Legal Reformation of Tax Court in Indonesia: Reforming Legal Culture, Institutional and Legislative Aspects
Bibliographic record
Abstract
This research is motivated by the many weaknesses that exist in the Ppajak court in Indonesia. Therefore, this research needs to be carried out with the aim that the tax court in the future will be better, more certain in law, and just. The problem is the reason for reforming the tax court in Indonesia and the way to reform the law on the tax court in Indonesia. The research method used is a statutory, historical, and comparative approach. The result of his research is that the tax court in Indonesia must be reformed because it contains many weaknesses. Furthermore, the findings show that tax court reform must be carried out from the aspects of legislation, institutional and legal culture. Based on the statutory aspect, synchronization of laws must be carried out. Based on the institutional aspect, institutional improvement must be carried out. Based on the aspect of legal culture, this must be done by increasing the morale of the parties. The novelty of this research is that the tax dispute settlement model is found after the tax court becomes a special court within the state administrative court. In conclusion, the tax court in Indonesia still contains many weaknesses, so it must be reformed immediately.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".