Effectiveness of Poverty Reduction Program with Value Added Creation in Agribusiness Sector and Formulation of Strategic Plan and Policies
Bibliographic record
Abstract
The purpose of this study is to formulate value creation models for agribusiness development to address rural poverty issues and analyze and design a Strategic (policy) model that should be developed for poverty alleviation in South Sumatra.The object of this study was conducted in Palembang City and Ogan Ilir Regency which identified the poor still relatively big. To measure the effectiveness of poverty alleviation programs that have been done by the government, conducted descriptive qualitative and quantitative analysis. Qualitative analysis is done by describing poverty alleviation programs that have been done, continued and will be done by the government together with other stakeholders. Further analyzed the problems or obstacles encountered in the implementation, formulation and develop a model of community empowerment that is considered effective enough to overcome poverty. The effectiveness analysis is calculated by comparing the planned targets with the results achieved.From the model formulated and built it is expected to obtain strategies and policies that can be taken by the government to overcome the problems of poverty both in the city and in the countryside.
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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 | 0.004 | 0.004 |
| 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 | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".