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Record W3162580774 · doi:10.33002/jelp001.05

THE LEGAL REGULATION OF CLIMATE CHANGE IN UKRAINE: ISSUES AND PROSPECTS

2021· article· en· W3162580774 on OpenAlexfundno aff
Ievgeniia Kopytsia

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicUkrainian Legal and Forensic Studies
Canadian institutionsnot available
FundersUniversité de MontréalMitacs
KeywordsClimate changeLegislationPolitical economy of climate changePolitical scienceState (computer science)Adaptation (eye)National securityEnvironmental resource managementEnvironmental planningBusinessEconomic systemEconomicsGeographyLawEcology

Abstract

fetched live from OpenAlex

When the climate change is one of the most urgent, complex and challenging global problems of the present, threatening global economy and international security, it has to be primarily regulated domestically, at the level of a State. The present article aims to examine the current state of legal regulation of the climate change issues in Ukraine. Accordingly, the critical analyses of the national legislation on climate change regulation and whether it corresponds with the State policy’s strategic aims are conducted; the provisions of strategic documents on climate change adaptation and mitigation in Ukraine are examined and the evaluation of such regulatory mechanism’s efficiency and effectiveness is performed. As a result, the author points out the drawbacks of national policy and law encompassing the climate change and offers a set of suggestions for its improvement.

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)0.006
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.007
Scholarly communication0.0060.002
Open science0.0010.002
Research integrity0.0020.002
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 head0.026
GPT teacher head0.314
Teacher spread0.288 · 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
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

Citations8
Published2021
Admission routes1
Has abstractyes

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