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DEVELOPING A METHODOLOGY TO ASSESS THE ENVIRONMENTAL AND ECONOMIC PERFORMANCE INDEX BASED ON INTERNATIONAL RESEARCH TO RESOLVE THE ECONOMIC AND ENVIRONMENTAL PROBLEMS OF UKRAINE

2018· article· en· W2906041952 on OpenAlexaboutno aff
Nadiia Shmygol, Olga Galtsova, Iryna Varlamova

Bibliographic record

VenueBaltic Journal of Economic Studies · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Business Development Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsSustainabilityContext (archaeology)Sustainable developmentIndex (typography)Developing countryCommissionEconomic indicatorBusinessResource (disambiguation)Environmental pollutionEconomic growthEnvironmental resource managementEnvironmental planningPolitical scienceEconomicsEnvironmental protectionFinanceGeography

Abstract

fetched live from OpenAlex

The urgency of the research. Developing a new approach to economic and environmental problems grounded on the need to form new awareness and responsibility makes it necessary to conduct an in-depth study of the causes and nature of such problems at the current stage of the national economic development. The problem of developing and substantiating indices in countries such as the United Kingdom, Canada, the United States, is decided by special institutes. At the international level, numerous agencies, organizations, and committees such as WHO, UN, UNESCO, OECD, the World Bank, the European Commission, the Committee on Environmental Modelling (ISEM) are addressing this issue. For a comprehensive assessment of the sustainability of development, take into account the socio-economic and environmental indicators, as well as separate a group of institutional indicators. But for Ukraine, it is impossible to identify the links that require more attention and material support for raising the level of development both nationally and globally. Consequently, the method of calculating the index of sustainable development, taking into account the peculiarities of the functioning of the national economy, needs to be reconsidered and improved. Target setting. Both the state and the enterprises ignored the issues of environmental pollution, which gradually led to a threatening situation for the economy and the environment. Meanwhile, in the current context, economic and environmental problems remain unresolved and are increasingly deepening. Uninvestigated parts of general matters defining. Analysis of the resource potential revealed the urgent need to develop a clear and functioning mechanism of economic and environmental development, shaping the ecological awareness of the nation as a whole, managers and policy-makers, improving and transforming the existing regulatory framework and environmental legislation, as well as the corporate environmental management systems, in particular, based on the environmental performance index. The research objective. The goal of this article is to study the nature of economic and environmental problems of the industrial enterprises and to develop a model of the regional environmental and economic performance index aimed at reducing the environmental costs of the economic growth, ensuring the environmental sustainability of the region, and mitigating the harms in terms of public health. The statement of basic materials. There is evidence proving that the economic problems are mainly caused by the lack of attention to environmental issues. It is proved that to resolve the abovementioned problems, first, there is a need to develop the national economic and environmental awareness based on the national context, using international standards and introducing the best practices of international organizations. Conclusions. Thus, the strategic approach to ensure the sustainable socio-economic development of the country from the standpoint of the economic and environmental model is a transition from the implementation of separate measures to the development and implementation of an economic and environmental concept of the comprehensive public production rationalization.

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)0.007
metaresearch head score (Gemma)0.013
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: Methods · Consensus signal: Methods
Teacher disagreement score0.015
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0150.012
Science and technology studies0.0010.001
Scholarly communication0.0050.003
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.284
GPT teacher head0.360
Teacher spread0.075 · 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
GenreMethods

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

Citations17
Published2018
Admission routes1
Has abstractyes

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