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Environment in world politics: Challenges and prospects

2025· article· en· W4412663039 on OpenAlexaboutno aff

Bibliographic record

VenueInternational Journal of Arts Humanities and Social Studies · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPoliticsPolitical scienceEnvironmental ethicsData scienceComputer sciencePhilosophyLaw

Abstract

fetched live from OpenAlex

Protection of environment is a major issue in world politics. Environmental degradation, access to resources and their use, global warming, ozone layer depletion, climate change, sustainable development etc. are the major issues of world politics. Environmental crisis has affected the concept of security and has promoted geopolitical competition. The global environmental crisis can be resolved only through global cooperation. This is where the role of environment in world politics begins. Many efforts have been made at the global level to solve environmental problems. Major environmental conferences held at the global level include Stockholm Conference (1972), Montreal Protocol (1987), United Nations Conference on Environment and Sustainable Development or Earth Summit Rio de Janeiro (1992), Kyoto Protocol (1997), World Summit on Sustainable Development Johannesburg (2002), United Nations Climate Change Conference Paris (2015), etc. In this context, many thoughts and questions arise, such as; ‘what is the relationship between world politics and environment, How has the environmental crisis affected the global community, What efforts have been made towards environmental protection at the global level and what have been their achievements, What suggestions and recommendations can be made to solve environmental problems?’ An attempt has been made to solve these thoughts and questions in this research paper.

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)0.005
metaresearch head score (Gemma)0.003
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 score0.012
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0060.011
Scholarly communication0.0120.017
Open science0.0010.005
Research integrity0.0090.006
Insufficient payload (model declined to judge)0.0120.001

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 head0.091
GPT teacher head0.354
Teacher spread0.263 · 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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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