Sunset Policy dan Implikasinya terhadap Peningkatan Penerimaan Pajak Penghasilan di Daerah Istimewa Yogyakarta
Bibliographic record
Abstract
Sunset policy is a policy which decreases the amount of administrative sanction in the form of interest. This policy is governed by Article 37A Act Number 28 of 2007. The target of sunset policy is the taxpayer who has good faith either to admit having insufficient payment of income tax or to have willed to register a tax file number (NPWP). However, the time of sunset policy is limited; it takes only 1 (one) year to apply the policy from 1 January to 31 December 2008. The research found that first, in tax law side sunset policy has the same legal meaning as kwijtschelding. The same legal meaning refers to the same characteristics found both in sunset policy and in kwijtschelding. Second, the internal target was not achieved until November 2008 as a result there was less contribution to the increasing amount of income tax revenue in DIY.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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; both teacher heads agree on what is shown here.
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".