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Record W4407668014 · doi:10.25686/2306-2800.2019.4.34

ЭКОЛОГО-ЭКОНОМИЧЕСКОЕ РЕГУЛИРОВАНИЕ В ПРОМЫШЛЕННО РАЗВИТЫХ СТРАНАХ НА ПРИМЕРЕ США И КАНАДЫ

2020· article· ru· W4407668014 on OpenAlexaboutno aff
Д.Н. Ершов

Bibliographic record

VenueVestnik of Volga State University of Technology Economics and Management · 2020
Typearticle
Languageru
FieldSocial Sciences
TopicLegal and Regulatory Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsPhilosophy

Abstract

fetched live from OpenAlex

Материалы данной статьи представляют вторую часть исследований эколого-экономического регулирования в промышленно развитых странах (Вестник ПГТУ. Серия: Экономика и управление. 2019. 3. С. 5-21). На примере США и Канады показана трансформация эколого-экономического регулирования от отдельных не связанных между собой законодательных актов до использования системного законодательства и государственных институтов. Исследованы подходы к формированию государственной политики в сфере природопользования от простых ограничительных мер к комплексным мерам, включающим меры экономического стимулирования. Проанализированы факторы, влияющие на эколого-экономическое регулирование: исторические, научно-технические, технологические, социальные, информационные. Представлены основные черты современного состояния эколого-экономического регулирования и государственной политики в сфере природопользования и сформулированы выводы для России. Introduction. With the growing anthropogenic impact on the natural environment the urgency of the problem of reducing the environmental burden and rational nature management is increasing and requires the efforts of both individual countries and international structures. The mechanisms of environmental and economic regulation, which include restrictive measures as well as incentive measures, is an important element of the environmental policy of industrialized countries. The USA and Canada have undergone a long way in developing and improving the environmental legislation, and they have a significant experience in improving the mechanisms of environmental and economic regulation. This is of interest to Russia, where issues of creating conditions for harmonious nature management are in the process of formation. The study of international best practices can contribute to the development of a new state policy in the field of environmental and economic regulation and sustainable nature management. The goal of the study is to identify and analyze the factors that influenced the establishment, development, and improvement of environmental and economic regulation mechanisms as well as changes in US and Canadian public policies in the field of environmental management at different times. Analytical, historical, statistical, system-structural, and cause-effect methods were applied when performing the study. The research results are an ordered description of the development of mechanisms of environmental and economic regulation with an indication of the factors that influenced this development. The causal relationship that led to its current state was demonstrated. The expediency of studying international best practices and identifying ways to improve the mechanisms of environmental and economic regulation as well as state policy in the field of environmental management in general was justified. Conclusion. The experience acquired by the United States and Canada is of interest to Russia in terms of the processes of origin, development, and improvement of environmental and economic regulation mechanisms from simple tools to complex mechanisms within the framework of interconnected environmental legislation. This happened in the conditions of a gradual awareness by the society of the importance of environmental problems and an increase in the state priority of ecology. At present, Russian environmental policy is far from perfect and needs major review. The mechanisms of environmental and economic regulation, as part of the general state environmental policy, are irregularly applied and are not effective. It is necessary to move from the traditional sectoral approach to the creation of a comprehensive interconnected environmental legislation under which a modern effective system of mechanisms for environmental and economic regulation shall be formed.

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)0.004
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.988
Threshold uncertainty score0.104

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0050.008
Scholarly communication0.0130.007
Open science0.0010.004
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0310.013

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 head0.008
GPT teacher head0.174
Teacher spread0.167 · 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 designNot applicable
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".

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Citations0
Published2020
Admission routes1
Has abstractyes

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