Pengaruh Pendapatan Asli Daerah, Dana Bagi Hasil, Dana Alokasi Umum dan Dana Alokasi Khusus terhadap Belanja Daerah dan Pertumbuhan Ekonomi (Studi Kasus pada Kabupaten/Kota di Provinsi Kalimantan Selatan Tahun 2010-2019)
Bibliographic record
Abstract
This study was conducted to analyze the effect of PAD, DBH, DAU, DAK on Regional Expenditures and Economic Growth. This research was conducted in all regencies/cities in South Kalimantan Province within a period of 10 years, namely from 2010-2019. The data used is secondary data obtained from the Central Statistics Agency (BPS) and the website of the General Directorate of Balance (www.djpk.kemenkeu.go.id). The type of data studied is panel data with an analytical method that is path analysis. The results showed that PAD, DBH, DAU, and DAK had a significant effect on Regional Expenditures. PAD and Regional Expenditures have a significant effect on Economic Growth. Meanwhile, DBH, DAU, and DAK do not have a significant effect on Economic Growth. Regional Expenditures can be a mediator between PAD, DBH, DAU, and DAK on Economic Growth.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".