Fiscal Decentralization and Community Participation in Education Services in Deli Serdang Regency, Indonesia
Bibliographic record
Abstract
The research aims to determine the community's participation in education services in Deli Serdang Regency and fiscal decentralization.This research is important and beneficial in identifying patterns and characteristics of income and expenditure in education services, exploring various types and patterns of community participation in education, and establishing the link between income and expenditure in education services and community participation in education in Deli Serdang Regency.The research used the constructivist Paradigm and a qualitative approach.The researchers gathered data through documentation technique, indepth interviews and discussions with various informants from the Regency, Regional People's Representative Council (DPRD), Sub-Regencies, Schools (elementary and junior high), and Community Figures.The research also gathered data through literature review, document study, and secondary data.The findings show that there is a financial imbalance between the Central Government and the Local Government, and horizontally between provinces and regencies/cities in Indonesia.Secondly, Deli Serdang Regency's Local Own-Source Revenue (PAD) is relatively high compared to other regencies in Sumatera Utara.However, the PAD has not optimized.Thirdly, the Expenditure in Education Services in Deli Serdang Regency for 2017-2022 is relatively stable.In addition, education Services allocated more funds to Indirect Expenditure (Operational Expenditure) than Direct Expenditure (Capital Expenditure).
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".