Policy Implementation on the Rice of in Order to Increase Food Stock in Rembang District
Bibliographic record
Abstract
Food stock has become a concern of the Government since before the independence days. The Government always seeks to maintain food security so that the community would be sure needs their meal.The development of food security policy since the days of old order up to this time show the concentration of policies that are more or less the same, namely the availability of rice as a staple food. The purpose of this study is to: (1) decsribe and analyze the policy implementation on the rice availability in order to increase food security in Rembang District. (2) Describe and analyze what factors that support and hinder the policy implementation on the rice availability in order to increase food security in Rembang District. (3) Formulate a policy implementation model of rice availability in order to increase food security in Rembang for five years into the future. This research used a qualitative approach and including phenomenological research, with the research instrument of the researchers themselves. Data sources informants specified in purposive sampling, observation and documentation as well as supported by technical discussion. The results of this research indicate in general implementation of the food security policy in particular the rice availability in Rembang has not been implemented to its full potential, as well as the achievement of results. Rice availability policy implementation model proposed, namely: (1) increasing coordination with Regional food security Board optimization of Rembang, (2) Formulating policy areas which are more tangible, a clear change of degree movies, and the support of stakeholders be optimized especially from the head Area, (3) communication is increasingly clear through the medium of a simple but striking. (4) The structure of the organization or the bureaucracy that comes with it’s SOP.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".