Peran Perspektif Gender dalam Penyusunan Kebijakan Pemidanaan: Studi Kualitatif terhadap Kasus Kekerasan Berbasis Gender
Bibliographic record
Abstract
Gender-Based Violence (GBV) remains a critical issue in Indonesia, with a significant increase in reported cases over the past five years. Despite the implementation of the Sexual Violence Crime Law (UU TPKS) as a progressive step toward victim protection, challenges persist in the law enforcement process, particularly in integrating gender perspectives into the criminal justice system. This study aims to analyze the role of gender perspectives in sentencing policies for GBV perpetrators in Indonesia and compare them with more progressive legal frameworks in other countries. Using a qualitative approach with phenomenological methods, the study examines national regulations, judicial decisions, and stakeholder interviews, including victims, law enforcement officers, and legal experts. The findings indicate that while the number of GBV cases reported has increased from 15,200 in 2018 to 35,200 in 2023, only 10% of reported cases resulted in convictions. This reflects systemic weaknesses, such as insufficient legal enforcement, limited gender-sensitive training among judicial actors, and societal stigma against victims. Additionally, comparative analysis with countries like Sweden and Canada suggests that more inclusive and restorative justice approaches can enhance victim protection and reduce recidivism rates. This study contributes to the discourse on criminal law reform by highlighting the need for stronger regulatory frameworks, improved law enforcement mechanisms, and technological innovations in reporting and case management. The findings provide policy recommendations for strengthening Indonesia’s GBV sentencing policies through a gender-sensitive and victim-oriented approach.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".