Agroindustry Development Policy: A Strategy towards Poverty Alleviation
Bibliographic record
Abstract
The aim of this research is to explain poverty alleviation program through agroindustry development policy in East Kalimantan Repoblic of Indonesia. The main contribution of this research is to developed a new strategy toward poverty alleviation. The method of study was used descriptive-case study method. The data used in this research was gathered from many sources such BPS (Statistic Central Bureau), East Kalimantan Yearly Report, East Kalimantan Base Data, and some informants at provincial level. The poverty data, financial budget agro industry development project data, financial budget accelerate poverty alleviation data, empowerment people data obtained was analyzed by using time series analysis. The result indicated that the agroindustry development policy reduced poverty level. Since 2006 to 2015 was achieved significantly result with average of 0,57% per year. On the other hand, the number could have be improved it when migretion to the area had been reduced as in the same period.
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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 | 0.001 | 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 | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".