Increasing Public Participation through Awareness Raising Activities: A Case Study in Trao Reef Marine Reserve, Vietnam
Bibliographic record
Abstract
In the last few decades, community-based management has evolved to become an effective approach in managing natural resources and solving environmental problems around the world. In this approach, stakeholder participation is considered as a very important factor contributing to the success or failure of the management effort. To promote and enhance stakeholder participation, awareness raising activities could be conducted in various innovative forms. This is clearly illustrated in the case of Trao Reef, a locally-managed marine reserve in central Vietnam. The paper reviews the management approach applied to Trao Reef, focusing on analysis of stakeholder participation. The high level of environmental awareness of the local community contributed to the successful outcome of the project. Many communication activities and awareness raising campaigns were organized within the community to get them involved in all steps of the management process. The project enhanced the marine resources and ecosystem health, and helped to build a more sustainable livelihood and living lifestyle for the local community. Trao Reef has become a role model for effective environmental management that harmonizes the socio-economic benefits of the local community and nature conservation.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 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".