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Record W3169201865 · doi:10.6000/1929-4409.2021.10.92

Sentencing of Minor Offences in Indonesia: Policy, Practice and Reform

2021· article· en· W3169201865 on OpenAlex
Christina Maya Indah Susilowati

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Journal of Criminology and Sociology · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicLegal and Social Justice Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMinor (academic)Political scienceLawCriminologyPsychology

Abstract

fetched live from OpenAlex

This paper seeks to evaluate minor offenses in the Criminal Code in Indonesia. So far, the value limit for determining minor offenses in Indonesia is increasingly irrelevant to the value of the currency due to inflation. It will cause a gap in criminal law in dealing with changes. As the result, police will do unfair and non-humanistic law implementation. The objective of this study is to identify the importance of revising the lower limit of minor offenses in the Criminal Code in Indonesia. The study used a socio-legal method on the contextualization of Indonesian Criminal Codes related to the categorization of minor offense regulation in Government Regulation No. 2 of 2012 and in Penal Code, by utilizing a humanitarian perspective in law enforcement, especially by police who still charge some minor offenses with 5 years imprisonment. The results confirmed that some changes have been made related to this matter as the Indonesian Supreme Court has made some regulations, such as No. 2 of 2012 on adjustment in minor offense law. This means that all criminals doing minor offenses cannot behold as prisoners in the investigation or prosecution process. The main contribution of this study is to construct a perspective of legal and regulatory issues to emphasize a fair of justice in dealing with minor offenses with a model of humanistic law enforcement. The result is expected to practically contribute and recommend the importance of constructing fairness of justice principle in law enforcement in particular and of revising minor offense sentencing in general.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.589
Threshold uncertainty score0.480

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.054
GPT teacher head0.382
Teacher spread0.328 · 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