Governance Policy Sustainable Peatlands Through Community Economic Development in Bengkalis Regency
Bibliographic record
Abstract
Peatlands face considerable vulnerability to environmental conditions, posing a significant challenge to the economic well-being of local communities residing in these areas.Striking a balance between promoting the local economy and preserving the hydrological integrity of peatlands is crucial.This paper delves into the enhancement of a business model established through the Participatory Action Research (RAP) method, implemented in a 3 hectare pilot site currently undergoing monitoring and assessment.The findings from this monitoring and assessment phase will inform the second stage (loop) of the RAP process, facilitating refinements to the tested business model.Drawing insights from the Tanjung Leban Village in Bengkalis Regency, Riau Province, as a case study, it is deduced that a peatland-based commodity business model should incorporate pre-production activities.This precautionary measure aims to prevent peat subsidence and preserve the hydrological functionality of the area.Additionally, a temporal segregation of key activities (pre-production, production, and post-production) enhances the granularity of identifying required activities and resources.The study underscores the necessity of designing programs and interventions, such as peatland restoration initiatives, family welfare programs, and business incubator programs, with a focus on collective benefits for groups rather than individuals.To ensure an equitable distribution of benefits and costs among participants, program designers and implementers must carefully consider these dynamics.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 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".