Reconstructing the Authorities of Investigators of the Financial Service Authority
Bibliographic record
Abstract
Objective: Reconstruction of the authorities of investigators of the Financial Service Authority (FSA) as special investigators is needed to shed light on special cases of economic crimes in the financial services sector. Method: For investigators in general, it is difficult to handle such cases which have so far been assigned to the Police institution which basically has the main task of protecting society and maintaining public order. This has affected the powerless image of the criminal justice system in Indonesia in meeting the expectations of consumers and justice seekers as well as supporting national economic growth in a sustainable and stable manner, as defined to be the objective of the FSA establishment. This research method is empirical. Result: The results of the study show that the KSP Indosurya case worth IDR 106 trillion ended in the imprisonment of the plaintiff's lawyer while the defendant was declared acquitted because the criminal case was decided to be addressed as a civil case. Of course, this problem was rooted in a misdiagnosis at the stage of investigation and prosecution. Conclusion: For this reason, there must be a special investigative institution to handle special cases that will screen economic crimes in the financial services sector before they are forwarded to the courtroom.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".