Penerapan Pidana Tambahan Dalam Kuhp Baru: Kebiri Kimia Dan Publikasi Identitas Pelaku Percabulan Anak
Bibliographic record
Abstract
Several countries have implemented policies of chemical castration and the publication of the identities of child sex offenders as preventive measures and to protect the public. Chemical castration is applied in countries such as the United States, although its implementation varies depending on the laws of each individual state. In Poland, chemical castration is mandatory for offenders who have committed sexual crimes against children under the age of 15. South Korea also enforces a similar policy for offenders targeting children under the age of 16. Meanwhile, in Russia, chemical castration is carried out on a voluntary basis. On the other hand, the publication of offenders’ identities is also a form of additional punishment adopted in several countries. The United States has a Sex Offender Registry system that allows the public to access information about individuals convicted of sexual offenses. The United Kingdom applies the Child Sex Offender Disclosure Scheme, which permits authorities to disclose the identity of offenders to parents or concerned parties. Canada also allows the publication of offender identities for those considered high-risk, aiming to increase public awareness and vigilance.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.050 | 0.007 |
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".