Analisis Hubungan Pencegahan Korupsi dan Pajak Daerah di Indonesia Tahun 2018-2020
Bibliographic record
Abstract
Otonomi daerah bertujuan untuk memperbaiki perekonomian daerah agar terciptanya kesejahteraan masyarakat yang adil dan makmur. Namun kenyataannya sampai saat ini pemerintah daerah masih bergantung pada dana-dana transfer dari Pemerintah Pusat. KPK, melalui program Monitoring Center for Prevention (MCP), yang dikenal dengan sistem pencegahan korupsi berupaya agar Pemerintah Daerah mampu meningkatkan pajak daerah. Metode yang digunakan adalah regresi linier berganda dengan fixed effect. Hasil penelitian menunjukkan Sistem Pencegahan Korupsi yang diwakili dengan skor MCP memiliki hubungan yang positif dan siginifikan dengan pendapatan pajak daerah. Hal ini menunjukkan pentingnya sistem pencegahan korupsi di seluruh pemerintah daerah dengan melaksanakan good corporate governance
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.007 |
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 teacher head, 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".