Pengembangan Kapasitas dalam Mendukung Pemerintahan Daerah yang Inklusif
Bibliographic record
Abstract
ENGLISHLocal governments have important role in achieving development goals. The government's limited fiscal capacity requires optimization of the role of society in development to build inclusive governance, by developing community capacity. The aim of this research is to provide input on the concept of strengthening capacity in forming inclusive regional government based on empirical studies been implemented. The approach taken was qualitative descriptive research with secondary data from previous research. The Prisma method was used in data mining and compiling analysis. From this research found that the key to successful capacity development support inclusive government system: providing assurance of a balanced and harmonious correlation between government and society, reducing level of affected communities and marginalized communities, building an environment that allows healthy competition and ideas’ variation, providing equal opportunities for citizens in accessing resources and actively participating in maturing political process, mobilizing respect human rights, freedoms and supremacy of law, enforcing behavior according to the code of ethics between civil servants and political leaders, strengthening public sector financial management, increasing institutional reform, and strengthening research capacity. Therefore, the entire process of formulating development policies needs also involving the community, be in line with community preferences, needs and expectations. INDONESIAPemerintah daerah memiliki peran penting dalam mencapai tujuan pembangunan. Keterbatasan kemampuan fiskal pemerintah, perlu optimalisasi peran masyarakat dalam pembangunan untuk membangun tata pemerintahan yang inklusif, dengan cara pengembangan kapasitas masyarakat. Tujuan dari penelitian ini adalah memberikan masukan konsep penguatan kapasitas dalam membentuk pemerintahan daerah yang inklusif dengan berdasarkan pada studi empiris yang telah dilakukan. Pendekatan penelitian adalah deskriptif kualitatif dengan data sekunder dari hasil penelitian sebelumnya digunakan. Metode Prisma digunakan dalam penggalian data dan penyusunan hasil analisis. Dari penelitian ini ditemukan bahwa kunci keberhasilan pengembangan kapasitas dalam mendukung tata pemerintahan yang inklusif adalah: memberikan kepastian terhadap korelasi yang berimbang dan harmonis antara pemerintah dan masyarakat, menurunnya tingkat masyarakat terdampak dan masyarakat termarjinalkan, membangun lingkungan yang membantun persaingan dan variasi ide secara sehat, memberikan kesempatan yang sama kepada warga negara dalam mengakses sumber daya dan berpartisipasi aktif dalam proses pendewasaan politik, memobilisasi penghormatan terhadap hak asasi manusia, kebebasan, dan supremasi hukum, menegakkan perilaku sesuai kode etik antara pegawai negeri dan pemimpin politik, memperkuat pengelolaan keuangan sektor publik, meningkatkan reformasi kelembagaan, serta penguatan kapasitas penelitian. Oleh karena itu seluruh proses penyusunan kebijakan pembangunan perlu juga melibatkan masyarakat agar perencanaan sesuai dengan preferensi, kebutuhan dan harapan masyarakat.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.047 | 0.008 |
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".