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Record W7134505382

International experience of public involvement in the prevention of crimes against property

2015· article· W7134505382 on OpenAlexaboutno aff
С.Ю. Лукашевич

Bibliographic record

VenueInstitutional repository eNULAUIR of Yaroslav the Wise National University of Law (Yaroslav Mudryi National Law University) · 2015
Typearticle
Language
FieldSocial Sciences
TopicCrime Patterns and Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsEnforcementLaw enforcementProperty (philosophy)IdeologyRule of lawCivil law (Civil law)Criminal lawAlienation
DOInot available

Abstract

fetched live from OpenAlex

The right of property ownership belongs to one of the fundamental cornerstones of socio-economic rights of each individual. Owning property, using it legally, protecting ownership, a person plays its natural social nature. The presence of undoubted right of ownership and its legal protection, regardless of racial, ethnic, social, age, religious and ideological affiliation of a person is a sign of civil society and the rule of law. The right to property ownership, as well as other socio-economic inalienable human rights require constant and effective protection by law enforcement and others, including civil society mechanisms and institutions. Today, there are two General approaches to law enforcement and fight against crime, including against property. The first approach, which, in our opinion, can provide so called “approach of autonomy/professionalization of law enforcement” or “conservative” or “institutional-centric approach” based on the concentration of all functions to combat various types of crime purely within the powers and expertise of most law enforcement agencies, creating a certain condition of social alienation between the latter and the public sector. The second new approach, which is largely derived from long experience of law enforcement of European and North American countries and is considered more efficient and justified, could be called “dual” (double) or so, “which involves the cooperation of the public with law enforcement authorities in the fight against crime.” Based on the proven links between law enforcement agencies and the population, this experience can be divided, on the one hand, on activities that establish mechanisms and opportunities for bilateral or unilateral interaction between law enforcement agencies and the public. The first examples of measures can be considered public office constables in the UK, creating mini-stations in the USA and Canada (stations for the population in the city. Victoria British Columbia, Canada), the practice of foot patrol of the streets and whole areas (m. Newark state of New Jersey City). It should be noted that experts and researchers modestly and carefully evaluate the impact of public programs or initiatives neighbor observation. However, these initiatives have contributed to the reduction of burglary, theft and damage to rolling stock (vehicles) and real estate (houses, garages) property of citizens. Among the shortcomings of such programs is considerable passivity and indifference of the population. Thus, the modern sources of international law recognize the universality and social significance of ownership and the need for its protection. However, these sources of international law do not have any special legal and regulatory provisions regarding the mechanisms of public involvement in the prevention of crimes against property; the experience of joint participation of the public and law enforcement agencies in the prevention of crimes against property are selective national experiences of law enforcement systems and the public sector of some countries in North America and Western Europe, which should be considered in the broader context of the principles, mechanisms, approaches and institutions of the interaction between law enforcement agencies and the public in preventing and addressing a broader range of socially dangerous crimes.

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)0.003
metaresearch head score (Gemma)0.004
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: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.004
Scholarly communication0.0040.003
Open science0.0010.005
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0120.001

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 head0.108
GPT teacher head0.307
Teacher spread0.199 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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