Barriers to the Implementation of the Articles of Continuing Acts in the Law of Criminal Acts of Corruption in Indonesia
Bibliographic record
Abstract
The problem that will be discussed in this paper is the problem of obstacles to eradicating criminal acts of corruption regulated in the Corruption Crime Act in Indonesia, which in its implementation is often associated with the existence of norms in Article 64 Paragraph (1) of the Indonesian Criminal Code which regulates criminal acts. (voorgezette handling) corruption in Indonesia. To overcome this problem, a search for documents and literature studies was carried out, a study of laws and regulations, including decisions on corruption cases that had existed, then carried out a descriptive analysis to solve the problem. The study results show that the obstacles in the application of Article 64 of the Criminal Code are related to continuing acts of corruption in Indonesia. First, the difficulty of separating a criminal act as a single offense if it is carried out by state officials who handle the same problem and project every time. Day; Second, it is often interpreted that the will's decision is an act of corruption itself; Third, the determination of material actions (feit materieele); and Fourth, continuous action is not only seen as a rule relating to the issue of the imposition of crime and the weighting of criminal acts.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".