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International Legal Protection of the Atmosphere and Ozone Layer: the Continuation of the History

2022· article· en· W4205093653 on OpenAlexaboutno aff
Natalia Sokolova

Bibliographic record

VenueCourier of Kutafin Moscow State Law University (MSAL) · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicEnvironmental law and policy
Canadian institutionsnot available
Fundersnot available
KeywordsJurisdictionMontreal ProtocolConventionOzone layerInternational lawHarmAtmosphere (unit)Political scienceLawEnvironmental protectionEnvironmental planningEnvironmental scienceMeteorologyOzoneGeography

Abstract

fetched live from OpenAlex

The article examines the evolution of international legal regulation of atmospheric air from transboundary pollution over long distances both in connection with the formation of international judicial practice and a series of protocols that developed the 1979 Convention, specifying its content. On the one hand, we are talking about the search for criteria for fulfilling obligations through the concept of “critical load”. On the other hand, it is about clarifying substances and processes for which special regulation is introduced to increase the likelihood of preventing pollution.The protection of the atmosphere is also relevant to the protection of the ozone layer, provided not only through the fulfillment of obligations under the 1985 Convention, but mainly through the Montreal Protocol of 1987, which is achieved not only by more specific obligations, but also by a compliance procedure. If initially, within the framework of the international legal protection of atmospheric air and the protection of the ozone layer, the principles of international environmental law were only declared, then with the adoption of the protocols they received confirmation of their implementation. Strengthening such important principles such as no harm outside national jurisdiction, precaution, common but differentiated responsibility

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.975
Threshold uncertainty score0.981

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
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 head0.011
GPT teacher head0.199
Teacher spread0.188 · 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 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".

Quick stats

Citations2
Published2022
Admission routes1
Has abstractyes

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