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FOREIGN EXPERIENCE OF CRIMINOLOGICAL PROTECTION OF JUSTICE

2023· article· en· W4365393478 on OpenAlexaboutno aff
Yuliya KHRYSTOVA

Bibliographic record

VenueNaukovyy Visnyk Dnipropetrovs kogo Derzhavnogo Universytety Vnutrishnikh Sprav · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicDigital Transformation in Law
Canadian institutionsnot available
Fundersnot available
KeywordsCriminologyEconomic JusticePolitical scienceSociologyPsychologyLaw

Abstract

fetched live from OpenAlex

The article summarizes the experience of the implementation of measures to protect justice from potential threats by authorized subjects and the peculiarities of their interaction in the USA, Canada, France, England, Wales and Italy in order to solve the issue of increasing the efficiency of the work of the newly created state body with law enforcement functions – the Judicial Protection Service of Ukraine, and as well as improving the order of its interaction with the National Police and other bodies of the Ministry of Internal Affairs of Ukraine. It is suggested, that the provision of criminological protection of justice should be understood as activities related to the formation of an effective system of countering criminogenic influences and criminal offenses against justice to ensure its independence and the practical affirmation of the principle of the rule of law during the implementation of judicial proceedings, in particular, regarding the granting of powers to the subject determined to ensure the security of justice to terminate and prevention of offenses and crimes; his interaction with other subjects in the system of combating criminal offenses against justice; early detection and countermeasures against possible threats. It was established that for improving the implementation of this criminological function in Ukraine, the foreign experience of involving private security companies in the practice of delegating the relevant powers to police officers, and the interaction of special authorized subjects of ensuring the security of justice are of interest and require further scientific research.

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)0.002
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.005
Scholarly communication0.0030.002
Open science0.0000.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0090.001

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 head0.109
GPT teacher head0.260
Teacher spread0.152 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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