Changing paradigms in a changing climate: adaptive innovation towards forest management institutions to manage tropical forest in South and Southeast Asia
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Some communities in the tropics traditionally protect natural habitats for their cultural and \nmaterial sources, for example, in a form of sacred sites and as a communal forest. These \nnatural habitats play an important role in biodiversity conservation which maintain through \nindigenous institutions that do not require involvement of conservation organizations or \ngovernment bodies. These indigenous institutions regulate through customary laws and belief \nsystems led by community elders and traditional religious leaders. Evidence from our three \nresearch sites in south and south east Asia i.e., Matiranga in eastern Bangladesh, central \nMaluku in eastern Indonesia, and Palawan in the Philippines are presented here to highlight \non these accounts. We used different methods i.e., participatory rural appraisal, personal \nobservations, focus groups discussion and content analysis to elicit knowledge of the communities on how they conserve and manage their forests. Our result indicates that existing \nindigenous forest management institutions which are closely related to local people’s belief \nsystems served as enabling agents to manage forests. These belief systems play an important \nrole in monitoring of forest uses, and community leaders use to impose sanctions on the \ntransgressors. As a conclusion, reinforcing these indigenous institutions is one of the forest \nmanagement alternatives to mitigate future deforestation and degradation in the tropics. \nIndigenous management institutions can be strengthened by 1) backing their culture and \nconservation activities through giving recognition at government level, 2) establishing \nsustainable livelihood sources for communities living around the forests that can mitigate the \noverexploitation.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.002 |
| 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