Community-Based Mangrove Protection to Mitigate Climate Change: A Socio-Ecological Approach
Bibliographic record
Abstract
Protection of the mangrove ecosystem in the Climate Village Program (ProKlim) is a government effort to reduce climate change and reduce Greenhouse Gas (GHG) emissions from an ecological perspective.This study aims to analyze the protection of mangrove ecosystems based on community empowerment in the climate village program (ProKlim) in Pangkalan Jambi Village, Bengkalis Regency.The method used in this research is mixed method by combining quantitative and qualitative technique through observation and in-depth interviews.From the observation results, it was found that the condition of the mangroves in Pangkalan Jambi Village had been damaged.Based on interviews, it was found that community involvement was carried out with the concept of empowerment accompanied by PT.Pertamina Indonesia Refinery (KPI) Sungai Pakning, Bengkalis Regency Government and Riau Provincial Government so that the mindset of the people in Pangkalan Jambi Village, Bukit Batu District, increases positively in protecting the mangrove ecosystem.In protecting the mangrove ecosystem, real action is carried out through planning, implementing nurseries, planting and using technology by involving the community.The novelty of the paper lies in its novel combination of socio-ecological and mixed method approaches to highlight the importance of community-based conservation efforts in mitigating climate change impacts in a mangrove ecosystem protection.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".