Formulating Popular Policies for Peat Restoration Based on Livelihoods of Local Farmers
Why this work is in the frame
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Bibliographic record
Abstract
Important peatland issues developed were how to restore peatlands and followed by increasing rural livelihoods. This research aimed to analyze how peatlands can be utilized to alleviate poverty? and how to integrate peatland restoration with poverty alleviation. This research has been conducted in peatlands of OKI district, South Sumatra Indonesia in 2017. Data about bio geophysical aspects of peatlands, social, economic and political institutions of farmers were surveyed in the fields, performed in qualitative and quantitative approach, and analyzed in forms of tables and descriptions. Important themes have been discussed in formulating popular policies for peat restoration based on livelihoods of local farmers, among others poor groups; characteristics of farmers from the socio-political aspect; concept of peatland restoration and other lessons-learnt; compatibility of peat-based poverty alleviation; and need to improve policy making. The chronic poor sites tend to overlap with peatland degradation; it is more important to cultivate peatlands to prevent farmers from falling into deeper poverty than to reduce farmers out of poverty, and the intrinsic quality of peatlands and their contents tends to conflict with poverty alleviation goals, but there are some possible trends to minimize peatlands degradation and to alleviate poverty simultaneously. The best approach is to apply the 'win-lose' or 'lose-win' approach, even though we are not able to avoid peatland degradation at a zero level, but at least it can be inhibited. Cooperation between investors and farmers in managing peatlands is needed, so that the peatland resources are not completely degraded.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it