Traditional Knowledge of Homegarden-Dry Field Agroforestry as a Tool for Revitalization Management of Smallholder Land Use in Kulon Progo, Java, Indonesia
Bibliographic record
Abstract
Agroforestry homegarden-dry field are the last biodiversity resort of land management which synergizes the production and the conservation as well. Market orientation changes will encourage dry field homegarden monoculturization to be a threat. Based on these considerations homegarden-dry field has a degree of urgency for management revitalization to do. This study aims to determine the traditional knowledge of homegarden-dry field agroforestry management and its developer’s revitalization scheme. This research was conducted in Kulonprogo Regency, Java, Indonesia with three agroecological zones of the Kulon Progo Coastal Plain (cluster 1); Kulon Progo Plain (cluster 2) and Kulon Progo Hills-Mountains zone (cluster 3). The traditional practices that are developed in the agroforestry management can be seen from the space arrangement in the homegarden-dry fields that seems to be perfunctory. On its function connectivity there is an overlap among the cultivated species -trees and seasonal crops- but its productivity is low. However, crop and tree species diversity in agroforestry systems is higher compared to agriculture and forest crops. Based on these considerations then revitalization management of agroforestry homegarden-dry field (RMA-HD) is made by integrating in a single management unit. Through RMA-HD schemes, agroforestry in the outside part of the forest will have a new management approach, and may be promising for agroforestry reference in Indonesia, particularly for the pro-poor program which is compatible with the intensive smallholder management.
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How this classification was reachedexpand
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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".