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Record W3198892084 · doi:10.5539/jpl.v14n4p103

Criminal Profiling: Framing of Charges Upon Sexual Offences

2021· article· en· W3198892084 on OpenAlexvenueno aff
Muhamad Helmi Md Said, Haziratul Aqilah Huzailing, Vithiya Thevvi Paneerselvam, Sabrina Chu Soo Woon, Amir Redza Ahmad Fuad, Maryam Kamaruzaman, Maisarah Mustaffa

Bibliographic record

VenueJournal of Politics and Law · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicLegal and Social Justice Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCharge (physics)Criminal justiceCriminologyLawPolitical sciencePsychologyPhysics

Abstract

fetched live from OpenAlex

In criminal profiling in cases involving sexual offences, the charges must be drafted with a great degree of precision. Every sexual offence has its individual elements that need to be fulfilled before a charge is preferred. There are instances where the defects in charges are rendered to be fatal to the prosecution’s case and instances where Section 422 comes to aid and cures the irregularities in the charge. The objective of this research is to identify the common features that render a charge defective in cases related to sexual offences, the effect of the defects. It also aims to analyse the courts’ approach to determine whether the particular defect is fatal or curable and suggest solutions in handling defective charges to achieve the ultimate purpose of ensuring that justice is served and eliminating any prejudice towards the victim accused. Generally, charges for sexual offences are rendered defective when the charge fails to specify the kind of act which constitutes the alleged sexual act and the related provision. In order to achieve the objectives of this research, qualitative research was conducted through library research, case studies and data analysis. The possible solutions to handle a defective charge would be to determine whether a particular defect in itself would cause a miscarriage of justice by misleading an accused and stripping off the rights of the accused to defend himself. Since the purpose of a charge is mainly to notify the accused, as long as the defect in the charge did not mislead the accused in defending himself, the defects are considered mere irregularities.

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)0.012
metaresearch head score (Gemma)0.042
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 score0.014
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.042
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0090.006
Science and technology studies0.0140.021
Scholarly communication0.0110.017
Open science0.0020.014
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0060.001

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 head0.042
GPT teacher head0.336
Teacher spread0.294 · 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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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Same venueJournal of Politics and LawSame topicLegal and Social Justice StudiesFrench-language works237,207