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Analysis of development trends and structure of «green» investments in the world

2023· article· en· W4382397192 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueGalician economic journal · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Business Development Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsRenewable energyChinaSustainable developmentGreen economyBusinessInvestment (military)Work (physics)Green developmentNatural resource economicsEconomic growthEconomyEconomicsGeographyEngineeringPolitical science

Abstract

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The analysis of development trends and the structure of «green» investments of the countries of the world is a relevant topic in the modern world, since the «green» economy and sustainable development are among the main priorities of many states. In the scientific work, the main trends in the development of «green» investments in the world as a whole and separately in selected countries were analyzed, the regularities and peculiarities of their structure were revealed. The main focus of the research is on countries with a high level of development, dense population, as well as economies that are actively developing and that have serious problems with energy supply. Among such countries, we can highlight the USA, China, Japan, Germany, France, Great Britain, Canada, Italy, Spain, Australia, Brazil and others. It was determined that the dynamics of «green» investments in the world for the period 2011–2021 shows significant growth. In 2012, the total amount of «green» investment in the world was 254 billion USD, and in 2021 it will reach 2.5 trillion USD. The lion's share of «green» investments in the world is directed to the field of renewable energy, the second place is occupied by the production of electric cars, the third is energy efficiency, and the fourth is the protection of water resources. The priority directions of «green» investments are highlighted, in particular, renewable energy sources, energy-efficient technologies, environmentally friendly production, etc. Based on the results of the research, the main laws and trends of the development of «green» investments in different countries of the world were determined, as well as the peculiarities of their structure were revealed. Factors affecting the development of the green economy and «green» investments in the countries of the world, such as financial incentives, state regulation, technological progress, and increased public awareness of environmental issues, are also analyzed. The growing dynamics of the implementation of nature-based solutions at the global level was noted. The results of the research can be useful for developing strategies for the development of the «green» economy and «green» investments in different countries of the world, as well as for determining priorities in the development of environmentally friendly technologies and productions.

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.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.551

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.037
GPT teacher head0.241
Teacher spread0.205 · 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