The Disparity in Criminal Prosecution against Acid Attack on Investigator of Corruption Eradication Commission: "Novel Baswedan” Case
Why this work is in the frame
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Bibliographic record
Abstract
This study aims to analyze the causes of the disparity in the criminal prosecution against acid attack. It is suspected that there has been a conspiracy of abuse of power between investigators and prosecutors, which reflects injustice in the criminal procedure law. This research clarifies a case study of the disparity of prosecution through mutually acknowledged norms and values. Case studies also enable the researchers to study the real thing, and gain a better understanding of what disparities in criminal prosecution. The result of the research showed that it was suspected that there had been a conspiracy of abuse of power between the investigator and the prosecutor, so that there was no justice for the victim. The researchers suggest limiting the prosecutors 'discretion and the existence of an independent institution for prosecutors' supervisory functions.
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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 | 0.002 |
| 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 it