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Record W4380481942 · doi:10.6000/1929-4409.2020.09.223

Law Enforcement as Discretion and Legal Process

2022· article· en· W4380481942 on OpenAlexvenueno aff
Boris V. Makogon, Evgeniy V. Aristov, Evgeniy A. Chaban, Maxim V. Fedorov, Мадина Алиевна Умарова

Bibliographic record

VenueInternational Journal of Criminology and Sociology · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicPolicing Practices and Perceptions
Canadian institutionsnot available
Fundersnot available
KeywordsDiscretionEnforcementLawObjectivity (philosophy)Law enforcementProcess (computing)Legal researchBusinessPolitical scienceLaw and economicsComputer scienceSociology

Abstract

fetched live from OpenAlex

Coercive authority is central to the law inforcement, and the discretionary use of police authority is a decision-making process, as officers evaluate the situations in which they intervene and choose a course of action from among a set of alternatives. This article investigates the analytical and synthesis aspects of a wide range of sources, considering law enforcement from a dual perspective: as legal discretion and as a kind of legal process. This research applied the classical methodology of qualitative analysis of systems and processes, in particular, a system-analytical approach to the study of research objects. In conclusion, the role of law enforcement in the modern state-legal reality and the place of mandatory features of the legal process in the law enforcement structure is presented. Based on the study, it can be stated that The role of the procedural form is primarily that following its requirements will guarantee the objectivity and efficiency of law enforcement.

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 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)0.000
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 score0.513
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0010.000

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 head0.083
GPT teacher head0.430
Teacher spread0.347 · 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 teacher head, 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

Citations2
Published2022
Admission routes1
Has abstractyes

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