An Innovative Policy For Rural Development? Rethinking Barriers to Rural Communities Earning Their Living from Forests in Indonesia
Bibliographic record
Abstract
The government of Indonesia (GoI) has trialed a number of community forestry schemes, ranging from collaborative management to long-term forest management rights handed to local communities, and implements them in state forest land. This policy shift toward community forestry in Indonesia shows an emerging signal on acknowledgement on the ability of local forest users to manage forest resources sustainably,and gives the people opportunities to benefit from the resources and eventually improve their daily life. With so much of promises community forestry brings, this paper primarily asks why the program is yet to meet the high expectation of rural development, tackling the pervasive rural poverty. It aims to identify,analyze and address key constraints of rural communities in exercising their rights which are conside red as key factors to improve their live lihood and alleviate rural poverty. That the government-initiated community forestry schemes fall short of the initial targets in terms of the extent of state forest land areas managed by to forest communities to a large extent is explained bythe regulatory barriers of tenurial uncertainties and the complexlicensing procedures. Those coupled by the limited capacityas technical assistance rarely provided by government institutions appear to impede local people to secure better livelihood.Keywords: community forestry, livelihood, rural communities, poverty alleviation, regulatory barriers Inovasi kebijakan untuk pembangunan pedesaan? Mengulas berbagai hambatan masyarakat pedesaan untuk mendapat penghidupan dari dari hutan di IndonesiaIntisariPemerintah Indonesia telah meluncurkan berbagai program kehutanan sosial di kawasan hutan negara, mulai dari skema kemitraan sampai dengan pemberian hak kelola hutan bagi masyarakat lokal. Pergeseran paradigma kebijakan menuju kehutanan sosial memunculkan sinyal pengakuan terhadap kemampuan masyarakat lokal dalam mengelola hutan secara lestari, dan memberikan kesempatan bagi mereka untuk memanfaatkan sumberdaya hutan untuk memperbaiki kehidupan sehari-hari. Pertanyaan kunci yang diangkat dalam artikel ini adalah mengapa program kehutanan sosial belum mampu menggapai tujuan mulia untuk memerangi kemiskinan yang sangat akut di pedesaan sekitar hutan. Tujuan dari artikel ini adalah mengidentifikasi, menganalisis dan memecahkan berbagai hambatan yang dipandang sebagai faktor kunci bagi masyarakat pedesaan untuk memperbaiki tingkat penghidupan. Belum optimalnya berbagai program kehutanan sosial yang diluncurkan oleh pemerintah secara garis besar disebabkan oleh ketidakpastian tenurial dan prosedur perijinan yang sangat kompleks. Hal ini diperparah oleh terbatasnya pendampingan teknis yang pada akhirnya menghambat masyarakat pedesaan untuk menggapai penghidupan yang lebih baik.
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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 | 0.003 |
| 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 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| 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".