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Record W4380521132 · doi:10.6000/1929-4409.2020.09.28

The Path of Peace as a Conflict Resolution of Ordinary Crimes in Criminology Perspective in Indonesia

2022· article· en· W4380521132 on OpenAlexvenueno aff
Agus Budianto

Bibliographic record

VenueInternational Journal of Criminology and Sociology · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicLegal and Social Justice Studies
Canadian institutionsnot available
Fundersnot available
KeywordsImprisonmentCriminologyCriminal justiceOvercrowdingConvictPrisonRestorative justiceLawSociologyPunishment (psychology)Political sciencePsychologySocial psychology

Abstract

fetched live from OpenAlex

A peaceful path as a conflict resolution against general criminal acts can be realized in the provisions of criminal reform in the 2014 RKUHP in Indonesia. however, this RKUHP has come into conflict with the public over several crucial articles, so that the President of Indonesia said to cancel the application in 2019. As a result, several general criminal offences are still being processed in the Criminal Justice System. This paper is the result of a juridical the sociological study, with the main data being primary in the form of interviews with several informants with non-random sampling technique and using a case approach and deductive analysis. The results showed that the use of imprisonment on defendants of criminal offences to provide a deterrent effect was wrong. The application of imprisonment does not change the convict for the better, coupled with the fact that prisons in Indonesia are entering an extreme overcrowding situation which then the density has an impact on the coaching program in Lapas not going well. One strategy to overcome these problems is by efforts to form and develop the concept of restorative justice.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.012
Scholarly communication0.0090.005
Open science0.0010.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.067
GPT teacher head0.372
Teacher spread0.305 · 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 designObservational
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

Citations2
Published2022
Admission routes1
Has abstractyes

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