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The Authority of Judges in The Application of Restorative Justice for Children in Indonesia

2025· article· en· W4416574082 on OpenAlexaff
Riska Ameliana Dewi, Nurini Aprilianda, Bambang Hery Mulyono, Randy Hilman Priadi

Bibliographic record

VenueJURNAL HUKUM DAN PERADILAN · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicLegal and Policy Analysis in Indonesia
Canadian institutionsInstitute on Governance
Fundersnot available
KeywordsRestorative justiceNormativeEconomic JusticeSupreme courtLaw enforcementEnforcementValue (mathematics)Procedural justice

Abstract

fetched live from OpenAlex

This study aims to analyze the authority of judges in applying the principle of restorative justice in cases involving children in conflict with the law and the obstacles to its implementation. The research approach uses a normative legal method with a legislative, conceptual, and case approach. Secondary data were collected through a review of six main laws, eight court decisions, and twenty-five related academic sources, then analyzed qualitatively using deductive reasoning. The results show that the authority of judges in applying restorative justice is based on the value of substantive justice as stipulated in Supreme Court Regulation Number 1 of 2024. However, its implementation is still hampered by regulatory inconsistencies between law enforcement agencies, a low level of understanding among officials and the public, and the absence of uniform technical guidelines. This study emphasizes the need for regulatory synchronization and capacity building among officials to ensure the effective and fair implementation of restorative justice oriented towards the best interests of children in Indonesia.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.022
metaresearch head score (Gemma)0.036
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.116

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.036
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0060.008
Scholarly communication0.0070.002
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.020
GPT teacher head0.358
Teacher spread0.339 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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