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Record W3171296253 · doi:10.6000/1929-4409.2021.10.69

Restorative Justice as a Resolution for the Crime of Rape with Child Perpetrators

2021· article· en· W3171296253 on OpenAlexvenueno aff
Edhei Sulistyo, Pujiyono Pujiyono, Nur

Bibliographic record

VenueInternational Journal of Criminology and Sociology · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicLegal and Social Justice Studies
Canadian institutionsnot available
Fundersnot available
KeywordsRestorative justiceSanctionsCriminologyEconomic JusticePolitical scienceLawNormativeSexual violenceCriminal justicePsychologySociology

Abstract

fetched live from OpenAlex

A child who commits a criminal act can be called a child in conflict with the law. One of the crimes committed by children was rape, which involved elementary and junior high school children in Probolinggo; they reportedly raped a high school student until they became pregnant. Sexual crimes against children occur in Southeast Asian countries, such as the Philippines, Thailand, Sri Lanka, Malaysia, and Indonesia. The purpose of this study was to review restorative justice as an effort to resolve the criminal act of rape with child perpetrators. The research method used is normative juridical research, with the approach of laws and concepts and collecting primary legal material in the form of existing cases. This study found that the restorative justice process in juvenile crime is essential because there are essential things to focus on the regulation that requires the active role of the community, perpetrators, and victims of crime, including the affected community, in the restorative justice process. A fundamental balancing approach must also be taken, namely, first, imposing sanctions based on responsibility for recovering victims' losses as a consequence of criminal acts; second, rehabilitation and reintegration of actors; and third, strengthening community safety and security systems.

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)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.001
Science and technology studies0.0050.014
Scholarly communication0.0040.003
Open science0.0020.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0010.000

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 head0.058
GPT teacher head0.369
Teacher spread0.311 · 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 designTheoretical or conceptual
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

Citations7
Published2021
Admission routes1
Has abstractyes

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