Co-management in marine fisheries in Malalison Island, central Philippines
Bibliographic record
Abstract
This study, conducted from November 1995 to February 1996, describes the evolution and impact of fisheries co-management arrangements in a coral reef fishing village at Malalison Island, central Philippines. The island is the site of a community-based fishery resources management project of the Southeast Asian Fisheries Development Center Aquaculture Department, funded by the International Development Research Centre of Canada.Using a case study approach and inferential statistics in the analysis of data, the CD. management arrangements on the island are perceived to be successful based on equity, efficiency and sustainability criteria. Fishers, represented by the Fishermen's Association of Malalison Island (FAMI) who form the core group, participated actively in the management of fishery resources with legal and financial support both from the municipal and barangay (village) government. Potential problems nonetheless, still exist with the ambivalent attitude of fishers toward rule-breaking, especially of fishery rules directly affecting them. The future of co-management arrangements will largely depend on how the fishers and other stakeholders maintain and build earlier initiatives with the eventual phasing out of SEAFDEC AQD from the island. The rapid population growth could also affect project gains.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| 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".