The Influence Of Local Own-Source Revenue, Revenue Sharing Funds And Special Allocation Funds On GDRP In Pesisir Barat Districts Of Lampung Province
Bibliographic record
Abstract
Decentralization of policies provides great opportunities for regions to improve financial conditions. Efforts to increase regional revenues by paying attention to regional economic development, one of which is Regional Original Income (PAD), Profit Sharing Funds (DBH), Special Allocation Funds (DAK), and other legitimate income are other sources of income which are believed to encourage government to increase economic growth and community needs, especially the West Coast district. This research is quantitative descriptive in nature, with secondary data, Pesisir Barat Regency as the research observation area. The research was carried out with data from quarters 1 to 4 for 9 years time series from the period 2014: Quarter 1 - 2023: Quarter 4. The data is in the form of a timeseries so the methodology used is Ordinary Least Square (OLS) and Error Correction Model (ECM) . The research results show that regional original income (PAD) has a positive and significant influence on the long-term relationship with gross regional domestic product (GRDP), and does not have a positive and significant influence on the short-term relationship. Profit Sharing Funds (DBH) have a positive and significant influence on the long-term relationship with gross regional domestic product (GRDP), and have a positive and significant influence on the short-term relationship. Special Allocation Funds (DAK) have a positive and significant influence on the long-term relationship with gross regional domestic product (GRDP), and have a positive and significant influence on the short-term relationship.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".