An Evaluation of the Sustainable Community Development of Pig Farming, under the Serasah System, in Wonosobo Regency, Indonesia
Bibliographic record
Abstract
The purpose of this research is to evaluate the level of sustainability of pig farming,under the serasah system in Wonosobo Regency, Indonesia. This research is conducted in six villages located in the District of Kertek, the six village are Candimulyo, Candiyasan, Kapencar, Pagerejo, Purbosono, and Reco. The research’s activities are carried out in three phases: Preparation, data collection, and analysis. The preparation phase includes the collection of information from the reference sources required to initiate the research. The data collections’ phase, to obtain the primary data on theserasah system of pig farming, use the observation method, in-depth interviews and surveys via a questionnaire to identify the factors that contribute to the sustainability of pig farming within theserasah system. The in-depth interviews include talks with key figures in the villages’serasahpig farming system. The next stage is the processing of the data by analyzing every aspect of it. Based on the results of the assessment of the level of sustainability of pig farming in Wonosobo, the ecological aspect’s percentage is lower than that of the socio-economic aspects. The socio-economic aspects are showing progress towards sustainability, and the ecological aspects indicate they have made a good start towards sustainability. In other word serasah system pig farms have a good sustainability as farm business activities.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".