Kontribusi Usaha Kambing Bligon Dalam Mewujudkan Ketahanan Pangan Berbasis Ternak Wilayah (Studi di Daerah Pesisir Kabupaten Bantul, DIY)
Bibliographic record
Abstract
ABSTRACT Bligon goats, as one of the local livestock resources, had significant potential to improved the welfare of coastal communities in Bantul Regency. The aim of the research was to analyzed the contribution of the viability of the bligon goat business in realizing food resilience, livestock empowerment, and the foundations of national resilience in the coastal areas of Bantul Regency. The research was conducted in Bantul Regency at two kapanewons which represent coastal areas, namely Sanden and Srandakan. This study used an approach to economic conditions over the past year. The calculations carried out included total production, added value, the function of livestock as savings, insurances and fertilizer producers. The average age of farmers in the research location was 53 years 10 months, with an average of 13 years of farming experience and an average of 7 goats. The results of calculating the Net Benefit-Cost Ratio (B/C), Payback Period (PP), and Internal Rate of Return (IRR) in calculating the financial feasibility of the Bligon goat farming business in coastal areas showed that this business was worthy of development. The development of Bligon goat cultivation could be used in efforts to alleviated poverty in the community and supported sustainable economic growth in the coastal areas of Bantul Regency. The sustainability of this economic dimension was expected to make a positive contribution to food resilience and national resilience by encouraging an increase in the number of farmers and goats.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".