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Normative-regulatory compliance in industrial safety law: Comparative analysis and practical recommendations

2025· article· en· W7127135261 on OpenAlexaboutno aff
R. M. Sultanov, Albert Mufazalov, Arina Karataeva, Dmitry Manevich

Bibliographic record

VenueSpringer Link (Chiba Institute of Technology) · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicRegulation and Compliance Studies
Canadian institutionsnot available
Fundersnot available
KeywordsTransparency (behavior)Flexibility (engineering)Compliance (psychology)LegislatureContext (archaeology)State (computer science)Legislation

Abstract

fetched live from OpenAlex

The article is devoted to the analysis of the Theory of Regulatory Compliance in the context of Russian industrial safety legislation. A comparative analysis of the key principles of this theory and the regulatory acts in force in Russia, Germany, Canada, and Sweden has been conducted. The main issues of the Russian regulatory system have been identified, including excessive detail, a formal approach, and inconsistency in requirements. International methods, such as risk-based regulation, flexibility in regulatory requirements, and the development of self- regulation mechanisms, are discussed. The authors propose measures to improve the legislative framework, including eliminating the duplication of norms, introducing predictive risk assessment methods, expanding the powers of self-regulated organizations, and increasing the transparency of legal procedures. The implementation of these changes will improve the effectiveness of state control, reduce administrative burdens, and bring the Russian industrial safety system closer to international standards.

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)0.000
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 score0.879
Threshold uncertainty score0.693

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.060
GPT teacher head0.313
Teacher spread0.253 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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