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The Features of the Development of the Green Economy of the People’s Republic of China

2023· article· en· W4388493696 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

VenueBusiness Inform · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEnergy, Environment, Economic Growth
Canadian institutionsnot available
Fundersnot available
KeywordsGreen economyChinaGreen developmentGreen growthInvestment (military)BusinessEconomyEconomic systemEconomicsSustainable developmentPolitical sciencePolitics

Abstract

fetched live from OpenAlex

The article is aimed at assessing the current state of development of the green economy of China and providing recommendations for the development of the economy of such kind. As a result of the study, the definition of the «green economy» was analyzed, information was collected on the origins and development of the conception of the green economy, which covers economic, environmental, and social factors. The place of the People’s Republic of China among the selected countries (Canada, the USA, Germany, Japan, Turkmenistan, Ukraine) according to certain indicators of the green economy, in particular: CO2 emissions, the use of renewable energy sources, research and development costs, air pollution called PM2.5, total greenhouse gas emissions were substantiated. The article also compares the indicators of the green economy in the PRC with the average for all countries of the world. Recommendations for further development of the green economy in the PRC are provided, in particular, it concerns: increasing the volume of construction of environmental protection infrastructure and improving the environmental protection system; increasing investment in education and focusing on human capital; strengthening financial support for the green economy; improvement of the mechanism of patenting inventions and transformation of scientific and technological achievements; combination of the economic and the green development; deepening reforms and opening up to improve the quality of foreign investment. Prospects for further research in this direction are the assessment of the green economy of the PRC in the regional context on the basis of entropy along with systematization of existing indicators, as well as the construction of an own system of indices to assess the level of development of the green economy. Based on the calculated results of the assessment, it would be advisable to provide appropriate policy recommendations for each region of China in order to further develop the green economy.

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 score0.402
Threshold uncertainty score0.350

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.016
GPT teacher head0.188
Teacher spread0.171 · 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