLOS) regulates marine pollution from land-based sources worldwide. It provides a comprehensive framework for the development of regional conventions and national laws addressing marine pollution from land-based sources. UNCLOS is closely tied to human rights treaties, since the environment and human rights are interconnected. This study examines Tanzania’s legal system and its adherence to international and regional commitments to protect the maritime environment. Based on a review of relevant documents, the study finds that Tanzania’s regulatory framework largely aligns with international and regional conventions on marine pollution from land-based sources. However, the study concludes that environmental pollution caused by land-based sources remains a significant concern in the Indian Ocean in Tanzania. This may be attributed to factors such as unplanned settlements, limited institutional capacity for waste management, inadequate fines for environmental offenses, insufficient enforcement of environmental regulations, and restricted locus standi. By addressing these shortcomings, Tanzania can better fulfill its obligations under international agreements to improve environmental protection and promote sustainable development.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| 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".