ANALISA PEMBANGUNAN PARTISIPATIF DALAM MUSRENBANG-DES TAHUN 2017 DI GAMPONG PANGGONG KECAMATAN JOHAN PAHLAWAN KABUPATEN ACEH BARAT
Bibliographic record
Abstract
This research aims to find out how the implementation of participatory development and to know the factors that affect public participation Gampong Panggong subdistrict of West Aceh Regency Hero Johan. Methods used in this research is descriptive qualitative method where data is taken from interviews, field notes, documents, memos and other documents to get the proper interpretation. The results showed that overall the participatory development implemetasi in Gampong Panggong subdistrict of Aceh Heroes Baratmasih Johan less good, in this case only a part of the community that are involved in the planning development. This is due to social and economic factors which the community at large as a fisherman so just focus on the fulfillment of survival. In addition the implementation of planning construction of Gampong Panggong subdistrict of West Aceh Regency Hero Johan. dietemukannya multiple factors that affect the level of public participation in the planning of development in Gampong Panggong is the factor endowments include presence awareness, public participation, and support from the Government and society. While restricting factors include poor quality of education, low income levels, limited employment and diperdesaan.Keywords: Implemetasi, Participatory development
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 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".