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CRIMINAL LAW PROTECTION OF INDIVIDUALS FROM CYBERSTALKING

2024· article· en· W4406560047 on OpenAlex

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
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

VenueLEGAL ORDER History Theory Practice · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicStalking, Cyberstalking, and Harassment
Canadian institutionsnot available
Fundersnot available
KeywordsCriminologyCriminal lawLawPolitical sciencePsychology

Abstract

fetched live from OpenAlex

There is no doubt that crimes against individuals have a high degree of social danger, since they are aimed directly at causing harm to a person’s life, health, honor and dignity. Though in a rule of a law state, the protection of the individual is a paramount task, since a person, human rights and freedoms are the highest value in the state. The lack of norms ensuring the implementation of criminal liability for cyberstalking is in many ways an obstacle to the creation of a well-functioning mechanism for overcoming crisis phenomena in the criminal legal protection of individuals. The article examines the need to introduce criminal liability for cyberstalking in the Russian Federation. The authors analyze the norms of criminal legislation of foreign countries (India, Australia, USA, Canada, Germany), which provide liability for cyberstalking. Attention is drawn to the fact that the phenomenon under study carries a potential threat to the mental or physical state of the victim. In conclusion, the authors offer their vision of improving criminal legislation.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.972
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.001
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 head0.037
GPT teacher head0.314
Teacher spread0.277 · 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