Rantau Baru Village: An Eco-Socio-Educational Model for Environmental Management in Fishing Communities
Bibliographic record
Abstract
Rantau Baru Village is a fishermen's traditional village located on the banks of the Kampar River.Because of the fish season and declining fish population, the fishermen's economy is currently unstable.In addition, the natural disasters caused by massive floods in the last 10 years, specifically also affected the fisherman's welfare.This study aimed to evaluate the ecological, social, and economic aspects of Rantau Baru Village before formulating an ecosocio-educational model in environmental management for the local fishing community.The research was performed through field observation and interviews.Eco-socio-education sustainability in environmental management was analyzed based on the Multidimensional Scaling (MDS) approach using the Rapid Assessment Technique for Fisheries (RAPFISH) program.An eco-socio-educational model was based on important variables in the Leverage of Attributes analysis.The eco-socio-educational model applied to environmental aspects, namely forest reforestation counseling, landscape rehabilitation, and environmentally friendly fishing gear; to social aspects, namely healthy living behavior, education on types of diseases, improvement of health facilities such as the provision of clean water, drinking water, and adequate public sanitation; to economic aspects, training and mentoring to business actors or micro small and medium enterprises, starting to introduce the development of ecotourism and fisheries tourism.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".