Model Desa Berbasis Riset di Desa Kesongo Kecamatan Tuntang Kabupaten Semarang Miniatur Penyelenggaraan Pemerintahan di Indonesia
Bibliographic record
Abstract
In fact, villages are miniature government administrations in the daily lives of the community. Regional development problems are ultimately at the village level, encompassing issues such as citizen skills education, public services, community creativity, and innovation. This article was written to provide a research-based village model concept as a recommendation for a miniature village government administration. This study employs a qualitative descriptive methodology, which aims to comprehensively describe everyday phenomena by providing an accurate summary of the research object. Data collection was conducted through interviews, focus group discussions (FGDs), observation, and documentation studies. The location of this research is in the villages around Rawa Pening in Semarang Regency. The research analysis technique focuses on analyzing, describing, and summarizing qualitative data to gain a deep understanding of a phenomenon or social condition. The model of village and community governance is expected to generate resources, opportunities, knowledge, potential, and skills, thereby determining the future of development in their villages. Community empowerment continues to develop well with the synergy and collaboration of various stakeholders. Village empowerment is implemented in the innovation of the Research-Based Village concept; 1) compiling the history and potential of local village wisdom, 2) encouraging clean government and good governance in village governments, 3) encouraging the implementation of an Integrated Agricultural System, 4) providing support for the development of MSMEs, and 5) providing support for the Development of the Creative Economy and Circular Economy. The research-based village model is recommended for implementation in Central Java Province and Indonesia, taking into account the potential and local wisdom of each village, with the support of the local Regional Government.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".